PROGRAMME : M. TECH BIOINFORMATICS CURRICULUM€¦ · Kutta Method of fourth order- Runge ... 8th...

SATHYABAMA UNIVERSITY FACULTY OF BIO AND CHEMICAL ENGINEERING

PROGRAMME : M. TECHBIOINFORMATICS

CURRICULUMSEMESTER - 1

Sl. No. COURSE CODE COURSE TITLE L T P C PAGE No.

1. SMT5103 Applied Mathematics 3 1 0 4 1

2. SBI5101 Introduction to Bioinformatics 3 1 0 4 4

3. SBI5102 Biophysical Chemistry 3 1 0 4 5

4. SBI5103 Genomics and Proteomics 3 1 0 4 6

5. SBI5104 Medicinal and Pharmaceutical Chemistry 3 1 0 4 7

6. SBI5105 Computational Biology 3 1 0 4 8

PRACTICAL

7. SBI6531 PERL Programming and Biological Databases Lab 0 0 6 3 63

TOTAL CREDITS: 27

SEMESTER - 2


1. SBI5106 Biological Sequence Analysis 3 1 0 4 9

2. SBI5107 Molecular Modeling and Drug Design 3 1 0 4 10

3. ELECTIVE I 3 1 0 4

4. ELECTIVE II 3 1 0 4

5. ELECTIVE III 3 1 0 4

PRACTICAL

6. SBI6532 Sequence Analysis and Molecular Modeling Lab 0 0 6 3 64

7. S33PT Professional Training 0 0 10 5

TOTAL CREDITS 28

SEMESTER - 3


1. SBI5201 Systems Biology and Metabolic Engineering 3 1 0 4 18

2. ELECTIVE IV 3 1 0 4

3. ELECTIVE V 3 1 0 4

4. ELECTIVE VI 3 1 0 4

L - LECTURE HOURS, T – TUTORIAL HOURS, P – PRACTICAL HOURS, C – CREDITS

M.E. / M.Tech REGULAR xi REGULATIONS 2015

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PRACTICAL

5. SBI6535 JAVA Programming & Systems Biology Lab 0 0 6 3 66

6. Project Work - Phase I

TOTAL CREDITS 19

SEMESTER - 4


1. S33PROJ Project Work - Phase I & II 0 0 40 20

TOTAL CREDITS 20

TOTAL CREDITS FOR THE PROGRAMME: 94

LIST OF ELECTIVES


1. SBI5601 Structural and Functional Genomics 3 1 0 4 78

2. SBI5602 Microarray- Techniques and Applications 3 1 0 4 79

3. SBI5603 Data Mining For Bioinformatics 3 1 0 4 80

4. SBI5604 PERL & CGI Programming 3 1 0 4 81

5. SBI5605 Machine Learning for Bioinformatics 3 1 0 4 82

6. SBI5606 High Performance Computing 3 1 0 4 83

7. SBI5607 Applied Bioinformatics 3 1 0 4 84

8. SBI5608 Clinical Data Management 3 1 0 4 85

9. SBI5609 Neuroinformatics 3 1 0 4 86

10. SBI5610 Computational Chemistry 3 1 0 4 87

11. SBI5611 Immunoinformatics & Computational Vaccinology 3 1 0 4 88

12. SBI5612 Cheminformatics 3 1 0 4 89

M.E. / M.Tech REGULAR xii REGULATIONS 2015

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M.E. / M.Tech REGULAR 1 REGULATIONS 2015

SMT5103 APPLIED MATHEMATICS

(Common to M.Tech Bio-Technology & Bio-Informatics)

L T P Credits Total Marks

3 1 0 4 100

UNIT 1 MATRIX THEORY 11 Hrs. QR decomposition – Eigen values using shifted QR algorithm - Singular Value Decomposition - Pseudo inverse- Least square approximations.

UNIT 2 CALCULUS OF VARIATIONS 13 Hrs. Concept of Functionals - Euler’s equation – functional dependent on first and higher order derivatives – Functionals on several dependent variables – Iso perimetric problems - Variational problems with moving boundaries

UNIT 3 MULTIVARIATE ANALYSIS 13 Hrs. Multiple Regression Analysis - Principal Component Analysis – Canonical Correlation Analysis – Factor Analysis – Discriminant Analysis – Cluster Analysis (No Derivations)

UNIT 4 NUMERICAL METHODS – I 11 Hrs. Numerical solution of Ordinary Differential equation – Euler’s method – Modified Euler’s method - Runge - Kutta Method of fourth order- Runge - Kutta method of simultaneous first order differential equation- Runge - Kutta method of second order differential equation-Milne’s Predictor Corrector method- Adam-Bashforth predictor - corrrector method

UNIT 5 NUMERICAL METHODS – II 12 Hrs. Numerical solution of Partial Differential Equations- Classification- Elliptic equations-Solution of Laplace equation by Liebmann’s Iteration process- Poisson equation- Parabolic equation - Bender Schmidt Method- crank Nicholson Difference Method- Solution for Hyperbolic equation

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Narayanan S., Manicavachagom Pillay T.K., Ramanaiah G., Advanced Mathematics for Engineering students, Volume I, 2nd

Edition, S.Viswanathan Printers and Publishers, 1992. 2. Venkataraman M.K., Engineering Mathematics – First Year, 2nd Edition, National Publishing Company, Chennai, 2000. 3. Kreyszig.E, Advanced Engineering Mathematics, 8th Edition, John Wiley & Sons, Singapore, 2001. 4. Jain M.K., Iyengar SRK and Jain R.L., Numerical Methods for Scientific and Engineering Computation, Wiley Eastern Ltd.,

1987 5. Balagurusamy E., Numerical Methods – Tata McGraw Hill, 2000 6. Veerarajan T., Engineering Mathematics for First Year, 2nd Edition, Tata McGrawHill Publishers, 2008. 7. Dr. Kandasamy P. Numerical Methods, S.Chand & Company, New Delhi, 2003.

END SEMESTER EXAMINATION QUESTION PAPER PATTERN Max. Marks : 80 Exam Duration : 3 Hrs. PART A : 6 Questions of 5 Marks each – No Choice 30 Marks PART B : 2 Questions from each unit of internal choice, carrying 10 Marks each 50 Marks

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SBI5101 INTRODUCTION TO BIOINFORMATICS L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE To enable the student to have knowledge in bioinformatics tools and databases. This will facilitate the student to

do projects in modern biology.

UNIT 1 INTRODUCTION TO BIOINFORMATICS 12 Hrs. History of Bioinformatics-role of Bioinformatics in biological sciences- genetic material-central dogma-introduction to internet-WWW, network basics, LAN & WAN standards-network topologies and protocols- FTP, HTTP, HTML, URLs, network-EBNet, NCBI network– algorithm-introduction to biological algorithm- division of Bioinformatics- Bioinformatics program in India. Representing and reasoning about sequence data.

UNIT 2 DATABASES IN BIOINFORMATICS 12 Hrs. Databases contents in Bioinformatics- nucleotide databases - Genbank, NCBI, EMBL, DDBJ, UniGene, SGD, EMI Genomes, -protein databases-classification of protein databases-PIR, SWISSPROT, TrEMBL, Prosite, PRINTS -structural databases-PDB, MMDB, SCOP, CATH, PDB_SELECT,PDBSUM, DSSP, FSSP, DALI, PRODOM, protein families & pattern databases, Pfam, KEGG - sequence storage sequence accuracy-EST,STS- sequence retrieval systems- Entrez-SRS- sequence query refinement using Boolean operators, limits, preview, history and index. Protein-Protein Interaction Networks, databases: PPI Server, BIND, MINT, GRID, PIM – Hybrigenics.

