The 16th International Conference on...

Conference Programs

Conference Organizers

The University of

Technology Sydney

(UTS), Australia

Graduate School at Shenzhen, Tsinghua

University (GSST), China

Asia Pacific

Bioinformatics

Network (APBioNet)

Conference Sponsors

International Society for

Computational Biology

(ISCB)

Precision Medicine Research Center, Taihe

Hospital, Hubei, China

School of Public Health

(Shenzhen), Sun Yat-sen

University, China

School of Electrical and

Information Engineering,

Anhui University of

Technology, China

Graduate School at Shenzhen, Tsinghua University

(GSST), China

The University of Technology

Sydney (UTS), Australia

InCoB 2017

The 16th International Conference on Bioinformatics

September 20 to 22, 2017

The Graduate School at Shenzhen, Tsinghua University, China

Conference program InCoB 2017

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Table of Contents

Preface .................................................................................................................................................... 2

Schedules on Paper/Poster Presentations, Keynotes/Invited Talks, Panel, Reception and Banquet .... 3

Important Notes on Poster/Paper Presentation and File Format ......................................................... 3

Presentation Rooms and Map for Roads to Lunch Place .................................................................... 3

Program at a Glance (conference days 1, 2 and 3) ............................................................................. 4

Full Programs ...................................................................................................................................... 6

Day 1 Full Program (Wednesday, 20 Sept. 2017) ........................................................................... 6

Day 2 Full Program (Thursday, 21 Sept. 2017) ................................................................................ 9

Day 3 Full Program (Friday, 22 Sept. 2017) ................................................................................... 11

Keynotes and Invited Talks: Abstracts and Biography of Speakers ...................................................... 14

List of Best Paper Awards from BMC Track .......................................................................................... 25

List of Provisionally Accepted Posters .................................................................................................. 28

Conference Committees ....................................................................................................................... 29

Conference Venue ................................................................................................................................. 33

How to reach to Conference Venue for international participants? ................................................ 35

交通信息 for domestic participants ................................................................................................. 35

Sponsors ................................................................................................................................................ 36

Collaborating Journals........................................................................................................................... 37

Contact information .............................................................................................................................. 37


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Preface

The 16th

International Conference on Bioinformatics (InCoB 2017) has been taking place at

the Graduate School at Shenzhen, Tsinghua University, Shenzhen, China from September 20

to 22, 2017. InCoB is the annual conference of Asia-Pacific Bioinformatics Network

(APBioNet) that showcases the latest research and technologies in all areas of bioinformatics.

Since 2002, InCoB has been attended by practitioners from both biology fields and

computing backgrounds in the Asia-Pacific region, and also from other regions.

The theme for InCoB 2017 is: Big Data and Big Impact in Bioinformatics. Key topics include:

integration of algorithms for bioinformatics, translational bioinformatics, population genetics,

drug design and discovery, biomarker identification, systems biology, biological sequence

analysis, biomedical text mining, ontologies, expression data analysis, structural

bioinformatics, metabolism data analysis, imaging informatics and health informatics for the

understanding of complex biological and medical phenomena.

InCoB 2017 call-for-papers and call-for-posters attracted 168 submissions. We accepted 12

posters. We also accepted one paper and recommended it to be published by Bioinformatics

(subject to additional reviews), accepted 3 papers to be published by IEEE/ACM

Transactions on Computational Biology and Bioinformatics (TCBB), accepted 3 papers to be

published by Journal of Bioinformatics and Computational Biology (JBCB), accepted one

paper by PeerJ, and accepted 57 papers from the BMC track which will be published by

BMC Genomics, BMC Bioinformatics, BMC Systems Biology, or BMC Medical Genomics.

The program committee has conducted at least two rounds of rigorous reviews for all of these

accepted papers.

We were excited to have 8 keynotes and invited talks in the conference. The speakers are

Limsoon Wong (NUS, Singapore), Yong Hou (BGI-research, China), Jianzhu Chen (MIT,

USA), Saman Halgamuge (ANU, Australia), Xiujie Wang (CAS, China), Xinghua Shi

(UNCC, USA), Yuelong Shu (SYSU, China) and Alfonso Valencia (BSC, Spain). We thank

them very much for their generous time and significant contribution to the conference.

The conference was organized by University of Technology Sydney (UTS) and Graduated

School at Shenzhen, Tsinghua University (GSST). We would like to thank the sponsors for

their financial support, thank the Program Committee for their review comments, thank the

local organizing committee for their diligent work, thank all the authors for the participation,

and thank all other persons who have made contribution to the success of the conference.

Jinyan Li, Lan Ma (Conference Co-chairs)

Christian Schönbach, Siu-Ming Yiu, Tatsuya Akutsu, Paul Horton (PC Co-chairs)

September, 2017


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Schedules on Paper/Poster Presentations,

Keynotes/Invited Talks, Panel, Reception and Banquet

Important Notes on Poster/Paper Presentation and File Format

Time for the presentation of a paper is limited to 20 minutes only, including Q and A.

Punctuality of the start and ending time will be strictly implemented by the Session

Chairs which would provide a sound guarantee to the smooth running of the whole

conference program.

Time for the presentation of a keynote speech is 50 minutes, including Q and A.

Time for the presentation of an invited talk is 40 minutes, including Q and A.

Presentation file should be prepared as MS PPT or Adobe PDF.

Poster should be prepared in the size A0 (841 x 1189 mm).

Presentation Rooms and Map for Roads to Lunch Place

Main conference room – Conference hall at Level 2 of Building CII, Tsinghua

Graduate School campus.

Other conference rooms – Two class rooms at Building C (Building CI, level 1

seminar room 107 and Building CIII, level 2 seminar room 206), Tsinghua Graduate

School campus.

Road paths between conference site and lunch, reception place (Staff Restaurant, 快

乐时间餐厅)

Conference

site


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Program at a Glance (conference days 1, 2 and 3)

Conference Day 1

8:15 AM Registration at Building CII Ground Floor Foyer

9:00 AM – 9: 15 AM

Conference Opening Addresses and Welcome (GSST Dean, conference co-chairs and APBioNet President) Building CII, Level 2 Conference Hall Venue

9:15 AM – 10:45 AM

Keynote Speech and Invited Talk (Session Chair: Tatsuya Akutsu) Building CII, Level 2 Conference Hall Venue

10:45 AM Tea and Coffee

11:10 AM – 11:50 AM

APBioNet Annual General Meeting (President of APBioNet, and Shandar) Building CII, Level 2 Conference Hall Venue

11:50 AM – 12:30 PM Venue

3 parallel sessions for paper presentation RNA informatics Disease informatics Molecular sites prediction conference hall CIII, room 203 CI, room 107

12:30 PM Lunch and Poster/Trade Display Viewing (Staff Restaurant)

1:40 PM – 3:20 PM

Keynote Speeches (Session Chair: Shoba Ranganathan) Building CII, Level 2 Conference Hall Venue

3:20 PM Tea and Coffee

3:45 PM – 5:35 PM Venue

3 parallel sessions for paper/poster presentation Genomic informatics Molecular networks Target prediction and drugs Conference hall CIII, room 203 CI, room 107

5:35 PM Poster/Trade Display Viewing (staff restaurant)

6:00 PM Conference reception and dinner (staff restaurant)


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Conference Day 2


9:00 AM 10:30 AM

Keynote Speech and Invited Talk (Session Chairs: Ge Gao and Paul Horton) Building CII, Level 2 Conference Hall Venue


11:00 AM – 12:20 PM Venue

3 parallel sessions for paper presentation Biomarkers small RNAs Bioimaging and Classification Conference hall CIII, room 203 CI, room 206


1:30 PM – 3:10 PM

Keynote Speeches (Session Chair: Christian Schönbach) Building CII, Level 2 Conference Hall Venue


3:35 PM – 4:50 PM

Panel: Big Data Driven Bioinformatics and Precision Medicine: Status and Future (Tatsuya Akutsu, Saman Halgamuge, Paul Horton, Shoba Ranganathan, Christian Schönbach, Yuelong Shu, Alfonso Valencia, Xiujie Wang) Hospital’s compass and perspective (Liang Zhao) Session Chairs: Lan Ma and Jinyan Li Building CII, Level 2 Conference Hall

Venue

4:50 PM – 5:30 PM Venue

3 parallel sessions for paper presentation Integrative bioinformatics Proteome informatics Clustering algorithms Conference hall CIII, room 203 CI, room 206

5:50 PM Shuttle Bus to Kylin Villa for conference banquet

6:30 PM Conference banquet at Kylin Villa

Conference Day 3

9:00 AM – 10:40 AM Venue

3 parallel sessions for paper presentation Structural bioinformatics NGS informatics Ontology, text mining Conference hall CIII, room 203 CI, room 107


11:10 AM – 12:30 AM Venue

3 parallel sessions for paper presentation Systems biology Integrative bioinformatics Bio-discovery Conference hall CIII, room 203 CI, room 107


1:40 PM – 2:00 PM

Awards, InCoB 2018 presentation and Closing remarks (Conference co-chairs and APBioNet President)

Venue Building CII Level 2 Conference Hall


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Full Programs

Day 1 Full Program (Wednesday, 20 Sept. 2017)


9:00 AM – 9: 15 AM

Conference Opening Addresses and Welcome (Prof Guangzhi Xia, Associate Dean of GSST, conference co-chairs, and APBioNet President) Building CII, Level 2 Conference Hall Venue

