A graduate student's experience in bioinformatics

19
A graduate student's A graduate student's experience in experience in bioinformatics bioinformatics Morgan Langille Morgan Langille BiNS, SFU BiNS, SFU Feb. 29, 2008 Feb. 29, 2008 http:// tinyurl.com/2woa4v

description

I present my experiences in bioinformatics with a focus of graduate school in the MSFHR/CIHR Strategic Training Program for Bioinformatics. This presentation was given to BiNS (Bioinformatics Network of Students) at SFU.

Transcript of A graduate student's experience in bioinformatics

Page 1: A graduate student's experience in bioinformatics

A graduate student's A graduate student's experience in bioinformaticsexperience in bioinformatics

Morgan LangilleMorgan LangilleBiNS, SFUBiNS, SFU

Feb. 29, 2008Feb. 29, 2008

http://tinyurl.com/2woa4v

Page 2: A graduate student's experience in bioinformatics

19991999Graduated High Graduated High

SchoolSchoolSussex, NBSussex, NB

No personal No personal computercomputer

Feb. 29, 2008Feb. 29, 2008 22BiNSBiNS

Page 3: A graduate student's experience in bioinformatics

Undergraduate at UNBUndergraduate at UNB

What can I do with a BSc (Biology) & a BCS?What can I do with a BSc (Biology) & a BCS?- Dean of Science, - Dean of Science,

““There is something called ‘Bioinformatics’” There is something called ‘Bioinformatics’” Feb. 29, 2008Feb. 29, 2008 33BiNSBiNS

Page 4: A graduate student's experience in bioinformatics

CS vs BiologyCS vs Biology

ORGORG $000$000NUM1NUM1 FCBFCB $00,$A1,$99,$23$00,$A1,$99,$23NUM2NUM2 FCBFCB $00,$A1,$A0,$A0$00,$A1,$A0,$A0RESRES FCBFCB $00,$00,$00,$00$00,$00,$00,$00

ORGORG $E000$E000LDABLDAB #$04#$04 COUNTERCOUNTERLDXLDX #NUM1#NUM1 X point to NUM1X point to NUM1LDYLDY #NUM2#NUM2 Y points to NUM2Y points to NUM2

L1:L1: LDAALDAA 0,X0,X load one byte to ACCaload one byte to ACCaCMPACMPA 0,Y0,Y compare it to Bcompare it to BBNEBNE L2L2 done if not eqdone if not eqINXINX advance the pointersadvance the pointers

Feb. 29, 2008Feb. 29, 2008 44BiNSBiNS

Page 5: A graduate student's experience in bioinformatics

CS vs BiologyCS vs Biology

Feb. 29, 2008Feb. 29, 2008 55BiNSBiNS

Page 6: A graduate student's experience in bioinformatics

BioinformaticsBioinformatics

Feb. 29, 2008Feb. 29, 2008 66BiNSBiNS

Page 7: A graduate student's experience in bioinformatics

Undergraduate ResearchUndergraduate Research

2002 Summer 2002 Summer – Computer science supervisorComputer science supervisor– PSI-BLAST improvementsPSI-BLAST improvements

2003 & 2004 Summer2003 & 2004 Summer– Genetics supervisorGenetics supervisor– Retro transposition duplications in Retro transposition duplications in DrosophilaDrosophila

Feb. 29, 2008Feb. 29, 2008 77BiNSBiNS

Page 8: A graduate student's experience in bioinformatics

Finished Undergrad 2004Finished Undergrad 2004

Considered:Considered:– Working (potato genomics)Working (potato genomics)– Med schoolMed school– Graduate SchoolGraduate School

CIHR/MSFHR Training Program in CIHR/MSFHR Training Program in BioinformaticsBioinformatics– Actual courses in bioinformaticsActual courses in bioinformatics– Several supervisors all working in bioinformaticsSeveral supervisors all working in bioinformatics– Guaranteed fundingGuaranteed funding

Feb. 29, 2008Feb. 29, 2008 88BiNSBiNS

Page 9: A graduate student's experience in bioinformatics

Applied and acceptedApplied and accepted

4 months later, 4 months later,

I was driving across I was driving across CanadaCanada

Upon arrival in Upon arrival in VancouverVancouver– Meet & GreetMeet & Greet

Met several supervisors Met several supervisors and other students in and other students in the programthe program

Feb. 29, 2008Feb. 29, 2008 99BiNSBiNS

Page 10: A graduate student's experience in bioinformatics

CoursesCourses

CMPT 881 - Computational BiologyCMPT 881 - Computational Biology

MBB841 - BioinformaticsMBB841 - Bioinformatics

CMPT 880 - Medical Image AnalysisCMPT 880 - Medical Image Analysis

MBB 659 - Special Topics in BioinformaticsMBB 659 - Special Topics in Bioinformatics

MEDG505 - Genome AnalysisMEDG505 - Genome Analysis

MBB505 - Problem Based Learning in BioinformaticsMBB505 - Problem Based Learning in Bioinformatics

Feb. 29, 2008Feb. 29, 2008 1010BiNSBiNS

Page 11: A graduate student's experience in bioinformatics

Research RotationsResearch Rotations

Bioinformatics encompasses a huge range of Bioinformatics encompasses a huge range of projectsprojects– Gene predictionGene prediction– Protein Structure ModelingProtein Structure Modeling– Drug DesignDrug Design– Protein InteractionsProtein Interactions– Data integration and visualizationData integration and visualization