UNIT 3 SEQUENCE SUBMISSION 12 Hrs. Sequence submission tools-BANKIT-SEQUIN-WEBIN-SAKURA- literature databases: PubMed and Medline. Mathematical model databases, Taxonomic databases, RNA databases. Data mining and its techniques - data warehousing - Sequence annotation: principles of genome annotation - annotation tools & resources. Genomic databases: Introduction, Genome projects, Genome browsers, UCSC, NCBI, Ensembl. InterPreTS - protein interaction prediction through tertiary structure.

UNIT 4 APPLICATIONS OF BIOINFORMATICS 12 Hrs. Applications of Bioinformatics - phylogenetic analysis-steps in phylogenetic analysis-microarrays - DNA and protein microarrays - Bioinformatics in pharmaceutical industry: informatics & drug- discovery - pharmainformatics resources drug discovery and designing-SNP. Application of Bioinformatics in Agriculture, Medicine, Environment, Biodiversity and research.

UNIT 5 FILE FORMATS AND TOOLS 12 Hrs. File formats-raw/plain format-NCBI, Genbank flat file format-ASN.1, GCG, FASTA, EMBL, NBRF, PIR, swissprot sequence formats, PDB format, etc. - introduction to structure prediction methods. Introduction to software and tools.

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Attwood T.K and Parry-Smith, Introduction to Bioinformatics, Addison Wesley Longman, 1999. 2. David W Mount, Bioinformatics: Sequence and Genome Analysis, 2nd edition, CBS publishers, 2004. 3. Arun Jagota, Data Analysis and Classification for Bioinformatics, Pine Press, 2001. 4. Des Higgins and Willie Taylor, Bioinformatics Sequence, Structures and Databanks, Oxford University Press, USA, 2000.


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SBI5102 BIOPHYSICAL CHEMISTRY L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE To have a thorough knowledge in the concepts of biophysics, which will enable the student to have a better vision

of the molecules and the nature.

UNIT 1 PRINCIPLES OF BIOPHYSICS 12 Hrs. Principles of biophysics: Methods for separation and characterization of macromolecules: general principles, sedimentation, Centrifugation techniques- principles, types and applications. Ultracentrifugation- types, optical methods used and applications of preparative and analytical ultracentrifuges. mechanisms of information storage, processing, retrieval in biological system.

UNIT 2 CHROMATOGRAPHY 12 Hrs. Chromatography- Principles, methodology and applications of chromatography using paper, thin layer, column (gel filtration, ion exchange, affinity), gas and types of HPLC. Electrophoresis- Principles and types of electrophoresis and their applications for proteins, nucleic acids, including gradient gel and pulse-filed gel electrophoresis; Agarose gel electrophoresis.

UNIT 3 SPECTROSCOPY 12 Hrs. Spectroscopic Techniques. Principle, Instrument Design, Methods & Applications of UV-Visible Spectra, IR Spectra, Raman Spectra, Luminescence spectroscopy: fluorescence - phosphorescence, NMR and ESR Spectra. Circular dichroism and optical rotatory dispersion. Elastic and inelastic scattering. Optical absorption, Photoemission, Inverse photoemission, Beer law, Electron energy loss.

UNIT 4 X-RAY DIFFRACTION 12 Hrs. Basics of crystallography,Crystals, Molecular crystal symmetry, X- rays- production and properties of X-ray, Characteristics of X-ray lines, Application of XRD, Instrumental sources of error. Basic features of typical XRD elements. X-ray Absorption and diffraction X-ray diffraction by crystals, Bragg’s Law, Constructive and destructive interference of waves. Detection of diffracted-x-rays. Laue powder and rotation methods, Calculating electron density and Patterson maps (Fourier transform and Structure factors, convolutions), phases, X-ray Absorption and diffraction, X-ray fluorescence, detection and applications Neutron diffraction, Electron diffraction, Application in Biology.

UNIT 5 MOLECULAR THERMODYNAMICS 12 Hrs. Molecular thermodynamics – complexities in modeling macromolecular structure, molecular mechanics, stabilizing interactions in macromolecules, Disulphide bridges, Role of water and weak interactions, simulating macromolecular structure- Statistical thermodynamics: general principles, structural transitions in polypeptides and proteins, structural transitions in polynucleotides and DNA, non-regular structures, operon.

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Upadhyay and Upadhya Nath, Biophysical Chemistry, Himalaya Publishing House, 2009. 2. Keith Wilson and John Walker, Practical Biochemistry, Fifth edition, Cambridge University Press, 2000. 3. Douglas A. Skoog, Instrumentation analysis, Stanford University Publisher, 2003. 4. Cantor R., Schimmel P.R., Biophysical Chemistry, Vol. I, II, W.H. Freeman & Co., 1985.


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SBI5103 GENOMICS AND PROTEOMICS L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE This paper enables the student to understand the mechanism of single gene giving rise to more than one protein.

UNIT 1 GENOMES & GENOME PROJECTS 12 Hrs. Brief outlook of various genome projects and their outcome Genome projects- overview and importance- Human Genome Project – Goals, Ethical, Legal, Social Issues of HGP - IPR & Patents, variations in the general structure and organization in genomes expression profiles.

UNIT 2 MAPPING GENOMES 12 Hrs. Genome marking and mapping techniques- genetic marker – RFLP, STR, SSLP, VNTR, AFLP, RAPD, SINES AND LINES, Alu Family - Physical marker, EST, STS, FISH, Radiation hybrid, Sequence marker, SNP’s Various techniques of genome sequencing – short gun, direct short gun, clone contig approach, chromosome walking, primer walking, chromosome jumping, genomic DNA library, cDNA library- Mapping and Sequence assembly, Expression analysis,

UNIT 3 GENOMIC DATABASES & MICROARRAY 12 Hrs. Genome databases – Completely sequenced eukaryotic genomes – Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster,Arabidopsis thaliana , MGD (Mouse genome database). HGC- NCBI, and EMBL, EBI genome, celera, DNA Microarray –Brief overview of various microarray data analysis methods. From Expression data to Pathways– SAGE. DNA chip or Gene chip.Application of microarray: expression analysis. Microarray database: Affymetrix, ArrayExpress, Comparative genome databases.

UNIT 4 PROTEOMICS 12 Hrs. Proteome projects and their significance. Proteomic Technologies – Protein separation technologies: 2D-PAGE for proteome analysis, Liquid chromatography. Protein detection – Protein identification and characterization: Mass spectrometry –Principles of mass spectrometry. EMI – MS, Tandem MS, TOF – MS.

UNIT 5 PROTEOME ANALYSIS 12 Hrs. Proteome analysis- Proteome – Bridging Genomics and Proteomics – Analysis of Proteome – 2D PAGE – Mass spectrometry – MALDI TOF – Micro array Technology - Application of Proteome analysis –– Protein Chips Application. Drug Development and Toxicology- Legal aspects of Genomics & proteomics – Bioethics – IPR & Patents.

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. T.A. Brown., Genomes., John Wiley & Sons, 2002. 2. David W. Mount., Bioinformatics – Sequence & Genome Analysis., CBS Publishers, 2003. 3. Proteomics: From Sequence to Function by S.Pennington and M.Dunn, 2000. 4. Introduction to Proteomics: A tool for new Biology by Daniel C.Leibler, 2002. 5. S.Sahai, Genomics and Proteomics, " Functional an Computational Aspects ", Pienum Publications, 1999


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SBI5104 MEDICINAL AND PHARMACEUTICAL

CHEMISTRY L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE This paper enables the student to apply their knowledge in applying the principles in organic, physical, medicinal

and analytical chemistry to pharmaceuticals.