9:15 AM – 10:45 AM

Keynote Speech and Invited Talk (Session Chair: Tatsuya Akutsu) Building CII, Level 2 Conference Hall Venue

9:15 AM Keynote Speech Advancing clinical proteomics via analysis based on biological complexes Limsoon Wong, National University of Singapore, Singapore

10:05 AM Invited Talk Single cell sequencing and its application in cancer research Yong Hou, BGI-Research, Shenzhen, China


11:10 AM – 11:50 AM

APBioNet Annual General Meeting (President of APBioNet, and Shandar) Building CII, Level 2 Conference Hall Venue

11:50 AM – 12:30 PM

3 parallel sessions for paper presentation (2 papers in each session)

Parallel session 1.1: RNA-sequencing informatics Chair: Yun Zheng

Venue Building CII, Level 2 conference Hall

11:50 AM CORNAS: Coverage-dependent RNA-Seq analysis of gene expression data without biological replicates; Joel Low, Tsung Fei Khang and Martti Tammi (Paper ID 9)

12:10 PM Biclustering of human tissue-specific circular RNAs reveals potential circRNA biomarkers; Yu-Chen Liu, Yu-Jung Chiu, Jian-Rong Li, Chuan-Hu Sun, Chun-Chi Liu and Hsien-Da Huang (Paper ID 71)

Parallel session 1.2: Disease informatics Chair: Paul Horton

Venue Building CIII, Level 2 Seminar Room 203

11:50 AM Tensor decomposition-based unsupervised feature extraction identifies candidate genes that induce post-traumatic stress disorder-mediated heart diseases; Y-H. Taguchi (Paper ID 2)

12:10 PM Hadamard Kernel SVM: Applications for Breast Cancer Outcome Predictions; Hao Jiang, Wai-Ki Ching, Wai-Shun Cheung, Wenpin Hou and Hong Yin (Paper ID 4)

Parallel session 1.3: Molecular sites prediction Chair: Shoba Ranganathan

Venue Building CI, Level 1 Seminar Room 107

11:50 AM Success: evolutionary and structural properties of amino acids prove effective for succinylation site prediction; Yosvany López, Alok Sharma, Abdollah Dehzangi, Sunil Pranit Lal, Ghazaleh Taherzadeh, Abdul Sattar and Tatsuhiko Tsunoda (Paper ID 3)


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12:10 PM Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions; Min-Gang Su, Julia Tzu-Ya Weng, Justin Bo-Kai Hsu, Kai-Yao Huang, Yu-Hsiang Chi and Tzong Yi Lee (Paper ID 20)


1:40 PM – 3:20 PM

Keynote Speeches (Session Chair: Shoba Ranganathan) Building CII, Level 2 Conference Hall Venue

1:40 PM Keynote Speech Drugs and the Brain: What can Analytics reveal in the Age of Data Engineering and Deep Learning? Saman Halgamuge, Australian National University, Australia

2:30 PM Keynote Speech Application of Informatics in Immunological Research Jianzhu Chen, MIT, USA


3:45 PM – 5:35 PM

3 parallel sessions for paper presentation (5 papers and one poster in each session)

Parallel session 2.1: Genomic informatics Chair: Paul Horton

Venue Building CII Level 2 conference Hall

03:45 PM 16sPIP: A Comprehensive Analysis Pipeline for Rapid Pathogen Detection in Clinical Samples Based on 16S Metagenomic Sequencing; Jiaojiao Miao, Na Han, Yujun Qiang, Tingting Zhang, Xiuwen Li and Wen Zhang (Paper ID 12)

04:05 PM PGAP-X: Extension on pan-genome analysis pipeline; Yongbing Zhao, Chen Sun, Dongyu Zhao, Yadong Zhang, Yang You, Xinmiao Jia, Junhui Yang, Lingping Wang, Haohuan Fu, Yu Kang, Fei Chen, Jun Yu, Jiayan Wu and Jingfa Xiao (Paper ID 16)

04:25 PM Subtype identification from heterogeneous TCGA datasets on a genomic scale by multi-view clustering with enhanced consensus; Menglan Cai and Limin Li (Paper ID 31)

04:45 PM GT-WGS: an efficient and economic tool for large-scale WGS analyses based on the AWS cloud service; Yiqi Wang, Gen Li, Mark Ma, Fazhong He, Zhuo Song, Wei Zhang and Chengkun Wu (Paper ID 63)

05:05 PM Classifying cancer genome aberrations by their mutually exclusive effects on transcription; Jonathan Dayton and Stephen Piccolo (Paper ID 97)

05:25 PM A Comparison Study for Supervised Machine Learning Models in Cancer Classification; Huaming Chen, Hong Zhao, Lei Wang, Jiangning Song and Jun Shen (poster ID 53)

Parallel session 2.2: Molecular networks Chair: Jiajie Peng


03:45 PM Refine Gene Functional Similarity Network Based on Interaction Networks; Maozu Guo and Zhen Tian (Paper ID 28)

04:05 PM Predicting binary, discrete and continued lncRNA-disease associations via a unified framework based on graph regression; Jian-Yu Shi, Hua Huang, Yan-Ning Zhang, Yu-Xi Long and Siu-Ming Yiu (Paper ID 43)


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04:25 PM CPredictor3.0: Effectively detecting protein complexes from PPI networks with expression data and functional annotations; Ying Xu, Jiaogen Zhou, Shuigeng Zhou and Jihong Guan (Paper ID 46)

04:45 PM Computational analysis reveals the coupling between bistability and the sign of a feedback loop in a TGF-β1 activation model; Huipeng Li, Lakshmi Venkatraman, Balakrishnan Chakrapani Narmada, Jacob White, Hanry Yu and Lisa Tucker-Kellogg (Paper ID 60)

05:05 PM Construction and analysis of gene-gene dynamics influence networks based on a Boolean model; Maulida Mazaya, Hung-Cuong Trinh and Yung-Keun Kwon (Paper ID 86)

05:25 PM Rapid Cluster Analysis of Wound Microbiota; Timothy Chappell, Shlomo Geva, James M Hogan, Flavia Huygens, Wayne Kelly and Dimitri Perrin (Poster ID 135)

Parallel session 2.3: Target prediction and drugs Chair: Shandar Ahmad


03:45 PM A novel algorithm for finding optimal driver nodes to target control complex networks and its applications for drug targets identification; Guo Weifeng, Zhang Shaowu, Shi Qianqian, Zhang Chengming, Zeng Tao and Chen Luonan (Paper ID 14)

04:05 PM A linear programming computational framework integrates phosphor-proteomics and prior knowledge to predict drug efficacy; Zhiwei Ji, Bing Wang, Ke Yan, Ligang Dong, Guanmin Meng and Lei Shi (Paper ID 23)

04:25 PM A computational model to predict the best orange-derived adjuvants in vaccination strategies against Human Papillomavirus; Marzio Pennisi, Giulia Russo, Silvia Ravalli and Francesco Pappalardo (Paper ID 45)

04:45 PM Pharmacophore anchor models of flaviviral NS3 proteases lead to drug repurposing for DENV infection; Nikhil Pathak, Mei-Ling Lai, Wen-Yu Chen, Betty-Wu Hsieh, Guann-Yi Yu and Jinn-Moon Yang (Paper ID 50)

05:05 PM Dependency-based long short term memory network for drug-drug interaction extraction; Wei Wang, Xi Yang, Canqun Yang, Xiao-Wei Guo, Xiang Zhang and Chengkun Wu (Paper ID 89)

05:25 PM High performance computing for accelerating a next-generation sequencing-based clinical pathogen identification pipeline; Haoran Ma, Tin Wee Tan and Kenneth Hon Kim Ban (Poster ID 62)

5:35 PM Poster/Trade Display Viewing (staff restaurant)

6:00 PM Conference reception and dinner

8:00 PM Day 1 program close


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Day 2 Full Program (Thursday, 21 Sept. 2017)


9:00 AM 10:30 AM

Keynote Speech and Invited Talk (Session Chairs: Ge Gao and Paul Horton) Building CII, Level 2 Conference Hall Venue

9:00 AM Keynote Speech Using Bioinformatics to Identify New Regulatory Mechanisms Xiujie Wang, Chinese Academy of Sciences, China

9:50 AM Invited Talk An Integrative Approach Toward Predictive Modelling for Big Data Genomics Xinghua (Mindy) Shi, University of North Carolina at Charlotte, USA


11:00 AM – 12:20 PM


Parallel session 3.1: Biomarkers Chair: Tatsuya Akutsu


11:00 AM ezTree: an automated pipeline for identifying marker genes and inferring phylogenetic relationships for uncultivated prokaryotic draft genomes; Yu-Wei Wu (Paper ID 17)

11:20 AM Identification of prognostic signature in cancer based on DNA methylation interaction network; Weilin Hu and Xionghui Zhou (Paper ID 19)

11:40 AM Detecting Causal Gene Regulations from Short Time-series Data Based on Prediction of Topologically Equivalent Attractors; Ben-Gong Zhang, Weibo Li, Yazhou Shi, Xiaoping Liu and Luonan Chen (Paper ID 21)

12:00 PM MultiDCoX: Multi-factor Analysis of Differential Co-expression; Herty Liany, Jagath Rajapakse and R. Krishna Murthy Karuturi (Paper ID 49)

Parallel session 3.2: small RNAs Chair: Christian Schönbach


11:00 AM A survey on cellular RNA editing activity in response to Candida albicans infections; Yaowei Huang, Yingying Cao, Jiarui Li, Yuanhua Liu, Wu Zhong, Xuan Li, Chen Chen and Pei Hao (Paper ID 67)