BTP allows you to try out 3 different projects and BTP allows you to try out 3 different projects and supervisorssupervisors

Feb. 29, 2008Feb. 29, 2008 1111BiNSBiNS

Page 12: A graduate student's experience in bioinformatics

11stst Research Rotation Research Rotation

Deconstruction of Data Transformations into Reusable Web Deconstruction of Data Transformations into Reusable Web Services -> Leading to Data Integration Services -> Leading to Data Integration (Supervised by: Mark Wilkinson)(Supervised by: Mark Wilkinson)

GoalsGoals– Identify categories of data transformationsIdentify categories of data transformations– Describe categories in machine readable syntaxDescribe categories in machine readable syntax– Automate data transformationsAutomate data transformations

Approach: Break down bioinformatic use cases into Approach: Break down bioinformatic use cases into smaller generic transformation stepssmaller generic transformation steps

Use Case Example: Identification of SNPs that are Use Case Example: Identification of SNPs that are predictive of variation of disease statespredictive of variation of disease states

Feb. 29, 2008Feb. 29, 2008 1212BiNSBiNS

Page 13: A graduate student's experience in bioinformatics

22ndnd Research Rotation Research Rotation

Comparative Genomics Approach to Identifying Genomic Comparative Genomics Approach to Identifying Genomic Islands Islands (Supervised by: Fiona Brinkman)(Supervised by: Fiona Brinkman)

Genomic Islands (GIs) are regions of a genome that are thought to Genomic Islands (GIs) are regions of a genome that are thought to have originated from a horizontal transfer eventhave originated from a horizontal transfer event

Sequence based prediction methodsSequence based prediction methods– Search for genomic anomalies that suggest horizontal transfer Search for genomic anomalies that suggest horizontal transfer

%G+C, nucleotide bias, presence of mobility genes, etc%G+C, nucleotide bias, presence of mobility genes, etc

Comparative genomics based methodsComparative genomics based methods– Identify unique regions within a query genome that are not Identify unique regions within a query genome that are not

present in any closely related microbial genomespresent in any closely related microbial genomes

Feb. 29, 2008Feb. 29, 2008 1313BiNSBiNS

Page 14: A graduate student's experience in bioinformatics

33rdrd Research Rotation Research Rotation

Ontology Development for Flow Cytometry DataOntology Development for Flow Cytometry Data(Supervised by: Ryan Brinkman)(Supervised by: Ryan Brinkman)

To develop an ontology for flow cytometry dataTo develop an ontology for flow cytometry data

Using the OWL (Web Ontology Language) and Protégé Using the OWL (Web Ontology Language) and Protégé ontology editor ontology editor

Integrate new ontology with the FuGO upper ontologyIntegrate new ontology with the FuGO upper ontology

Use existing knowledge base from ExperibaseUse existing knowledge base from Experibase

Feb. 29, 2008Feb. 29, 2008 1414BiNSBiNS

Page 15: A graduate student's experience in bioinformatics

Life during BTP…Life during BTP…

Everyone goes to their own labs, but still keep in touch!Everyone goes to their own labs, but still keep in touch!

Student Representative on the BTP Steering CommitteeStudent Representative on the BTP Steering Committee

Monthly student “meetings”Monthly student “meetings”

VanBUG (Vancouver Bioinformatics User Group) VanBUG (Vancouver Bioinformatics User Group)

BTP Wiki BTP Wiki

Facebook GroupFacebook Group

Feb. 29, 2008Feb. 29, 2008 1515BiNSBiNS

Page 16: A graduate student's experience in bioinformatics

ConferencesConferencesOne perk of being a graduate studentOne perk of being a graduate studentBTP has a travel allowanceBTP has a travel allowance

Feb. 29, 2008Feb. 29, 2008 1616BiNSBiNS

Page 17: A graduate student's experience in bioinformatics

Life after graduate schoolLife after graduate school

AcademiaAcademia– Professors, Research Associate, Research Assistants, …Professors, Research Associate, Research Assistants, …

IndustryIndustry– PharmaPharma

Drug designDrug design

– AgricultureAgricultureLivestockLivestockPlantsPlants

– Personal GenomicsPersonal GenomicsSNPsSNPs$1000 personal genome$1000 personal genome

http://www.bioinformatics.org/jobs/http://www.bioinformatics.org/jobs/Feb. 29, 2008Feb. 29, 2008 1717BiNSBiNS

Page 18: A graduate student's experience in bioinformatics

My 2 centsMy 2 cents

Bioinformatics is not a bubbleBioinformatics is not a bubble– The skills you learn will be applicable in the futureThe skills you learn will be applicable in the future

Think carefully about choosing your supervisor Think carefully about choosing your supervisor and projectand project– Talk to the supervisorTalk to the supervisor– Talk to lab membersTalk to lab members– Talk to others in the communityTalk to others in the community– Read recent papers from the labRead recent papers from the lab

Masters or PhD? Masters or PhD? – Start in Master’s, then after 1 year reassessStart in Master’s, then after 1 year reassess

Feb. 29, 2008Feb. 29, 2008 1818BiNSBiNS

Page 19: A graduate student's experience in bioinformatics

AcknowledgementsAcknowledgements

Feb. 29, 2008Feb. 29, 2008 1919BiNSBiNS

http://tinyurl.com/2woa4v