UNIT 1 OVERVIEW OF MEDICINAL CHEMISTRY 12 Hrs. What is Drug? Drug Targets, Pharmacokinetic issues and medicines - Classification of drugs. Properties of drugs - Sources of drugs - plant, animal, synthetic - Recombinant technology - Nomenclature of drugs- INNs, BAN, USAN - History and their role in formulation development & therapeutics and clinical setting - Route of Administration - Oral, parentral, Rectal, Topical administration - Inhalation.

UNIT 2 PHARMACOKINETICS 12 Hrs. Absorption, distribution, metabolism (biotransformation) and excretion (elimination) of drugs - Physicochemical, biological and pharmaceutical factors altering biopharmaceutical performance of drugs - Passage of drugs across biological barrier (passive diffusion, active transport, facilitated diffusion and pinocytosis) - Factors influencing absorption physiochemical, physiological and pharmaceutical - Drug distribution in the body, plasma protein binding.

UNIT 3 PHARMACODYNAMICS 12 Hrs. Introduction- Enzymes-structure and function - Inhibitors acting at the active site of an enzyme, Inhibitors acting at allosteric binding sites, Uncompetitive and non-competitive inhibitors - Transition-state analogues, suicide substrates - Isozyme selectivity of inhibitors - Medicinal uses of enzyme inhibitors -Drug Action – physicochemical properties and stereo chemistry of compound. Isosterism and bioisosterism Enzyme kinetics - Receptors - Structure and function - the design of agonists, antagonists, partial agonists, inverse agonists, receptor types & subtypes.

UNIT 4 PHARMACOLOGICAL EFFECT OF DRUGS 12 Hrs. Classification- antibacterial agents - Mechanism of antibacterial action - antimetabolites - sulfonamides – application of sulfonamides - penicillins - structure and mechanism of action, structure activity relationships of penicillins – antiviral agents, anticancer agents and antiulcer agents – Allergic drugs and anti-allergic drugs – Mode of action – Side effects of drugs - Advantages and disadvantages - structure and mechanism of drug action.

UNIT 5 DRUG DISCOVERY 12 Hrs. Physicochemical properties in relation to drug design - structure activity relationship - isoelectric replacement – QSAR Hansch (property - property relationship) and free Wilson (Structure - property relationship) analysis - SAR vs QSAR - 3DQSAR –CoMFA - HINT – CoMSIA – CoMASA – SOMFA – HASL - CoMMA - MS-Whim - Devising a research strategy - challenges in drug discovery, development of new drugs - legal aspects of product protection - getting drug to market. Clinical trials and post market validation.

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Graham L.Patrick, An Introduction to Medicinal Chemistry, Oxford University Press, 2009. 2. Camille.G.Wermuth, The Practice of Medicinal Chemistry, 3rd Edition, Academic Press, 2008. 3. Wilson & Gisvold’s, Lippincott Williams & Wilkins, Text book of Organic Medicinal and Pharmaceutical Chemistry, 11th

Edition, 2003. 4. Frank D King, Medicinal Chemistry- Principles and Practice, Royal Society of Chemistry, 1994. 5. Tripathi K.D., Essentials of Medicinal Pharmacology, 5th Edition, Jaypee Medical Publishers, India, 2004. 6. Seth S.D, Vimlesh Seth, Text book of Pharmacology, 3rd Edition, Elsevier India, 2009.


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SBI5105 COMPUTATIONAL BIOLOGY L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE This paper enables the student to apply a predictive model to understand the mechanism of various

biomolecules.

UNIT 1 INTRODUCTION 12 Hrs. Introduction to Bioinformatics and Computational Biology with historical background, major developments. Strings & Graphs-Native string search, Suffix tree, KMP Algorithms, Boyer-Moore Algorithms, Sequence alignment- Alignment Algorithms for two sequences., Advance sequence alignment techniques- linear space, Gap penalty, Affine gap, Time warping. - Topics based on basic string matching.

UNIT 2 BASIC PROBABILITY 12 Hrs. Basic probability and statistics theory: Random Variables, Probability distribution, Combinatorial Optimization. Markov processes, Entropy - application. Restriction maps: graphs, interval graphs, measuring fragment sizes- Matrices- PAM & BLOSUM

UNIT 3 DATABASES & GRAPHIC SEQUENCE ANALYSIS 12 Hrs. Databases & graphic sequence analysis: DNA and Protein sequence databases - Sequence alignment, Dynamic programming-Progressive alignment, alignment - global distance alignment(indel functions, position dependent weights) algorithm,-local alignment algorithm(self comparision ,tandem repeats) - Multiple sequence alignment algorithm - Sequence alignment with scores, Markov model, Hidden markov model – CpG. Gene finding – gibbs sampling.

UNIT 4 STRUCTURE PREDICTION 12 Hrs. Structure prediction: secondary structure prediction -GOR, CHOU-FASMEN, Support vector machine (SVM), Hidden markov model (HMM). RNA structure prediction – combinatorics, consensus folding. Tools for RNA structure prediction, amino acid pair potential, lattice model of protein- Hart & initial approximate algorithm, tertiary structure prediction : homology modellling- ab-initio method- minimization energy structure - protein threading. Accessment and evaluation of 3-D structure.

UNIT 5 PHYLOGENETIC ANALYSIS 12 Hrs. Phylogenetic Analysis:Introduction-basic steps in phylogenetic analysis- Introduction to systematics – Classification systems – Phylocode and Biocode - phenetic method-UPGMA, cladistic – clustering method- Maximum likelihood, maximum parsimony. Estimating Sampling errors using Bootstrap- Transformed Distance, Neighbors- Relation, Neighbor-Joining - Evolutionary analysis: use of the PHYLIP package- tree construction -trees and sequences: trees, distances - Models of sequence Evolution Molecular Clock Application of Phylogenies. Types of phylogenetic tree. Tree evaluation methods –Randomization method and Skewness test.

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Michael Waterman, Introduction to Computational Biology: Maps, Sequences & Genomes, Chapman & Hall, 1995. 2. Hugo O. Villar, Advances in computational biology, Jai press Inc, 1996. 3. Dan Gusifield, Algorithm on strings, trees, & sequences: Computer Science & Computational Biology, 1997. 4. John Abelson, Russell F. Doolittle, Melvin I. Simon, Methods in Enzymology, Vol & 266, 1996. 5. Peter Clote and Rolf Backofen, Computational molecular biology, 2000.


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SEC6540 EMBEDDED SYSTEMS AND CIRCUITS LAB (For MI)

L T P C Total Marks

0 0 6 3 100

Experiments based on Analog Integrated Circuits i) Basic inverting adder, non inverting adder, unity follower. ii) Instrumentation Amplifier iii) High pass, low pass and band pass filter design iv) Comparator and wave form generator.

Experiments based on Advanced Digital System Design i) Half and full adder ii) Half and full subtractor iii) Study of basic flip flops iv) Study of registers and counters.

Experiments based on Advanced Microcontrollers & Embedded Systems i) Basic system design using PIC microcontroller. ii) Basic system design using AVR microcontroller. iii) Study of ARM Processor.

SBI6531 PERL PROGRAMMING AND BIOLOGICAL DATABASES LAB

L T P C Total Marks 0 0 6 3 100

PERL PROGRAMMING LAB 1. Perl basics and variables 2. Control and loop statements 3. To find greatest of 3 numbers 4. To check whether a number is prime or not 5. Generating fibonacci series 6. To perform matrix addition & multiplication 7. Functions and subroutines 8. Command line argument 9. Regular expressions 10. Perl web server 11. Modules:LWP 12. Translate DNA to protein by using perl module 13. Program to perform file handling, concatenation& string length 14. Program- shift, unshift, splice & slice 15. Program to perform until, for, for each, while operations 16. Program to perform GC count, chop, chomp, reverse compliment 17. File handling using arrays and scoping of variables 18. BIOPERL: objects in Bioperl, using Bioperl

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SBI5106 BIOLOGICAL SEQUENCE ANALYSIS L T P Credits Total Marks 3 1 0 4 100

COURSE OBJECTIVES Students are allowed to explore the fundamentals of local and global alignments along with the usage of a

substitution Matrix. Students are further exposed to heuristic techniques in aligning and analyzing a multiple sequence.