11:20 AM Phased secondary small interfering RNAs in Panax notoginseng; Kun Chen, Li Liu, Xiaotuo Zhang, Yuanyuan Yuan, Shuchao Ren, Junqiang Guo, Qingyi Wang, Peiran Liao, Shipeng Li, Xiuming Cui, Yong-Fang Li and Yun Zheng (Paper ID 61)

11:40 AM A comprehensive study on cellular RNA editing activity in response to infections with different subtypes of influenza A viruses; Yingying Cao, Ruiyuan Cao, Yaowei Huang, Hongxia Zhou, Yuanhua Liu, Xuan Li, Wu Zhong and Pei Hao (Paper ID 81)

12:00 PM R3D-BLAST2: an improved search tool for similar RNA 3D substructures; Ching-Yu Yen, Jian-Cheng Lin, Kun-Tze Chen and Chin Lung Lu (Paper ID 64)

Parallel session 3.3: Bioimaging and Classification Chair: Liang Zhao


11:00 AM An improved discriminative filter bank selection approach for motor imagery EEG signal classification using mutual information; Shiu Kumar, Alok Sharma and Tatsuhiko Tsunoda (Paper ID 5)


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11:20 AM Constraint-based Perturbation Analysis with Cluster Newton Method : A Case Study of Personalized Parameter Estimations with Irinotecan Whole-Body Physiologically Based Pharmacokinetic Model; Shun Asami, Daisuke Kiga and Akihiko Konagaya (Paper ID 24)

11:40 AM Automatic plankton image classification combining multiple view features via multiple kernel learning; Haiyong Zheng, Ruchen Wang, Zhibin Yu, Nan Wang, Zhaorui Gu and Bing Zheng (Paper ID 35)

12:00 PM Automated classification and characterization of the mitotic spindle following knockdown of a mitosis-related protein; Matloob Khushi, Imraan Dean, Erdahl Teber, Megan Chircop, Jonathan Arthur and Neftali Flores-Rodriguez (Paper ID 37)


1:30 PM – 3:10 PM

Keynote Speeches (Session Chair: Christian Schönbach) Building CII, Level 2 Conference Hall Venue

1:30 PM Keynote Speech Bioinformatics in the prevention and control of infectious diseases Yuelong Shu, Sun Yat-Sen University, China

2:20 PM Keynote Speech Networks based approaches in epigenomics, evolution and biomedicine

Alfonso Valencia, Barcelona Supercomputing Center, Spain


3:35 PM – 4:50 PM

Panel: Big Data Driven Bioinformatics and Precision Medicine: Status and Future Panellists: Tatsuya Akutsu, Saman Halgamuge, Paul Horton, Shoba Ranganathan, Christian Schönbach, Yuelong Shu, Alfonso Valencia, Xiujie Wang Hospital’s compass and perspective (Liang Zhao) Session Chairs: Lan Ma and Jinyan Li Building CII, Level 2 Conference Hall

Venue

4:50 PM – 5:30 PM


Parallel session 4.1: Integrative bioinformatics Chair: Shandar Ahmad


4:50 PM Construction of Pará rubber tree genome and multi-transcriptome database accelerates rubber researches; Yuko Makita, Mika Kawashima, Nyok Sean Lau, Minami Matsui and Ahmad Sofiman Othman (Paper ID 52)

5:10 PM Identification of natural antimicrobial peptides from bacteria through metagenomic and metatranscriptomic analysis of high-throughput transcriptome data of Taiwanese oolong teas; Kai-Yao Huang, Tzu-Hao Chang, Jhih-Hua Jhong, Yu-Hsiang Chi, Wen-Chi Li, Chien-Lung Chan, K. Robert Lai and Tzong-Yi Lee (Paper ID 79)

Parallel session 4.2: Proteome informatics Chair: Pei Hao


4:50 PM Exploration of charged states of balanol analogues acting as ATP mimics in kinases; Ari Hardianto, Muhammad Yusuf, Fei Liu and Shoba Ranganathan (Paper ID 54)


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5:10 PM A sparse autoencoder-based deep neural network for protein solvent accessibility and contact number prediction; Lei Deng, Chao Fan and Zhiwen Zeng (Paper ID 103)

Parallel session 4.3: Clustering algorithms Chair: Min Li


4:50 PM Divisive Hierarchical Maximum Likelihood Clustering; Alok Sharma, Yosvany Lopez and Tatsuhiko Tsunoda (Paper ID 30)

5:10 PM Investigation on changes of modularity and robustness by edge-removal mutations in signaling networks; Truong Cong Doan and Yung-Keun Kwon (Paper ID 90)

5:50 PM Shuttle Bus to Kylin Villa for conference banquet

6:30 PM Conference banquet at Kylin Villa, hosted by Professor Guangzhi Xia, Associate Dean of GSST.

8:30 PM Day 2 program close

Day 3 Full Program (Friday, 22 Sept. 2017)

9:00 AM – 10:40 AM


Parallel session 5.1: Structural bioinformatics Chair: Paul Horton


9:00 AM Mapping T-cell epitopes in the ebolavirus proteome; Wan Ching Lim and Asif M. Khan (Paper ID 65)

9:20 AM Search for overlapping subgraphs to detect multiple epitopes from an antigen; Shaogui Wu, Jin Xie, Jiawen Jiang, Wencui Li, Fei Luo and Liang Zhao (Paper ID 107)

9:40 AM MPTM: A TOOL FOR MINING PROTEIN POST-TRANSLATIONAL MODIFICATIONS FROM LITERATURE; Dongdong Sun, Minghui Wang and Ao Li (Paper ID 6)

10:00 AM Differential responses of innate immunity triggered by different subtypes of influenza A viruses in human and avian hosts; Yingying Cao, Yaowei Huang, Ke Xu, Yuanhua Liu, Ye Xu, Pei Hao, Wu Zhong and Xuan Li (Paper ID 119)

10:20 AM MDD-Carb: a combinatorial model for the identification of protein carbonylation sites with substrate motifs; Hui-Ju Kao, Shun-Long Weng, Kai-Yao Huang, Fergie Joanda Kaunang, Justin Bo-Kai Hsu, Chien-Hsun Huang and Tzong Yi Lee (Paper ID 125)

Parallel session 5.2: NGS informatics Chair: Tao Zeng


9:00 AM GTZ: a fast compression and cloud transmission tool optimized for FASTQ files; Yuting Xing, Gen Li, Zhenguo Wang, Bolun Feng, Zhuo Song and Chengkun Wu (Paper ID 88)

9:20 AM CoMet: A workflow using contig coverage and composition for binning a metagenomic sample with high precision; Damayanthi Herath, Sen-Lin Tang, Kshitij Tandon, David Ackland and Saman Halgamuge (Paper ID 112)

9:40 AM Bi-level error correction for PacBio long reads; Yuansheng Liu, Chaowang Lan, Michael Blumenstein and Jinyan Li (Paper ID 51)


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10:00 AM GapReduce: a gap filling algorithm based on partitioned read sets; Junwei Luo, Jianxin Wang, Juan Shang, Huimin Luo, Min Li, Fangxiang Wu and Yi Pan (Paper ID 101)

10:20 AM N.A.

Parallel session 5.3: Ontology, text mining Chair: Bing Wang


9:00 AM InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk; Liang Cheng, Yue Jiang, Hong Ju, Jie Sun, Meng Zhou, Yang Hu and Jiajie Peng (Paper ID 8)

9:20 AM Ontology-based systematic representation and analysis of traditional Chinese drugs against rheumatism; Qingping Liu, Jiahao Wang, Yan Zhu and Yongqun He (Paper ID 98)

9:40 AM Identifying term relations cross different gene ontology categories; Jiajie Peng, Honggang Wang, Junya Lu, Weiwei Hui, Yadong Wang and Xuequn Shang (Paper ID 130)

10:00 AM 2D-EM Clustering Approach for High-Dimensional Data; Alok Sharma, Piotr J. Kamola and Tatsuhiko Tsunoda (Paper ID 139)

10:20 AM Detection and Recognition for Life State of Cell Cancer Using Two-Stage Cascade CNNs; Haigen Hu, Qiu Guan, Shengyong Chen, Zhiwei Ji and Yao Lin (Paper ID 84)


11:10 AM – 12:30 AM


Parallel session 6.1: Systems biology Chair: Chengkun Wu


11:10 AM Characteristics of functional enrichment and gene expression level of human putative transcriptional target genes; Naoki Osato (Paper ID 110)

11:30 AM Novel human microbe-disease association prediction using network consistency projection; Zhi-Chao Jiang and De-Shuang Huang (Paper ID 114)

11:50 AM The node-weighted Steiner tree approach to identify elements of cancer-related signaling pathways; Yahui Sun, Chenkai Ma and Saman Halgamuge (Paper ID 116)

12:10 PM Integrating transcriptional activity in genome-scale models of metabolism; Daniel Trejo Banos, Mohamed Elati and Pauline Trébulle (Paper ID 48)

Parallel session 6.2: Integrative bioinformatics Chair: Tatsuya Akutsu


11:10 AM A Polynomial Based Model for Cell Fate Prediction in Human Diseases; Lichun Ma and Jie Zheng (Paper ID 75)

11:30 AM Utilizing Random Forest QSAR models with optimized parameters for target identification and its application to target-fishing server; Kyoungyeul Lee, Minho Lee and Dongsup Kim (Paper ID 111)

11:50 AM Discovery of cell-type specific DNA motif grammar in cis-regulatory elements using Random Forest; Xin Wang, Peijie Lin and Joshua Ho (Paper ID 123)


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12:10 PM CNN-BLPred: A Convolutional Neural Network based predictor for β-Lactamases (BL) and their classes; Clarence White, Hamid Ismail, Hiroto Saigo and Dukka Kc (Paper ID 132)

Parallel session 6.3: Bio-discovery Chair: Jinyan Li


11:10 AM Bone Marrow Cavity Segmentation using Graph-cuts with Wavelet-Based Texture Feature; Hironori Shigeta, Tomohiro Mashita, Junichi Kikuta, Shigeto Seno, Haruo Takemura, Masaru Ishii and Hideo Matsuda (Paper ID 105)

11:30 AM Comparison of different approaches for identifying subnetworks in metabolic networks; Abolfazl Rezvan and Changiz Eslahchi (Paper ID 129)

11:50 AM Automated Classification of Tropical Shrub Species: A Hybrid of Leaf Shape and Machine Learning Approach; Siow Wee Chang, Miraemiliana Murat, Arpah A., Hwa Jen Yap and Kien Thai Yong (Paper ID 93)

12:10 PM Analysis of Viral Diversity for Vaccine Target Discovery; Asif M. Khan, Yongli Hu, Olivo Miotto, Natascha M. Thevasagayam, Rashmi Sukumaran, Hadia Syahirah Abd Raman, Vladimir Brusic, Tin Wee Tan and J. Thomas August (Paper ID 66)


1:40 PM – 2:00 PM

Awards, InCoB 2018 presentation and Closing remarks (Conference co-chairs and APBioNet President)

Venue Building CII, Level 2 Conference Hall

2:00 PM Day 3 program close (Conference close, see you in InCoB 2018)


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Keynotes and Invited Talks: Abstracts and Biography

of Speakers

Limsoon Wong

School of Computing, National University of

Singapore

Keynote speech:

Advancing clinical proteomics via analysis based on

biological complexes

Biography: Wong Limsoon is Kwan-Im-Thong-Hood-Cho-Temple Chair Professor of

Computer Science at the National University of Singapore. He currently works mostly on

knowledge discovery technologies and their application to biomedicine. He is a Fellow of the

ACM, inducted for his contributions to database theory and computational biology. His other

awards include the 2003 FEER Asian Innovation Gold Award for his work on treatment

optimization of childhood leukemias, and the ICDT 2014 Test of Time Award for his work

on naturally embedded query languages.

Advancing clinical proteomics via analysis based on biological complexes

Abstract: Mass spectrometry (MS)-based proteomics is a widely used and powerful tool for

profiling systems-wide protein expression changes. It can be applied for various purposes, e.g.

biomarker discovery in diseases and study of drug responses. Nonetheless, MS-based

proteomics tend to have consistency issues (poor reproducibility and inter-sample agreement)

and coverage issues (inability to detect the entire proteome) that need to be urgently

addressed. This talk discusses how these issues can be addressed by proteomic profile

analysis techniques that use biological networks (especially protein complexes) as the

biological context. In particular, several techniques that we have been developing for

complex-based analysis of proteomics profile are described. These techniques are useful in

identifying proteomics-profile analysis results that are more consistent, more reproducible,

more robust in the presence of batch effects, and more biologically coherent, and these

techniques allow expansion of the detected proteome to uncover and/or discover novel

proteins. Incidentally, I think this work beautifully demonstrates the triumph of logic and

computational thinking over noise.


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Yong Hou

BGI-research, BGI-Shenzhen, China

Invited talk:

Single cell sequencing and its application

in cancer research

Biography: Dr. Yong Hou was trained as PhD in bioinformatics in Copenhagen University,

and now works as Research Scientist and Associate Director of BGI-Research. He has strong

background of next generation sequencing data analysis and interpretation, especially on

single cell analysis and cancer research. Published more than 30 peer reviewed scientific

papers on journals including Cell, Nature Biotechnology, Nature Communications and listed

as the co-inventor of more than 30 of patents in related area. He has granted more than 12

million RMB from national or local funding agencies to investigate the clinical application of

next generation sequencing on cancer diagnosis. He is invited as guest editor for Journal of

Clinical and Translational Medicine on Clinical Bioinformatics Session, and reviewer of

BMC Bioinformatics, Oncotarget and Cell Biology and Toxicology. Now he is focusing on

the translational research of applying next generation sequencing and single cell analysis to

cancer precision medicine.

Single cell sequencing and its application in cancer research

Abstract: Single cell sequencing emerges as the Method of Year 2012 and one of technology

changing the trajectory for cancer on the recent published New England Journal of Medicine.

From 2010, we seek to answer why sequencing single cell is important. We and others

demonstrated the cell-cell genetic variation using single cell sequencing on a variety of

cancers, gamete cells, neurons et al. Using single cell sequencing, we also observed

individual cells within the same population may differ dramatically, and these differences can

have important consequences for the cancer precision diagnosis We found single cell

sequencing could systematically describe the given “state” of a cancer cell, define cancer-

normal cell-to-cell variation, measure the impact of environmental perturbations, and help

understand cellular responses in the larger context of cancer tissues. However, in the future,

better WGA methods and lower cost single cell sequencing pipeline could facilitate the

clinical usage of single cell sequencing towards cancer precision diagnosis.


16 | P a g e

Saman Halgamuge

Research School of Engineering, The

Australian National University, Australia

Keynote speech:

Drugs and the Brain: What can Analytics

reveal in the Age of Data Engineering and

Deep Learning?

Biography: Saman Halgamuge, Fellow of the IEEE, is a Professor and the Director/Head of

Research School of Engineering, The Australian National University. He previously held

appointments as Professor and Associate Dean International at the University of Melbourne.

He graduated with Dipl.-Ing and PhD degrees in Data Engineering (“Datentechnik”) from

Technical University of Darmstadt, Germany and B.Sc. Engineering from University of

Moratuwa, Sri Lanka. He is an Associate Editor of BMC Bioinformatics, IEEE Transactions

on Circuits and Systems II and Applied Mathematics (Hindawi). His research that lead to 25o

publications has been funded over the last 20 years by Australian Research Council (16

grants), National Health and Medical Research Council (2 grants), industry and other external

organisations (13 grants or contracts) and funding to support stipends for 45 PhD students.

His research record is in Data engineering, which includes Data Analytics and Optimization

focusing on applications in Mechatronics, Energy, Biology and Medicine. He is a member of

the Australian Research Council College of Experts panel for Engineering, Information and

Computing Sciences. His publication profile is at Google Scholar.

Drugs and the Brain: What can Analytics reveal in the Age of Data Engineering and

Deep Learning?

Abstract: The concept of Data Engineering or “Datentechnique” has been a popular specialisation

of Electrical Engineering in Germany for several decades. It covers broadly algorithms, computing,

electronic hardware, AI, Control, and Networking etc. In today’s context, Data Engineering can be

considered as the integration of multiple types of sensing, networked control, AI, data analytics and

electronic hardware. Deep Learning (DL), in particular the Unsupervised DL has been useful in

applications of Bioinformatics in particular in Metagenomics but also increasingly in other areas of

knowledge discovery [1,2,3]. The inadequately studied direct interaction between drugs and the brain

and also the computational work on drug repositioning are such applications. This lack of knowledge

left room for some patients to experiment on their own in some cases with dangerous substances as

well as with cocktails of existing drugs, plant extracts etc. Several projects in speaker’s research group

located in Australian National University and University of Melbourne focus on drug usage and the

impact on the brain. Repositioning of existing drugs as appropriate medication for previously not

associated medical conditions help reduce the time, costs and risks of drug development.

Identification of drug groups either as clusters or subnetworks has already been used to simplify the

visualization and interpretation of data for the purpose of drug repositioning. In the first part of the

presentation a new Physarum-inspired Prize-Collecting Steiner Tree algorithm is used to solve this

problem on Drug Similarity Networks (DSN) that are generated using the chemical, therapeutic,

http://scholar.google.com.au/citations?sortby=pubdate&hl=en&user=9cafqywAAAAJ&view_op=list_works


17 | P a g e

protein, and phenotype features of drugs [4]. In the second part, characterisation of drugs using Multi-

Electrode Arrays (MEA) is discussed. MEA is an extracellular recording technology that enables the

analysis of networks of neurons in vitro by producing “big data”. Neurons in culture exhibit a range of

behavioural dynamics, which can be measured in terms of individual action potentials, network-wide

synchronized firing and a host of other features that characterize network activity [5-6]. MEA data

analysis is used to differentiate between two types of antiepileptic drugs with different mechanisms of

action. It initially extracts features that characterise different aspects of neuronal activity that can be

used to characterise network states. This utilises existing feature extraction methods as well as novel

methods that are adaptive to activity patterns in unperturbed and perturbed network states. These

features are then used to build network signatures that allow novel compounds to be compared with

compounds with known mechanisms of action. This research demonstrates that MEA-based

workflows can assist in rapid and efficient screening of pharmacological compounds, making them a

useful addition to drug development pipelines. In the third part, developing new methods for

modelling neurons to help identifying disease mechanisms leading to drug discovery is discussed [7].