UNIT 1 INTRODUCTION TO SEQUENCES & PAIRWISE SEQUENCE ALIGNMENTS 12 Hrs. Biological sequence datas, Sequence similarity & homology , Pairwise alignment techniques – Dot matrix, Dynamic programming Algorithm of Pairwise alignment, Global alignment, Local alignment methods, Measures of sequence alignment - Scoring system – PAM and BLOSUM substitution matrices, Gap penalty. Sequence file formats: GenBank, FASTA, GCG, MSF

UNIT 2 MULTIPLE SEQUENCE ALIGNMENT & DATABASES SEQUENCE similarity 12 Hrs. Multiple sequence alignment – progressive methods, Iterative methods ,Hidden Markov Models in multiple sequence alignment. Specific scoring matrices, Tools for multiple sequence alignment. CLUSTAL W, PILEUP. Heuristic algorithms – FASTA and BLAST, Gapped BLAST & PSI BLAST, PHI-BLAST, E-value - Significance of sequence alignment..

UNIT 3 PHYLOGENETICS 12 Hrs. Basics for Phylogenetics - Construction of phylogenetic trees - Phylogenetic Analysis Tree building methods - Distance methods - FM, UPGMA, NJ. Character based method-MP & ML, phylogenetic software. Comparison of NA – Protein based phylogenetic analysis.

UNIT 4 PREDICTIVE METHODS ON Protein SEQUENCES 12 Hrs. Predictive methods: Different secondary structure prediction methods – Chou fasman method, GOR method, Algorithm behind the methods - Tools used for secondary structure prediction - Prediction methods using Protein sequences – PRPSEARCH, MOWSE, TGREASE, SAPS, BLOCKS, nnpredict, PredictProtein, PREDATOR, PSIPRED, JPRED, SOPMA Protein sequence analysis: Compositional analysis; Hydrophobicity profiles; Amphiphilicity detection; Moment analysis; Transmembrane prediction methods; Secondary structure prediction methods

UNIT 5 PREDICTIVE METHODS ON NUCLEIC ACID SEQUENCES 12 Hrs. Prediction methods using DNA sequences – Michael Zhan’s Exon Finder, Gene scan, Morgan, Genie, Gene finder, Gene parser. Predictive methods using protein sequences- Prediction of RNA secondary structure- Expressed sequence tags (ESTs).

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. David W. Mount. Bioinformatics: Sequences and genome analyses. Cold Spring Harbor Laboratory press, 2000. 2. Durbin R., Eddy S., Krogh A.& Mitchison G., Biological Sequence Analysis: Probabilistic Models of Proteins & Nucleic

Acids,Cambridge University Press, 1999. 3. Des Higgins, Willie Taylor. Bioinformatics Sequence Structure & Data Banks. A practical approach. 2010 4. Gusfield D., Algorithms on Strings, Trees & Sequences: Computer Science & Computational Biology, Cambridge University

Press,1997. 5. Pevzner P., Computational Molecular Biology: An Algorithmic Approach, MIT Press, 2000. 6. Setubal J. & Meidanis J., Introduction to Computational Molecular Biology, PWS Publishing Company, 1997.


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SBI5107 MOLECULAR MODELING AND DRUG DESIGN L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE Awareness regarding the designing of molecules and drugs is provided. The various concepts in the modeling of

molecules like quantum mechanics and energy minimization along with the structure function relationship is also dealt with.

UNIT 1 QUANTUM CHEMISTRY & THERMODYNAMICS 12 Hrs. Basic concepts in molecular modeling - Internal parameters - Z-matrix – Introduction to quantum chemistry –basic postulates – Schrodinger wave equation – Derivation – Hydrogen atom – Born-Oppenheimer approximation - Laws of thermodynamics - entropy – enthalpy - free energy calculations-chemical potential - Calculating thermodynamic properties using force field; Transferability of force field parameters, treatment of delocaliised pi system; Force field for metals and inorganic systems – Application of energy minimization.

UNIT 2 MOLECULAR MECHANICS & VISUALIZATION 12 Hrs. Molecular geometry - Conformational parameters - Potential energy Surface - Molecular mechanics: empirical forces fields - bond stretching - angle bending - torsional terms – non-bonded and electrostatic interaction - types of force fields - energy minimization - simplex – sequential univariate method - steepest descent - conjugate gradient method - Newton–Raphson method – Molecular Dynamics with continuous potentials and at constant temperature and pressure; Timedependent properties; Solvent effects in Molecular Dynamics - Conformational analysis - Molecular visualization - Molecular graphics – Rendering - Rasmol.

UNIT 3 MOLECULAR DYNAMICS 12 Hrs. Molecular Dynamics(MD) simulation of biopolymers - time steps - Setting up MD - energy conservation in MD Simulation -continuous potentials and constraint dynamics - MD at constant temperature and pressure - incorporating solvent effects - examples-random number generator - Monte Carlo simulation of biological macromolecules - MD softwares.

UNIT 4 STRUCTURE PREDICTION 12 Hrs. Prediction of secondary structure - membrane prediction – Comparative modeling - Sequence Alignment Homolog’s - analogs - Homology modeling - steps in homology modeling – side chain modeling – loop modeling - fold recognition – ab initio prediction – Predicting protein structures by threading protein folding – active site/binding site prediction – tools – databases - CASP.

UNIT 5 DRUG DESIGN 12 Hrs. Drug Design: Role of Bioinformatics in drug design - Drug discovery cycle - Physicochemical principles of drug action - lead discovery - lead modification - optimization - Docking –docking algorithms - Structure Based Drug Design -Rational Design - Pharmacophore identification, Deriving 3D pharmacophore - Structure Activity Relationship: QSARs and QSPRs, QSAR Methodology, Various Descriptors used in QSARs: Electronic; Topology; Quantum Chemical based Descriptors. - ADME/T - de novo ligand design, Applications of 3D Database Searching and Molecular docking - drug delivery.

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Leach A.R. , Molecular Modelling - Principles and Applications, 2nd Edition, Prentice Hall, 2001. 2. Prasad R.K., Quantum Chemistry, Halsted Press, 1992. 3. Ramachandran K. I., Deepa G., Namboori K., Computational Chemistry and Molecular Modeling: Principles and Applications,

Springer, 2008. 4. McCammon, J.A. and Harvey, S.C., Dynamics of Proteins and Nucleic Acids, Cambridge University Press, Cambridge, 1987. 5. Young, D.C., Computational Chemistry: A Practical Guide for Applying Techniques to Real-World Problems, Wiley-

Interscience, 2001.