The development of a “cell-computer hybrid system” to enable real-time modelling of neural

conductance models is an on-going project. This real-time system enables accurate models to be built

on as little as 1 second of recording data. The project conducted by PhD student Yadeesha and co-

supervised by Prof Steve Petrou and his colleagues in the Florey Institute of Neuroscience and Mental

Health incorporates the dynamic clamp; an electrophysiological method that enables “wetware in the

loop” analysis for real-time interaction of our biological system with an in silico computer model.

Acknowledgement: Prof Karin Verspoor of University of Melbourne and Prof Steve Petrou of

Howard Florey Institute, former PhD students Isaam Saeed, Duleepa Jayasundara, Jayantha

Siriwardena and current PhD students Yadeesha Deerasooriya, Dulini Mendis, Nusrath Hameed and

Yahui Sun. Australian Research Council grants DP150103512 and LP140100670 partially supported

this research.

The following research papers cover the content of the presentation:

[1] D Jayasundara, I Saeed, S Maheswararajah, BC Chang, SL Tang and S. K. Halgamuge, “ViQuaS: an improved reconstruction pipeline for viral

quasispecies spectra generated by next-generation sequencing”, Bioinformatics 31 (6), 886-896, 2014.

[2] I Saeed, SL Tang, SK Halgamuge, “Unsupervised discovery of microbial population structure within metagenomes using nucleotide base composition”,

Nucleic acids research 40 (5), e34, 2011.

[3] PN Hameed, K Verspoor, S Kusljic, S Halgamuge, “Positive-Unlabeled Learning for inferring drug interactions based on heterogeneous attributes” BMC

bioinformatics 18 (1), 2017

[4] Y. Sun, N. Hameed, K. Verspoor and S. K. Halgamuge, “A Physarum-inspired Prize-Collecting Steiner Tree approach to identify subnetworks for drug

repositioning”, BMC Systems Biology, 10 (5), 128, 2016.

[5] G. D. C. Mendis, E. Morrisroe, S. Petrou, S.K. Halgamuge, “Use of adaptive network burst detection methods for multielectrode array data and the

generation of artificial spike patterns for method evaluation", Journal of Neural Engineering, 2016, 13(2):026009

[6] G. D. C. Mendis, E. Morrisroe, C. A. Reid, S. K. Halgamuge and S. Petrou, "Use of local field potentials of dissociated cultures grown on multi-electrode

arrays for pharmacological assays," 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Orlando,

FL, 2016, pp. 952-956.

[7] Y. Deerasooriya, G. Berecki, S. Halgamuge and S. Petrou, “Real Cell-Computer Hybrid System”,

http://www.cfne.unimelb.edu.au/news/real-cell/, Centre for Neural Engineering, University of Melbourne, 2017

http://www.cfne.unimelb.edu.au/news/real-cell/


18 | P a g e

Jianzhu Chen

Koch Institute for Integrative Cancer

Research, Massachusetts Institute of

Technology, USA

Keynote speech:

Application of Informatics in

Immunological Research

Biography: Jianzhu Chen is Professor of Biology at Koch Institute for Integrative Cancer

Research and Department of Biology at Massachusetts Institute of Technology (MIT). He is

also the lead Principle Investigator of the Infectious Disease Interdisciplinary Research

Group of Singapore-MIT Alliance for Research and Technology (SMART). Dr. Chen’s

research seeks fundamental understanding of the immune system as well as its application in

disease intervention. Recently, his research activity has focused on developing humanized

mouse technology for modeling human diseases with autologous immune system and

therapeutic development. Dr. Chen received a B.S. degree from Wuhan University in China

and a Ph.D. degree from Stanford University. He was a postdoctoral fellow and then an

instructor at Harvard Medical School before he joined the faculty in the Department of

Biology at MIT.

Application of Informatics in Immunological Research

Abstract: The availability of large amount of data in genomic, transcriptional, structural,

pathway and network analyses have fundamentally changed how biomedical research is

conducted. Informatics analysis has become an integral part of any biological research project

by not only supporting analysis of large data set but also providing initial analysis of

publically available data to generate hypothesis to be tested. In our study of transcriptional

control of memory T cell development and maintenance, we first mined public data base of

transcriptional profiles of naïve, effector and memory CD8 T cells. This analysis resulted in

identification of transcription factors known to be involved in memory CD8 T cell

development as well as new transcription factors whose role in memory T cell development is

not known. We then tested the role of some transcription factors in memory T cell

development in cell culture and in mouse models and obtained direct experimental support

for these transcription factors in memory CD8 T cell development. Increasingly, biological

data set is integrated with chemical data set in study of metabolism, physiology, and drug

development. In this context, we have screened human macrophage responses to FDA-

approved drugs, bioactive compounds and natural compounds (over 4,000). We identified

around 300 compounds that can either polarize human macrophages to inflammatory (M1) or

anti-inflammatory (M2) state. Again, informatics analysis helps to sort through the large data

set. However, how to rationally narrow down 300 compounds to a dozen or so compounds

that can be tested experimentally remains a challenge. Similarly, how to rationally identify

specific compound that might be used for treating specific disease also requires more

sophisticated informatics approaches.


19 | P a g e

Xiujie Wang

Institute of Genetics and Developmental

Biology, Chinese Academy of Sciences,

China

Keynote speech:

Using Bioinformatics to Identify New

Regulatory Mechanisms

Biography: Professor Xiujie Wang received her Ph.D. degree in bioinformatics from The

Rockefeller University in 2004, and is currently the Director for Center of Molecular Systems

Biology, a Principal Investigator at the Institute of Genetics and Developmental Biology

(IGDB), Chinese Academy of Sciences. Since joining IGDB at the beginning of 2005, Dr.

Wang has been leading a research group working on bioinformatics and systems biology,

with an emphasis on non-coding RNA prediction and functional study as well as

transcriptomic data analysis. They have identified miRNA-24 as a key regulator for heart

failure, discovered a cluster of stem cell pluripotency related miRNAs, and revealed the new

roles of miRNAs in regulating the formation of RNA m6A modification. Dr. Wang’s group

has published over 80 research papers on journals including Cell Stem Cell, Genes &

Development, PNAS, Circulation Research, Genome Biology, Nucleic Acids Research, etc,

and developed a few bioinformatics software, including GOEAST, psRobot, ISRNA. Dr.

Wang received NSFC Outstanding Young Scientist Award and DuPont Young Scientist

Award in 2007, was elected to the Ten Thousand Talent Leading Scientist Program, and

jointly won China National Natural Science Award (Second Class) in 2014 and 2016,

respectively.

Using Bioinformatics to Identify New Regulatory Mechanisms

Abstract: Increasing amount of large-scale biological data had been produced in recent years

with the broad application of high-throughput sequencing technologies. In combination with

bioinformatic analysis and experimental validation, we have identified a cluster of miRNAs

whose expression abundance is positively correlated with the pluripotency level of ESCs, and

confirmed that one of the functions of these miRNAs is to target the key component of the

PRC2 complex therefore to regulate H3K27me3 modification. We also identified a long non-

coding RNA which functions as a ceRNA to compete for miRNAs targeting a key

pluripotency factor, Nanog. We have proven that ESC-specific transcription factors are

capable to produce ESC-specific transcripts with alternative transcription start sites from

ubiquitously expressed genes, thus confer ubiquitously expressed genes novel functions to

involve in the maintenance of ESC pluripotency. In addition, we identified that the m6A

modification on mRNAs is regulated by miRNAs via a sequence pairing mechanism, which

revealed a new role for miRNAs in regulating mRNA epigenetic modifications.


20 | P a g e

Xinghua (Mindy) Shi

Department of Bioinformatics and Genomics,

University of North Carolina at Charlotte, USA

Invited talk:

An Integrative Approach Toward Predictive

Modelling for Big Data Genomics

Biography: Xinghua (Mindy) Shi is an assistant professor in the Department of

Bioinformatics and Genomics, College of Computing and Informatics, University of North

Carolina at Charlotte. Before joining UNC Charlotte, she was a postdoctoral research fellow

at Brigham and Women’s Hospital and Harvard Medical School, an NIH T32 medical

genetics training fellow at Harvard Medical School, a visiting research fellow in the Medical

and Population Genetics program at Broad Institute, and an associate in the Quantitative

Genetics Program at Harvard School of Public Health. She has received her Ph.D. and M.S.

degrees in Computer Science from the University of Chicago, and M.Eng and B. Eng degrees

in Computer Science from Beijing Institute of Technology, China. Her research interest is in

bioinformatics and computational systems biology. Particularly, she works on the design and

development of tools and algorithms to solve large-scale computational problems in biology

and biomedical research. She is currently focused on integrating genetic and epigenetic

datasets to study how genetic architecture affects biological processes and complex

phenotypes at the systems level. She is also interested in genetic privacy, complex network

analysis, and big data analytics in biomedical research. Her work is supported by multiple

agencies and foundations including Wells Fargo Foundation Fund, NSF, NIH, and DARPA.

An Integrative Approach Toward Predictive Modelling for Big Data Genomics

Abstract: The biological data deluge thanks to recent advances in biotechnology, has

fundamentally transformed life sciences and biomedical research into a data science frontier.

We witness a genomic era of data acquisition on a broader scale, with finer accuracy, higher

dimensionality, and higher throughput than ever. The unprecedented accumulation of

genomic data presents a unique challenging opportunity to dive deep into understanding the

complex interplay of (epi-)genetics with phenotypic variation. To fully exploit big genomic

data and enable translation of genomic analytics to clinical practice, we have developed a

suite of machine learning methods to investigate these complex relationships toward

predictive modeling in genomics. In this talk, I will first review the current status of

cataloging human genetic variation and assessing their functional impact in the 1000

Genomes Project. Next, I will present our recent work of integrating genomics and

interactome for quantitative trait locus network analysis, and constructing predictive models

based on a deep learning framework. Finally, I will summarize the talk and point to future

research directions in genetic privacy, and infrastructure support that transforms beyond

current high performance computing for big data genomics.


21 | P a g e

Yuelong Shu

School of Public Health (Shenzhen), Sun

Yat-sen University, WHO Collaborating

Center for Reference and Research on

Influenza, China

Keynote speech:

Bioinformatics in the prevention and

control of infectious diseases

Biography: Dr. Shu obtained his PhD degree in 1998 at the Institute of Virology, Chinese

Academy of Preventive Medicine. He got post-doctoral training at the Mount Sinai Medical

School (1998–1999), and University of California, Los Angeles (1999–2002). He is currently

the Dean of Public Health School (Shenzhen), Sun Yat-Sen University. He served as the

director of WHO Collaborating Center for Reference and Research on Influenza (2010-2017),

the director of Chinese National Influenza Centre (CNIC, 2004-2017), the deputy director of

National Institute for Viral Disease Control and Prevention of China CDC (2008-2017). Dr.

Shu played a leadership to establish the national influenza surveillance network in China

including 408 influenza laboratories and 554 influenza sentinel hospitals, which has played

important roles influenza vaccine composition recommendation and pandemic preparedness

and response. He has been committed to the research mainly on molecular evolution, the

mechanisms of interspecies transmission, infectivity, and pathogenicity of influenza viruses,

and the new detection techniques development and vaccine and antiviral drug related research.

In 2013, he firstly discovered a novel H7N9 avian influenza virus caused severe human

infection in China. He leads the studies on the biological features of the H7N9 avian

influenza virus; the findings provided scientific insights for the infectivity, transmissibility

and pathogenesis of the novel H7N9 virus. He successfully developed diagnosis kits for

H7N9 and pandemic H1N1 viruses to improve the clinical treatment. He also firstly identified

the avian influenza H10N8 and H5N6 viruses caused human infection. He made great

contributions to the prevention and control of H5N1 and pandemic H1N1 2009 in China.

Dr.Shu has lead more than 20 scientific projects supported by China central government

agencies, National Institutes of Health (NIH) and Centers for Disease Control and Prevention

(CDC), USA, et al. He is also the Distinguished Young Scholar funded by National Natural

Science Foundation of China. He has published more than 100 peer-reviewed scientific

journal papers including in Science, Nature, NEJM, Lancet et al. Dr. Shu was the winner for

National Science and Technology progress award and the China Youth Science and

technology prize; He was selected as the National Science and Technology Innovation Leader

in 2012 and nominated as the Science and Technology Innovator in 2014.

Bioinformatics in the prevention and control of infectious diseases

Abstract: Continually outbreaks caused by Influenza, ZIKA, Ebola and MERS et al suggest

that although huge progresses have been made in prevention and control of emerging


22 | P a g e

infectious diseases, they remain the threats for the global public health and still cause large

morbidity and mortality to humans. How to effectively control and prevent the infectious

diseases is still the globe priority of public heatlh. With the advent and rapid development of

DNA sequencing technology, sequencing-based methods have been extensively used in

surveillance of infectious diseases, during which process the “big data” for infectious

diseases, including but not limited to genomic, virological, epidemiological and

environmental data were accumulated rapidly. Based on such big data, numerous

bioinformatics methods have been developed and demonstrated to be helpful in rapid

identification, tracing, prediction and early warnings of emerging infectious diseases. Here,

we described our efforts in the prevention and control of influenza viruses by combining

computational methods and big data for influenza viruses, which were derived from the

world’s largest influenza surveillance network in China. Firstly, by integrating genomic,

virological and epidemiological data, for the first time we isolated and identified a novel

reassortant avian-origin influenza A (H7N9) virus which caused the outbreaks in China in the

spring of 2013. Further, through an in-depth evolutionary analysis of whole-genome

sequence data of H7N9 and H9N2 viruses, we identified the pathways for the generation of

diverse H7N9 genotypes in China. Similar method was also successfully used to identify the

origin of Zika virus outbreak in Brazil in 2006. Secondly, we had developed a novel method

named co-occurrence network model to capture the coevolution of viral genome, and present

each genome as s network. The co-occurrence network could help to build the good

association between viral genotype and pheonytpe. Characteristics derived from viral co-

occurrence network were successfully used to predict the antigenic variation of influenza

viruses, and to access the severity of Ebola viruses. Thirdly, we had also developed a

computational method, named PREDAC, for predicting antigenic clusters (i.e., a group of

viruses with similar antigenicity) based on the hemaggulutinin protein sequence of influenza

viruses, which allowed us to systematically model the antigenic evolution of influenza

viruses, including human influenza H3N2, H1N1 and highly pathogenic avian influenza

H5N1 viruses. Moreover, we demonstrated that coupling PREDAC and large-scale

sequencing of human influenza H3N2 viruses could significantly improve vaccine strain

recommendation for China. In summary, in the big data era, bioinformatics methods will

make a great contribution for prevention and control of infectious diseases.


23 | P a g e

Alfonso Valencia

Life Sciences Department, Barcelona

Supercomputing Centre (BSC), Spain

Keynote speech:

Networks based approaches in

epigenomics, evolution and biomedicine

Biography: Professor Alfonso Valencia has been recently appointed at the Barcelona

Supercomputing Center - Centro Nacional de Supercomputación (BSC-CNS) as Director of

the Life Sciences Department, with the support of the ICREA program. He is also the

Director of the National Institute of Bioinformatics (Salud Carlos III Institute platform (INB-

ISCII) and node of ELIXIR the European Infrastructure of Bioinformatics), Founder and

President of the International Society for Computational Biology and Co-Executive Director

of the main journal in the field (Bioinformatics of Oxford University Press). Alfonso

Valencia's research is centred in the area of Bioinformatics and Computational Biology. The

computational methods for the genome analysis are particularly application to Precision

Medicine. He has also worked in the development of computational methods for the

prediction of protein structures and functions, the analysis biological networks and for

modelling of molecular systems. These methods are based in the development of open and

collaborative structures and are immersed in large international collaborative projects.

Networks based approaches in epigenomics, evolution and biomedicine

Abstract: In the first study, we processed heterogeneous ChIP‐Seq information to build a

comprehensive genome co‐localization network of Chromatin Related Proteins (CRPs),

histone marks and DNA modifications in mouse embryonic stems cells. In this network, co‐

localization preferences can be translated into specific of “mESC Chromatin States”, such as

active regions or enhancers. The study of the properties of the “co‐localization” network

points to the 5hmC DNA modifications, as the key component in the organization of the

mouseESC network. In a second network based study, the importance of 5hmC, as organizer

of the epigenetic network, is reinforced by the evolutionary analysis of the protein

components of the network. There, 5hmC acts as a mediator in the co‐evolution of the CRPs

protein components of the mESC network. The third network‐based approach explores the

functional significance of the mESC Epigenetic Properties and Chromatin States, by

analysing them in the context of the structure of the chromatin in the cell nucleus. The results

revealed interesting properties of the organization of the mESC epigenetic control system, in

line with the emerging models of gene expression control and chromatin organization, and

again support the role of 5hmC as a factor present in a significant number of interactions

related with active transcription in mouse embryonic stems cells. One additional network


24 | P a g e

approach shows how the same network properties can help to understand the complex

relations between expression patterns related with human diseases.

Epigenomic Co‐localization and Co‐evolution Reveal a Key Role for 5hmC as a

Communication Hub in the Chromatin Network of ESCs. Perner et al., (2016) Cell

Rep. http://www.cell.com/cell‐reports/pdf/S2211‐ 247(16)00028‐0.pdf

Integrating epigenomic data and 3D genomic structure with a new measure of

chromatin assortativity. Pancaldi et al., (2016) Genome Biol.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4939006/

A molecular hypothesis to explain direct and inverse co‐morbidities between

Alzheimer's Disease, Glioblastoma and Lung cancer. Sanchez‐Valle et al., (2017)

Scientific Reports https://www.nature.com/articles/s41598‐017 04400‐6.

Parts of this work were developed in collaboration with: Vingron's (MPIMG, Berlin),

Fraser’s (Babraham Institute), and Baudot’s labs (CNRS, Marseille).

http://www.cell.com/cell--‐reports/pdf/S2211--‐

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4939006/

https://www.nature.com/articles/s41598--‐017--


25 | P a g e

List of Best Paper Awards from BMC Track

Haiyong Zheng, Ruchen Wang, Zhibin Yu, Nan

Wang, Zhaorui Gu and Bing Zheng. Automatic

plankton image classification combining multiple

view features via multiple kernel learning

BMC Bioinformatics

Supplement

Gold

Ari Hardianto, Muhammad Yusuf, Fei Liu and Shoba

Ranganathan. Exploration of charge states of balanol

analogues acting as ATP mimics in kinases

BMC Bioinformatics

Supplement

Gold

Ching-Yu Yen, Jian-Cheng Lin, Kun-Tze Chen and

Chin Lung Lu. R3D-BLAST2: an improved search

tool for similar RNA 3D substructures

BMC Bioinformatics

Supplement Gold

Jiajie Peng, Honggang Wang, Junya Lu, Weiwei Hui,

Yadong Wang and Xuequn Shang. Identifying term

relations cross different gene ontology categories

BMC Bioinformatics

Supplement

Silver

Jiaojiao Miao, Na Han, Yujun Qiang, Tingting Zhang,

Xiuwen Li and Wen Zhang. 16sPIP: A

Comprehensive Analysis Pipeline for Rapid Pathogen

Detection in Clinical Samples Based on 16S

Metagenomic Sequencing

BMC Bioinformatics

Supplement

Bronze

Nikhil Pathak, Mei-Ling Lai, Wen-Yu Chen, Betty-

Wu Hsieh, Guann-Yi Yu and Jinn-Moon Yang.