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BIOLOGICAL DATABASES LAB 1. Retrieval of sequences from NCBI 2. ORF Finder 3. Retrieval of sequences from EBI 4. Retrieval of structures from PDB 5. Rasmol, Pymol, Jmol 6. Retrieval of sequences from DDBJ 7. KEGG 8. Retrieval of sequences from PIR 9. OMIM 10. Structural databases, SRS

SBI6532 SEQUENCE ANALYSIS AND MOLECULAR MODELING LAB


SEQUENCE ANALYSIS LABORATORY - Genetics Computing Group (GCG) - Version 10-UNIX 1. Database Searching and Retrieval 2. Reference Searching

i) Fetch ii) LookUp

3. Sequence Searching i) BLAST ii) FastA

4. Importing and Exporting i) Reformat

5. Pairwise Comparison i) Gap ii) BestFit iii) FrameAlign iv) Compare v) DotPlot

6. Multiple Sequence Comparison i) PileUp ii) SeqLab Editor iii) HmmerBuild iv) HmmerCalibrate

7. Gene Finding and Pattern Recognition i) Gene finder ii) Motifs iii) FindPatterns

8. Mapping i) Map ii) Restriction Mapping iii) Vector mapping (Vector contamination)

9. Primer Selection i) Prime

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SBI5201 SYSTEMS BIOLOGY & METABOLIC

ENGINEERING L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE Students are allowed to develop predictive mathematical models for biological systems.

UNIT 1 TERMINOLOGY & PRINCIPLES 12 Hrs. Basic Terminology & Principles – The Biology – Modeling – Properties of Models - Advantages of Computational Modeling - Typical Aspects of Biological Systems and Corresponding Models - Network Versus Elements – Modularity - Robustness and Sensitivity - Data integration – Living Science - The human genome landscape - Genetic regulation and disease – Differential Gene expression & Developmental Biology.

UNIT 2 STANDARD MODELS AND APPROACHES 12 Hrs. Standard Models and Approaches - Metabolic Engineering - Metabolic Networks - Translating biochemical networks into linear algebra - Systems Equations - Information Contained in the Stoichiometric Matrix N – Elementary Flux Modes and Extreme Pathways - Flux Balance Analysis - Approximations Based on Timescale Separation –Metabolic Control Analysis - The Coefficients of Control Analysis - The Theorems of Metabolic Control Theory - Extensions of Metabolic Control Analysis - Selected Biological Processes - Cell Cycle - Aging.

UNIT 3 MODELING OF GENE EXPRESSION 12 Hrs. Modeling of Gene Expression – Modules of Gene Expression - Promoter Identification - Modeling Specific Processes in Eukaryotic Gene Expression - Description with Ordinary Differential Equations - Representation of Gene Network as Directed and Undirected Graphs - Bayesian Networks - Boolean Networks - Gene Expression Modeling with Stochastic Equations - Analysis of Gene Expression Data - Data Capture - Clustering Algorithms – Reverse Engineering Genetic Networks - Stochastic simulation methods and constraint based models – E-cell Project.

UNIT 4 EVOLUTION AND SELF - ORGANIZATION 12 Hrs. Evolution and Self-organization - Quasispecies and Hypercycles - Other Mathematical Models of Evolution - Prediction of Biological Systems from Optimality Principles - Data Integration - Database Networks – Information Measurement in Heterogeneous Data - The Human interactome - Protein-DNA and Protein-Protein Interactions – Scale free networks in Cell Biology.

UNIT 5 INFORMATION RETRIEVAL AND EXAMINATION 12 Hrs. Computer-based Information Retrieval and Examination – Systems Biology Databases and Tools on the Internet - Gene Ontology – Reactome - TRANSFAC and EPD - Genome Matrix - Modeling Tools - Modeling and Visualization - Mathematica and Matlab – Gepasi - E-Cell – PyBioS - Systems Biology Workbench – CellDesigner - Petri Nets -Model Exchange Languages, Data Formats - Systems Biology Markup Language - MathML.

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Edda Klipp, Ralf Herwig, Axel Kowald, Christoph Wierling, Hans Lehrach., Systems Biology in Practice: Concepts,

implementation and Application, Wiley-VCH, 2005. 2. Choi, Sangdun, Introduction to Systems Biology, Humana Press, 2007. 3. Alberghina, L. and Westerhoff, H, Systems Biology : Definitions and Perspectives, Springer, 2005.


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MICROARRAY DATA ANALYSIS 1. Working with Objects for Microarray Experiment Data. 2. Analyzing Illumina® Bead Summary Gene Expression Data. 3. Detecting DNA Copy Number Alteration in Array-Based CGH Data. 4. Analyzing Array-Based CGH Data Using Bayesian Hidden Markov Modeling. 5. Visualizing Microarray Data. 6. Gene Expression Profile Analysis.

MASS SPECTROMETRY DATA ANALYSIS 1. Preprocessing Raw Mass Spectrometry Data 2. Visualizing and Preprocessing Hyphenated Mass Spectrometry Data Sets for Metabolite and

Protein/Peptide Profiling. 3. Identifying Significant Features and Classifying Protein Profiles.

VISUALIZATION TOOLS 1. Working with Graph Theory Functions. 2. Working with the Clustergram Function. 3. Visually Representing Interconnected Data. 4. Visualizing the Three-Dimensional Structure of a Molecule.

SBI6535 JAVA PROGRAMMING ` & SYSTEMS BIOLOGY LAB


SYSTEMS BIOLOGY LAB 1. Modeling and Visuaklisation 2. E cell 3. Gepasi 4. Construction and Analysis of gene expression networks 5. Mat lab I 6. Mat Lab II

JAVA PROGRAMMING LAB

CLUSTER LAB 1. Parallel programming 2. MPI 3. MPI-BLAST 4. MPI-CLUSTALW 5. Running AMBER in Cluster

JAVA LAB 1. HTML program 2. Prime numbers 3. Floyds triangle 4. String search & String count 5. Inheritance 6. Interface 7. Exception handling 8. Applet program

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M. E. / M. Tech REGULAR 80 REGULATIONS 2015

SBI5601 STRUCTURAL AND FUNCTIONAL GENOMICS L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVES Students are allowed to acquire knowledge about the usage of high throughput tools for genome science. Students are allowed to comprehend, analyze, and evaluate the critical aspects of data interpretation in

genomics.

UNIT 1 INTRODUCTION 12 Hrs. Structure & Organization of Prokaryotic & Eukaryotic genome - Nucleotide and protein sequencing methods – Chemical, Enzymatic, high through put method – Automated sequencing methods – shotgun – chromosome walking, Contig assembly - Levels of structures in Biological macromolecules.

UNIT 2 CONFORMATIONAL ANALYSIS 12 Hrs. Biomolecules and their interactions - Forces that determine protein and nucleic acid structure, basic problems, polypeptide chains geometrics, potential energy calculations, observed values for rotation angles, hydrogen bonding, hydrophobic interactions and ionic interactions, disulphide bonds - Prediction of proteins structure - Nucleic acids, general characteristics of nucleic acid structure, geometrics, glycosidic bond rotational isomers - Ribose puckering -forces stabilizing ordered forms, base pairing, base stacking- tertiary structure of nucleic acids.

UNIT 3 STRUCTURAL ANALYSIS OF MACROMOLECULES 12 Hrs. Size and shape of macromolecules - methods of direct visualization - X-ray crystallography – X–ray diffraction, determination of molecular structures, electron microscopy, NMR. Protein structure databases - Protein Data Bank - SCOP - CATH - structure superposition - RMSD - TM-score- structure alignment - Different structure alignment algorithms - DALI, CE, VAST, TM-align - protein folds in PDB.

UNIT 4 STRUCTURE-FUNCTIONS RELATIONSHIP 12 Hrs. DNA binding proteins, Prokaryotic and Eukaryotic transcription factors - DNA polymerases, Helix-turn-Helix motif in DNA binding, Trp repressor, Zn fingers, helix-turn helix motifs in homeodomain, Leucine zippers - DNA polymerases,Membrane proteins and receptors, Trans-membrane segments, bacterio rhodopsin, photosynthetic centres, epidermal growth factor, insullin and PGDGF receptors and their interaction with effectors, protein phosphorylation, immunoglobulins, Serine proteases, ribonuclease, lysozyme.