Pharmacophore anchor models of flaviviral NS3

proteases lead to drug repurposing for DENV

infection

BMC Bioinformatics

Supplement

Bronze

Kyoungyeul Lee, Minho Lee and Dongsup Kim.

Utilizing Random Forest QSAR models with

optimized parameters for target identification and its

application to target-fishing server

BMC Bioinformatics

Supplement

Bronze

Yahui Sun, Chenkai Ma and Saman Halgamuge. The

node-weighted Steiner tree approach to identify

elements of cancer-related signaling pathways

BMC Bioinformatics

Supplement

Bronze

Yu-Wei Wu. ezTree: an automated pipeline for

identifying marker genes and inferring phylogenetic

relationships for uncultivated prokaryotic draft

genomes

BMC Genomics Supplement

Gold

Wan Ching Lim and Asif M. Khan. Mapping T-cell

epitopes in the ebolavirus proteome BMC Genomics Supplement

Gold

https://easychair.org/conferences/review_for_paper.cgi?a=13533408;paper=3266531










https://easychair.org/conferences/review_for_paper.cgi?paper=3283702;a=13533408





















26 | P a g e

Yaowei Huang, Yingying Cao, Jiarui Li, Yuanhua

Liu, Wu Zhong, Xuan Li, Chen Chen and Pei Hao. A

survey on cellular RNA editing activity in response to

Candida albicans infections


Gold

Yingying Cao, Ruiyuan Cao, Yaowei Huang, Hongxia

Zhou, Yuanhua Liu, Xuan Li, Wu Zhong and Pei Hao.

A comprehensive study on cellular RNA editing

activity in response to infections with different

subtypes of influenza A viruses


Gold

Kun Chen, Li Liu, Xiaotuo Zhang, Yuanyuan Yuan,

Shuchao Ren, Junqiang Guo, Qingyi Wang, Peiran

Liao, Shipeng Li, Xiuming Cui, Yong-Fang Li and

Yun Zheng. Phased secondary small interfering RNAs

in Panax notoginseng


Silver

Guo Weifeng, Zhang Shaowu, Shi Qianqian, Zhang

Chengming, Zeng Tao and Chen Luonan. A novel

algorithm for finding optimal driver nodes to target

control complex networks and its applications for drug

targets identification


Bronze

Yuko Makita, Mika Kawashima, Nyok Sean Lau,

Minami Matsui and Ahmad Sofiman Othman.

Construction of Pará rubber tree genome and multi-

transcriptome database accelerates rubber researches


Bronze

Asif M. Khan, Yongli Hu, Olivo Miotto, Natascha M.

Thevasagayam, Rashmi Sukumaran, Hadia Syahirah

Abd Raman, Vladimir Brusic, Tin Wee Tan and J.

Thomas August. Analysis of Viral Diversity for

Vaccine Target Discovery

BMC Medical Genomics

Supplement

Gold

Y-H. Taguchi. Tensor decomposition-based

unsupervised feature extraction identifies candidate

genes that induce post-traumatic stress disorder-

mediated heart diseases


Supplement

Silver

Jonathan Dayton and Stephen Piccolo. Classifying

cancer genome aberrations by their mutually exclusive

effects on transcription


Supplement Bronze

Zhiwei Ji, Bing Wang, Ke Yan, Ligang Dong,

Guanmin Meng and Lei Shi. A linear programming

computational framework integrates phosphor-

proteomics and prior knowledge to predict drug

efficacy

BMC Systems Biology

Supplement

Gold

Lichun Ma and Jie Zheng. A Polynomial Based Model

for Cell Fate Prediction in Human Diseases

BMC Systems Biology

Supplement Gold












































27 | P a g e

Kai-Yao Huang, Tzu-Hao Chang, Jhih-Hua Jhong,

Yu-Hsiang Chi, Wen-Chi Li, Chien-Lung Chan, K.

Robert Lai and Tzong-Yi Lee. Identification of natural

antimicrobial peptides from bacteria through

metagenomic and metatranscriptomic analysis of

high-throughput transcriptome data of Taiwanese

oolong teas

BMC Systems Biology

Supplement

Gold

Ying Xu, Jiaogen Zhou, Shuigeng Zhou and Jihong

Guan. CPredictor3.0: Effectively detecting protein

complexes from PPI networks with expression data

and functional annotations

BMC Systems Biology

Supplement

Silver

Min-Gang Su, Julia Tzu-Ya Weng, Justin Bo-Kai

Hsu, Kai-Yao Huang, Yu-Hsiang Chi and Tzong Yi

Lee. Investigation and identification of functional

post-translational modification sites associated with

drug binding and protein-protein interactions

BMC Systems Biology

Supplement

Bronze

Daniel Trejo Banos, Mohamed Elati and Pauline

Trébulle. Integrating transcriptional activity in

genome-scale models of metabolism

BMC Systems Biology

Supplement Bronze

Huipeng Li, Lakshmi Venkatraman, Balakrishnan

Chakrapani Narmada, Jacob White, Hanry Yu and

Lisa Tucker-Kellogg. Computational analysis reveals

the coupling between bistability and the sign of a

feedback loop in a TGF-β1 activation model

BMC Systems Biology

Supplement

Bronze

Maulida Mazaya, Hung-Cuong Trinh and Yung-Keun

Kwon. Construction and analysis of gene-gene

dynamics influence networks based on a Boolean

model

BMC Systems Biology

Supplement

Bronze

Truong Cong Doan and Yung-Keun Kwon.

Investigation on changes of modularity and robustness

by edge-removal mutations in signaling networks

BMC Systems Biology

Supplement

Bronze

Qingping Liu, Jiahao Wang, Yan Zhu and Yongqun

He. Ontology-based systematic representation and

analysis of traditional Chinese drugs against

rheumatism

BMC Systems Biology

Supplement

Bronze

Hui-Ju Kao, Shun-Long Weng, Kai-Yao Huang,

Fergie Joanda Kaunang, Justin Bo-Kai Hsu, Chien-

Hsun Huang and Tzong Yi Lee. MDD-Carb: a

combinatorial model for the identification of protein

carbonylation sites with substrate motifs

BMC Systems Biology

Supplement

Bronze










































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List of Provisionally Accepted Posters

A Comparison Study for Supervised Machine Learning Models in Cancer Classification;

Huaming Chen, Hong Zhao, Lei Wang, Jiangning Song and Jun Shen (Paper ID 53)

High performance computing for accelerating a next-generation sequencing-based clinical

pathogen identification pipeline; Haoran Ma, Tin Wee Tan and Kenneth Hon Kim Ban (Paper

ID 62)

Rapid Cluster Analysis of Wound Microbiota; Timothy Chappell, Shlomo Geva, James M

Hogan, Flavia Huygens, Wayne Kelly and Dimitri Perrin (Paper ID 135)

A New Semantic Disease-Disease Similarity Based on the Environment Information and

Disease-related Genes; Fatemeh Abbasi and Changiz Eslahchi (Paper ID 141)

MOROKOSHI: Transcriptome database in Sorghum bicolor and its updates; Yuko Makita,

Mika Kawashima, Tomoko Kuriyama, Setsuko Shimada and Minami Matsui (Paper ID 142)

Prediction of GPCR-G Protein Coupling Specificity Based on Transmembrane Topologies;

Riku Ashida and Yasuhito Inoue (Paper ID 143)

Identification of deregulated transcription factors involved in subtypes of cancers; Magali

Champion, Julien Chiquet, Pierre Neuvial, Mohamed Elati and Etienne Birmele (Paper ID

151)

Transfer-of-training framework to find similarity and classify protein complexes; Shruti

Gupta, Manisha Kalsan, Dana Mary Varghese, Ajay Arya, Ajay Kumar Verma and Shandar

Ahmad (Paper ID 154)

Infectious Disease Modelling and Surveillance through Unstructured Twitter Data for

understanding location specific Toxicological Trends; Saurabh Sugha and Dr Shandar Ahmad

(Paper ID 155)

Sequence evolution of the methicillin resistant mecA gene; Ling Li Koh, Charisma Nair

Murali, Mohammad Asif Khan and Swee Hua Erin Lim (Paper ID 160)

BioCarian: An Engine for Searching Biological Databases; Nazar Zaki and Chandana

Tennakoon (Paper ID 161)

TimeXNet: Prediction and analysis of cellular response pathways; Phit Ling Tan, Ashwini

Patil and Kenta Nakai (Paper ID 163)


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Conference Committees

Conference Co-chairs

Jinyan Li, University of Technology Sydney, Australia

Lan Ma, Graduate School at Shenzhen, Tsinghua University, China

Program Committee Co-chairs

Christian Schönbach, Kumamoto University, Japan

Siu-Ming Yiu, University of Hong Kong, China

Tatsuya Akutsu, Kyoto University, Japan

Paul Horton, Artificial Intelligence Research Center, AIST, Japan

Local Organizing Co-chairs

Yujiu Yang and Yu Cen, Graduate School at Shenzhen, Tsinghua University, China

Publication Co-chairs

Christian Schönbach, Kumamoto University, Japan

Shoba Ranganathan, Macquarie University, Australia

Muhammad Farhan Sjaugi, Perdana University, Malaysia

Publicity Co-chairs

Paul Horton, Artificial Intelligence Research Center, AIST, Japan

Shaoliang Peng, College of Computer, National University of Defense Technology, China

Conference Honorary Chairs

Shoba Ranganathan, Macquarie University, Australia

Limsoon Wong, National University of Singapore, Singapore.