UNIT 5 FUNCTIONAL GENOMICS 12 Hrs. Introduction to Functional Genomics - cytological maps - Hap Map - SNPs and variation- Genotyping, microarray- analysis and applications. Microarray oligo sets and fabrication - integrative genomics and Meta genomics. Quantitative Proteomics. Fluorescent imaging techniques. Quantitative RT-PCR analysis. High-throughput cloning and expression strategies. Next Generation Sequencing applications.

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Cantor R., Schimmel P.R.,Biophysical Chemistry, Vol. I, II, W.H. Freeman & Co., 1985. 2. Kensal E. van Holde, W. Curtis Johnson and P. Shing Ho, Principle of Physical Biochemistry, Prentice Hall, New York, 1998. 3. Pennington SR, Dunn MJ, Proteomics from Protein Sequence to Function, Viva Books Ltd, 2002. 4. G. Gibson and M. V. Muse. A primer of Genome Science. Sinauer Associates Inc; 2 edition, December 2004.


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SBI5602 MICROARRAY - TECHNIQUES AND APPLICATIONS


3 1 0 4 100

COURSE OBJECTIVE Students are allowed to understand the key concepts of class comparison and class discovery of genes.

UNIT 1 GENE EXPRESSION 12 Hrs. Basics of Gene expression- definition , gene expression studies, gene expression patterns- Applications of gene expression studies- Microarrays – definition , discovery,technique, making microarrays, spotted microarrays, Insitu synthesized oligonucleotide arrays, inkjet array synthesis, affymetrix techniques, DNA CHIP technology, photolithography, spot quality, sample preparation and labeling, washing, image acquisition Sequencing by Hybridization Arrays- DNA MassArray™ Technology- Printing DNA Microarrays-Types of micorarrays-Designing a microarray experiment.

UNIT 2 IMAGE PROCESSING 12 Hrs. Image processing, feature extraction, identifying positions of features- Normalisation – data cleaning and transformation, within array normalization , between array normalization, measuring and quantifying microarray variability –variability between replicate features on an array-, variability between hybridizations to different arrays. Analysis of differentially expressed genes- significance analysis of microarrays.

UNIT 3 PREDICTION 12 Hrs. Prediction of cross hybridization to related genes, thermodynamics of nucleic acid duplexes, prediction of Tm- probe secondary structure. Analysis of relationships between genes ,tissues or treatments- similarity of gene or sample profiles –dimensionality reduction, principal component analysis ,hierarchial clustering, machine learning methods for cluster analysis.classification of tissues and samples – validation.

UNIT 4 CARBOHYDRATE MICROARRAYS 12 Hrs. Carbohydrate microarrays- Carbohydrate sources- Synthesis of oligosaccharides - Isolation of oligosaccharides from natural sources- Arrays of monosaccharides and disaccharides- Arrays of polysaccharides- Arrays of oligosaccharides- Perspectives- DNA micro array analysis-clustering-immunological applications.

UNIT 5 DATABASES AND TOOLS FOR MICROARRAYS 12 Hrs. Bioinformatics in Arrays- Databases and tools for microarrays- Bioconductor, expression profiler, EST databases- Assessing levels of gene expression using EST’s , TIGR gene indices, STACK, SAGE,CGAP, Xprofiler, ARRAY DB, cluster, treeview, Scanalyze, genecluster, informatics aspects of microarray production- MGED and gene-ontology, description of MIAME ((Minimum Information About a Microarray Experiment), Business Aspects of Biochip Technologies- Microarray Technology in Treating Disease.

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Dov Stekel - Microarray bioinformatics, Cambridge, 2003. 2. Steen Knudsen - A Biologist's Guide to analysis of DNA microarraydata, second edition, John Wiley & Sons, Inc., 2004. 3. Andreas D Baxevanis and BF Francis Ouelette - Bioinformatics: A Practical Guide to the Analysis of Gene and Proteins ,

Wiley-Interscience, 1998 4. David W. Mount - Bioinformatics: Sequences and genome analyses, Cold Spring Harbor Laboratory press, 2000.


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SBI5603 DATA MINING FOR BIOINFORMATICS L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE Students are allowed to develop, apply and analyze the statistical techniques for solving the annotation problems

in bioinformatics

UNIT 1 MINING FREQUENT PATTERNS, ASSOCIATIONS AND CORRELATIONS 12 Hrs. Basic Concepts, Efficient and Scalable Frequent Itemset Mining Methods, Mining various kinds of Association Rules, From Association Mining to Correlation Analysis, Constraint-Based Association Mining.

UNIT 2 CLASSIFICATION AND PREDICTION 12 Hrs. Issues Regarding Classification and Prediction, Comparison of classification and prediction methods Classification by Decision Tree Induction, Advantages of decision tree, Tree pruning approaches, Direct acayclic graph representation, IF-THEN-RULES :Rule extraction, Rule pruning. Bayesian Classification, Rule-Based Classification, Classification by Backpropagation, Support Vector Machines, Associative Classification, Lazy Learners, Other Classification Methods, Prediction, Accuracy and Error measures, Evaluating the accuracy of a Classifier or a Predictor, Ensemble Methods.

UNIT 3 CLUSTER ANALYSIS INTRODUCTION 12 Hrs. Cluster-definition-Application of cluster analysis,Types of Data in Cluster Analysis, A Categorization of Major Clustering Methods, Partitioning Methods, Hierarchical Methods, Density-Based Methods, Grid-Based Methods, Model-Based Clustering Methods, Clustering High-Dimensional Data, Constraint-Based Cluster Analysis, Outlier Analysis.

UNIT 4 MINING STREAMS, TIME SERIES AND SEQUENCE DATA 12 Hrs. Mining Data Streams, Mining Time-Series Data, Mining Sequence Patterns in Transactional Databases, Mining Sequence Patterns in Biological Data, Graph Mining, Social Network Analysis and Multirelational Data Mining.Challenges in web mining. Mining Object, Spatial, Multimedia, Text and Web Data: Multidimensional Analysis and Descriptive Mining of Complex Data Objects, Spatial Data Mining, Multimedia Data Mining, Text Mining, Mining the World Wide Web.

UNIT 5 APPLICATIONS AND TRENDS IN DATA MINING 12 Hrs. Mining Applications, Data Mining System Products and Research Prototypes, Additional Themes on Data Mining and Social Impacts of Data Mining. Trends in data mining (visual data mining, Biological data mining, web mining, Distributed data mining, Real time data mining, Multi database data mining, privacy protection and security in data mining).

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Data Mining Techniques – Arun K Pujari,2nd edition, Universities Press,2001. 2. Insight into Data Mining,K.P.Soman,S.Diwakar,V.Ajay,PHI,2008. 3. Data Mining – Concepts and Techniques - Jiawei Han & Micheline Kamber, Morgan Kaufmann Publishers, Elsevier,2nd

Edition, 2006. 4. Introduction to Data Mining – Pang-Ning Tan, Michael Steinbach and Vipin Kumar, Pearson education,2014.


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SBI5604 PERL & CGI PROGRAMMING L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE Students explore the use of a specific class to parse the Common Gateway Interface query strings delivered by

POST (via STDIN) or GET (via ENVIRONMENT) requests.