Program Committee Members:

Abdul Baten, Southern Cross University

Akihiko Konagaya, Tokyo Institute of Technology

Anton Kratz, RIKEN

Ashwini Patil, Institute of Medical Science, University of Tokyo

Asif M. Khan, National University of Singapore

Barbara Holland, University of Tasmania

Brian Chen, Lehigh University

Bing Wang, Anhui University of Technology

Catherine Abbott, Flinders University

Chee Keong Kwoh, NTU

Chia-Lang Hsu, Department of Life Science, National Taiwan University

Chih Lee, Illumina

Chinh Tran-To Su, Nanyang Technological University

Christian Schönbach, Kumamoto University

Chun-Hsi Huang, University of Connecticut


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Daisuke Kiga, Waseda University

Daniele Santoni, National Research Council of Italy

Dongqing Wei, Shanghai Jiaotong Univ.

Fang Hsu, Feng Chia University

Filippo Castiglione, National Research Council of Italy (CNR)

Francesco Pappalardo, University of Catania

Gajendra Raghava, IMTECH

Ge Gao, Peking University

Guang Hu, Soochow university

Guang Lan Zhang, Boston University

Haiquan Li, University of Arizona

Hampapathalu Nagarajaram, University of Hyderabad

Hideo Matsuda, Osaka University

Hiroshi Mamitsuka, Kyoto University / Aalto University

Hongbin Shen, Shanghai Jiaotong University

Igor Kurochkin, Sysmex Co.

Ikuo Uchiyama, National Institutes of Natural Sciences

Jessica Mar, University of Queensland

Jiajie Peng, Northwestern Polytechnical University

Jianqiang Sun, National institute of advanced industrial science and technology, Japan

Jie Li, harbin institute of technology

Jinyan Li, University of Technology Sydney

Jonathan Chan, King Mongkut's University of Technology Thonburi

Juanying Xie, Shaanxi Normal University

Ka-Lok Ng, Department of Biomedical Informatics, Asia University

Kenta Nakai, Intitute of Medical Science, University of Tokyo

Kevin Yip, The Chinese University of Hong Kong

Lamiae Azizi, The University of Sydney

Lenny Moise, University of Rhode Island

Liang Zhao, Taihe Hospital, Hubei University of Medicine

Limsoon Wong, National University of Singapore

Lin Liu, University of South Australia

Lin Gao, Xidian University

Mahmoud Elhefnawi, American University in Cairo

Martti Tammi, National University of Singapore

Masakazu Sekijima, Tokyo Institute of Technology

Masanori Arita, National Institute of Genetics

Matthew He, Nova Southeastern University

Mauno Vihinen, Lund University

Melissa Davis, Walter and Eliza Hall Institute of Medical Research

Michael Charleston, The University of Sydney

Michael Gromiha, IIT Madras

Michael A. Beer, Johns Hopkins University

Mikael Boden, The University of Queensland

Ming Chen, Zhejiang University

Ming-Jing Hwang, Institute of Biomedical Scienecs, Academia Sinica

Mohd Firdaus-Raih, Universiti Kebangsaan Malaysia


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Narayanaswamy Srinivasan, Indian Institute of Science

Nicola Armstrong, Murdoch University

Nikolai Petrovsky, Flinders Medical Centre

Osamu Maruyama, Kyushu University

Paolo Tieri, Consiglio Nazionale delle Ricerche

Paul Horton, AIST, Computational Biology Research Center

Paul Kennedy, University of Technology, Sydney

Peng Chen, Chinese Academy of Sciences

Peter Bond, A*STAR

Prashanti Manda, University of North Carolina

Qingyao Wu, South China University of Technology

Ran Su, School of Computer Software, Tianjin University

Ruiting Lan, University of New South Wales

Santo Motta, University of Catania

Shandar Ahmad, Jawaharlal Nehru University

Shanfeng Zhu, Fudan University

Shaoliang Peng, National University of Defense Technology

Shinichi Morishita, University of Tokyo

Shinji Kondo, NIG

Shoba Ranganathan, Macquarie University

Shuigeng Zhou, Fudan University

Sing-Hoi Sze, Texas A&M University

Siu Ming Yiu, The University of Hong Kong

Sorayya Malek, University of Malaya

Susumu Goto, Research Organization of Information and Systems

Tao Liu, Children's Cancer Institute Australia

Tao Zeng, Nanyang Technological University

Tatsuya Akutsu, Kyoto University

Tetsuo Shibuya, The University of Tokyo

Thomas Wong, The Australian National University

Thuc Duy Le, University of South Australia

Tsung Fei Khang, University of Malaya

Ueng-Cheng Yang, National Yang Ming University

Ulykbek Kairov, Center for Life Sciences, Nazarbayev University

Vladimir Bajic, King Abddulah University of Science and Technology (KAUST)

Vladimir Brusic, Nazarbayev University

Wai-Ki Ching, The University of Hong Kong

Wenlian Hsu, Academia Sinica

Wentian Li, Feinstein Institute for Medical Research

Wing-Kai Hon, Nation Tsing Hua University

Xiaoke Ma, Xidian University

Xiaoli Li, Institute for Infocomm Research

Xiaoming Sun, Harvard University

Xiaodong Liu, Anhui University of Technology

Xing-Ming Zhao, Tongji University

Y-H. Taguchi, Department of Physics. Chuo University

Yanni Sun, Michigan State University


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Yaoqi Zhou, Griffith University

Yasubumi Sakakibara, Keio University

Yee Hwa (Jean) Yang, University of Sydney

Yinglei Lai, George Washington University

Yingqiu Xie, Nazarbayev University

Yoichi Takenaka, Kansai University

Yongqun He, University of Michigan

Yufeng Wu, University of Connecticut

Yun Zheng, Fudan University

Zhenhua Li, National University of Singapore Hospital

Zhongming Zhao, University of Texas Health Science Center at Houston

Zuguo Yu, Xiangtan University


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Conference Venue

The conference venue is at Building CII of the Graduate School at Shenzhen, Tsinghua

University. Namely, CII 栋深圳大学城清华园区 (in Chinese).

Address: Tsinghua Campus, The University Town, Shenzhen 518055, P.R. China

Local Maps:


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How to reach to Conference Venue for international participants?

The best way from Shenzhen Bao’an International Airport is to take taxi to the conference

venue. It costs about RMB 100.00 (around 15 USD).

The address of the conference venue is “Building C, Graduate School at Shenzhen, Tsinghua

University, Tsinghua Campus, The University Town, Shenzhen 518055”. Namely, CII 栋深

圳大学城清华园区 (in Chinese).

交通信息 for domestic participants (http://www.sz.tsinghua.edu.cn/publish/sz/183/index.html)

深圳火车站至深圳研究生院的线路有：

1. 地铁线路：乘坐地铁 1 号线(罗宝线), 在车公庙站下车，转乘地铁 7 号线(西丽线)到

西丽湖站，自 D 出口上至地面,步行至清华校区。

2. 公交线路：火车站西广场乘 101 路，至深圳动物园站下，退 10 米走丽水路，沿西

湖林语小区北侧人行道步行至清华校区。

深圳北站（高铁站）至深圳研究生院的线路有：

地铁线路：乘坐地铁 5 号线(环中线), 在西丽站下车，转乘 7 号线(西丽线)到西丽湖

站，自 D 出口上至地面,步行至清华校区。

深圳机场至深圳研究生院的公交线路有：

1. 330 机场大巴

路线：在竹子林站下车、在马路对面转 101 路或 N5 路(夜班车)大巴到动物园站下，

退 10 米走丽水路，沿西湖林语小区北侧人行道步行至清华校区。

2. 地铁

路线：坐地铁 11 号线(机场线)至前海湾站，转乘地铁 5 号线(环中线)至西丽站，再

转乘地铁 7 号线(西丽线)到西丽湖站，自 D 出口上至地面,步行至清华校区。

http://www.sz.tsinghua.edu.cn/publish/sz/183/index.html


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Sponsors

International Society for

Computational Biology (ISCB)

Precision Medicine Research Center,

Taihe Hospital, Hubei, China

School of Public Health (Shenzhen),

Sun Yat-sen University, China

School of Electrical and Information

Engineering, Anhui University of

Technology, China

Graduate School at Shenzhen,

Tsinghua University, China

The University of Technology Sydney

(UTS), Australia


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Collaborating Journals

Bioinformatics

BMC Bioinformatics

BMC Genomics

BMC Systems Biology

IEEE/ACM Transactions on Computational Biology and Bioinformatics


Journal of Bioinformatics and Computational Biology

PeerJ

Contact information

For conference related matters, please contact:

Jinyan Li (phone number +61 450151181, international roaming)

Cen Yu (local phone number +86 15002085791)

Yang Yujiu (local phone number +86 15817212260)

Ma Lan (local phone number +86 18038153022)

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