UNIT 1 DATA TYPES 12 Hrs. Introduction to Perl – a functional approach –data types- strings- text formatting –printf– Introduction to arrays – qw function- split function – for each loop – advanced array operation – copying and creating arrays – populating arrays with sequential data – determination of the size of an array – counting arrays– accessing first element of an array -accessing last element in an array – adding elements – removing elements – altering elements – array slices – splicing array – sorting arrays – reversing arrays – arrays from strings- constructing atgc.pl

UNIT 2 PERL CONTROL STATEMENTS 12 Hrs. Perl control statements – control structures – if statements – if-else – if-elsif – if-elsif-else – while loop- do while loop – until loop – for loop – foreach loop – nested loops -- scoping of variables. Loop control statements –next statements—last statements – Continue statements– redo statements– goto statements. Perl regular expressions – special characters (+, *,? [ ]) – regex operator – pattern modifier operator – conditional matching operator – range operator – match quantifiers – Pattern comments. –the m// operator--the s/// operator – the chop and chomp operators- tr/// function

UNIT 3 FILES 12 Hrs. Files – Operating files – file modes – file test operators – accessing files with <>, @ ARGV variable – accessing file with perl modules – extracting files – deleting files – appending files. Introduction to Perl modules – the getopt: Long module – accessing directories – Cwd module – system function – perl sub routines and functions- trapping errors at run time.

UNIT 4 CGI 12 Hrs. Common Gateway Interface:- HTML form elements, GET, POST & HEAD Method, CGI Environment Variables, Handling forms, Passing Parameters via CGI, Debugging CGI programs. The LWP: Simple module HTML Specifications and Syntax,

UNIT 5 BIOPERL 12 Hrs. General Bioperl Classes, Sequences, Bioperl objects -- Sequence objects (Seq, Primary sequence, LocatableSeq, RelSegement, LiveSeq, RichSeq, SeqWithQuality, and SeqI), -- location objects – interface objects and implementation objects. Sequence Manipulation, Features and Location Classes. Alignments: AlignIO. Transforming sequence files (SeqIO). Identifying restriction enzyme sites, Identifying amino acid cleavage sites. Analysis: Blast, Genscan; Databases: Database Classes, Accessing a local database-– accessing remote databases- bioperl modules - parsing blast reports – align sequences – clustalw.pm – Tcofee.pm, Parsing HMM reports. Searching for genes and other structures in genomic DNA. Using 3D structure objects and reading PDB files. Tree objects and phylogenetic trees.

Max. 60 Hours TEXT / REFERENCE BOOKS 1. Harshawardhan P. Bal - Perl programming for Bioinformatics, Tata McGraw-Hill, 2004. 2. Larry Wall, Tom Christiansen & John Orwant, Programming Perl , 3rd ed, O’Reilly, 2000. 3. James D. Tisdall, Beginning Perl for Bioinformatics, O'Reilly, 2001. 4. Eric Ladd, J.O’Donnell, Using HTML 4, XML and JAVA, Prentice Hall of India, 1999. 5. Brown, Perl- The complete reference, Tata McGraw-Hill, New Delhi, 2004.


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SBI5605 MACHINE LEARNING FOR BIOINFORMATICS L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE Students are allowed to understand the modeling methods, such as supervised classification and clustering along

with the application of probabilistic graphical models for knowledge discovery, as well as deterministic and stochastic heuristics for optimization.

UNIT 1 MACHINE LEARNING 12 Hrs. Machine-Learning Foundations: The Probabilistic Framework -Introduction: Bayesian modeling -The Cox Jaynes axioms - Bayesian inference & induction -Model structures: graphical models & other tricks - Probabilistic Modeling & Inference: Examples -The simplest sequence models - Statistical mechanics Machine Learning Algorithms - Introduction -Dynamic programming -Gradient descent -EM/GEM algorithms –Markov chain Monte-Carlo methods - Simulated annealing – Evolutionary & genetic algorithms. Learning algorithms: miscellaneous aspects.

UNIT 2 SUPPORT VECTOR MACHINE (SVM) 12 Hrs. SVM: introduction – architecture – kernel - ROC – feature selection – sensitivity – specificity – accuracy – implementation - svm applications in sequence analysis, structure prediction , drug design –svm light - libsvm – weka.

UNIT 3 NEURAL NETWORKS 12 Hrs. Neural Networks: The Theory -Introduction - Universal approximation properties – Priors & likelihoods - Learning algorithms: backpropagation - Neural Networks: Applications - Sequence encoding & output interpretation- Sequence correlations & neural networks – Prediction of protein secondary structure - Prediction of signal peptides & their cleavage sites - Applications for DNA & RNA nucleotide sequences - Prediction performance evaluation - Different performance measures -Perceptrons and Multilayer Perceptrons -Neural Networks in Drug Design.

UNIT 4 HIDDEN MARKOV MODELS 12 Hrs. Hidden Markov Models: The Theory - Introduction -Prior information & initialization -Likelihood & basic algorithms - Learning algorithms -Applications of HMMs: general aspects -Protein applications - DNA & RNA applications - Advantages & limitations of HMMs – tools.

UNIT 5 PROBABILISTIC GRAPHICAL MODELS 12 Hrs. Probabilistic Graphical Models in Bioinformatics - Markov models & DNA symmetries - Markov models & gene finders - Hybrid models & neural network parameterization of graphical models -The single-model case - Bi-directional recurrent neural networks for protein secondary structure prediction

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Pierre Baldi and Soren Brunak, Bioinformatics: the Machine Learning Approach – Publisher: MIT Press, 1998. 2. David W Mount, Bioinformatics: sequence and genome analysis, 2nd edition, CBS publishers, 2004. 3. Zupan J., Gasteiger J.- Neural Networks in Chemistry and Drug Design. Wiley-VCH, 2000.


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SBI5606 HIGH PERFORMANCE COMPUTING L T P Credits Total Marks 3 1 0 4 100

COURSE OBJECTIVE Students are allowed to implement the strategies of High Performance Computing (HPC) for analyzing the task of

data management in biological research and to resolve difficult problems in Big Data analysis.

UNIT 1 INTRODUCTION 12 Hrs. High-Performance Computing –Definition,Architectures: Vector, Memory hierarchy ,Distributed memory, Shared memory. Introduction to parallel computing, Distributed memory programming. parallel computer models- Parallel processing- pipeline Overview of Recent Supercomputers –Introduction: grid computing- meta computing-cloud computing.

UNIT 2 CLUSTER & HPC 12 Hrs. Cluster computing at a glance – cluster classifications- cluster middleware – cluster applications – cluster setup and administration – multi path communication – distributed shared memory - representative cluster system: Biowulf – RWC PC cluster II- Parallel Processing on Linux Clusters. Java for HPC: java and different flavors of parallel programming models. HPC program optimization.

UNIT 3 PARALLEL PROGRAMMING 12 Hrs. Fundamental concepts – uses od parallel programming Designing for threads – scheduling - Threading and parallel programming constructs – Synchronization – Critical sections – Deadlock. Threading APIs. OPENMP PROGRAMMING: OpenMP- Non-blocking algorithms – Memory and cache related issues. Parallel programming models (Shared memory model, thread model, Distributed memory model, Data parallel model, Hybrid model, SPMD). Designing parallel programs. MPI PROGRAMMING: MPI Model – collective communication – data decomposition – communicators and topologies – point-to-point communication – MPI Library- parallel virtual machine. Parallel examples (Array processing PI calculation, Simple heat equation).

UNIT 4 GRID COMPUTING 12 Hrs. Introduction: What is a grid? -Infrastructure of hardware and software -Main Projects and Applications -The Open Grid Forum -International Grid Trust Federation. Grid Architecture - Overview of Resource Managers - Overview of Grid Systems - Application Management : Grid Application Description Languages -Application Partitioning -Meta-scheduling –Mapping –Monitoring - Web Services - Grid Portals - Clouds.

UNIT 5 APPLICATIONS & CASE STUDY 12 Hrs. Applications and Algorithms- Globus tool kit- object oriented implementation of parallel genetic algorithm- http://openmp.org.- mpi-blast, mpi-clustalw

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Rajkumar Buyya - High Performance Cluster Computing: Programming and Applications, Prentice Hall PTR, NJ, USA, 1999. 2. Michael J Quinn, Parallel programming in C with MPI and OpenMP, Tata McGraw-Hill, 2003. 3. Kevin Dowd - High Performance Computing, O'Reilly, 1993. 4. David E. Culler, Jaswinder Pal Singh, “Parallel computing architecture: A hardware/software approach”, Morgan

Kaufmann/Elsevier Publishers, 1999. 5. Ahmar Abbas, “Grid Computing: A Practical Guide to technology and Applications”, Charles River media, 2003.


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http://www.gridbus.org/~raj/cluster/LinuxClusters.ppt

http://www.phptr.com/browse/product.asp?product_id=%7BDA8FC375-6C6B-41AA-9A80-907556682E5A%7D

http://www.phptr.com/



SBI5607 APPLIED BIOINFORMATICS L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE Students are allowed to implement the theoretical basis of selected methods in dynamic programming to solve

the annotated models in sequence analysis.

UNIT 1 MODEL ORGANISMS 12 Hrs. Model organisms – structural properties of model genomes – characteristic & features – genome and proteome (Streptomyce sp., mouse, rat) – synteny – linkage disequilibrium – ’All against all’ – and ’between’ - analysis.

UNIT 2 GENE MODULES 12 Hrs. Introduction to genomic scale data-Computational aspects – gene modules – gene regulatory networks - gene history – functional annotation -genome wide analysis of functional linkages – high resolution expression analysis- statistical problems in gene expression analysis. Tools for gene xepression analysis-ArrayStar, GenomeSpace, MaizeGDB, Genevestigator.

UNIT 3 HAPMAP 12 Hrs. HapMap – Quantitative trait loci – homogeneity and heterogeneity – Haplotype – multilocus genotype – data analysis – Human population analysis – statistical method – Hardy-Weinberg proportion – Ewen watterson test,inference of phase and missing data, SNP tagging, Single SNP and multipoint test.

UNIT 4 CLUSTERS 12 Hrs. Clusters – Various clustering approaches.Hierarchal Clustering –Exclusive clustering, Overlapping clustering, Probabilistic clusteringand K-Means Analysis. Class -Heuristic programming comparative analysis – HUPO data bases – lead molecule and ligand characterization – Markov chains - Monte Carlo approaches of analysis. Application of clustering.

UNIT 5 PREDICTIVE SPECIATION 12 Hrs. Predictive speciation – Cladistics – evolutionary models – mammalian evolution – populational variations –personalized medicine and pharmacogenomics –Future prospects of personalized medicine. Pharmacogenomics –future medicine mendelian diseases – complex diseases – genetic drug resistance in Candida albicum.

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. David W. Mount, Bioinformatics: Sequences and Genome Analyses, Cold Spring Harbor Laboratory Press, 2000. 2. Michael Waterman, Introduction to Computational Biology: Maps, Sequences & Genomes, Chapman & Hall, 1995. 3. Alizadeh et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature. 403(6769):503-

11. 2000. 4. Tusher, V. G., Tibshirani, R., and Chu, G. Significance analysis of microarrays applied to the ionizing radiation response.

Proc Natl Acad Sci U S A 98, 5116-5121, 2001. 5. Shen-Orr SS, Milo R, Mangan S and Alon U, Network motifs in the transcriptional regulation network of Escherichia coli.

Nature Genetics 31:64–68. 2002. (This module focuses on static measures; transition to dynamics in next module).


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SBI5608 CLINICAL DATA MANAGEMENT L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE Students are allowed to apply their management skills in understanding the function of clinical data in the process

of product development in medicine.

UNIT 1 CLINICAL TRIAL 12 Hrs. Clinical Trial – definition – ethical considerations - phases - regulatory requirements for clinical trials - role of regulatory authorities - gene therapy clinical trial - case report form design - function of the CRF - the life history of the crf, data capture - automated data acquisition from optical images.Classes of clinical trials.-Drug trials, The randomized trials.

UNIT 2 DATA VALIDATION 12 Hrs. Data validation - steps, data presentation, coding of data - MedDRA and other medical terminologies – data definition, forms, and database design - defining data items to be collected - design of case report forms – database design, computer systems for data management and data entry - software for data management and data entry -data management software - software selection - screen layout - distributed computing.

UNIT 3 LOCAL DATA MANAGEMENT SYSTEMS 12 Hrs. Local Data Management Systems - selection of patients- eligibility check and patient entry- regulatory compliance patient registration - maintaining files for the trial- protocol compliance - patient’s role - forms scheduling- calendar system - card system - submission of materials - monitoring trial inventories - documentation of procedures.

UNIT 4 CENTRAL QUALITY CONTROL OF DATA 12 Hrs. Central Quality Control of Data - eligibility checking - checking for correct identifiers - queries to the institutions requests for overdue data - quality control at reference centers, data management and good clinical practice – guidelines of good clinical practice - good clinical practice responsibilities of the sponsor/coordinating center - implementation of good clinical practice at participating sites. Standard operating procedures (SOPs). Case report Form design, Computer system validation. (CSV). Patient record data, Society for clinical data management. Medical coding.

UNIT 5 SOFTWARE TOOLS FOR TRIALS MANAGEMENT 12 Hrs. Software tools for trials management - Clinical trials mamnagement system (CTMS), Oracle’s Siebel clinical trials data management system. Open source clinical trials software (OpenClinica), Clintrial,MACRO, RAVE,Patchmaster, Patientprofile, Popsipen.DSG, EDC clinical trial software. Managing clinical trial data using SAS.database update - calculated variables - logical/edit checks – electronic queries - overdue data requests - standard reports- interface with statistical software- online data lookup , follow – up and close - out phase - trials with a long follow - up phase- collecting follow - up data- preparing for analysis

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Richard K. Rondel, Sheila A. Varley, Colin F. Webb, Clinical Data Managemen”, 2nd Edition, John Wiley & Sons Ltd., 2000. 2. Eleanor Mcfadden, Management of Data in Clinical Trials, 2nd Edition, John Wiley & Sons, 2007. 3. Rick Ng, Drugs from Discovery to Approval, Wiley-Liss Ltd., 2004.


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SBI5609 NEUROINFORMATICS L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE Students are provided with the skills of data management, network analysis and simulation to connections in

neural systems.

UNIT 1 NEUROSCIENTIFIC INFORMATION 12 Hrs. Integration of neuroscientific information the genome level to the level of human behavior - Major goal - produce digital capabilities for a web-based information management system in the form of databases and associated data management tools.

UNIT 2 DATABASES AND SOFTWARE TOOLS 12 Hrs. Databases and software tools - for the benefit of neuroscientists, behavioral scientists, clinicians - databases for Neuroinformatics - Surface Management System (SuMS), The fMRIDC, BrainMap, BrainInfo, X-Anat, The Brain Architecture Management System (BAMS), The Ligand Gated Ion Channel database (LGICdb), ModelDB - Neuroinformatic software tools - GENESIS, NEURON, Catacomb, Channelab, HHsim, NEOSIM, NANS, SNNAP, etc - data sharing in neuroscience

UNIT 3 COMPUTATIONAL MODELING 12 Hrs. The computational modeling of ion channels - various parts of neurons - full neurons and - neural networks - modeling - overlaps with system biology - benefit from bioinformatics databases - Indian Neuroinformatics research - National Brain Research Centre.

UNIT 4 BRAIN FUNCTIONS 12 Hrs. Computational modeling - understanding of brain functions in normal and various disorder states - Concepts of membrane transport - Membrane-pore diffusion - Active transport - Action potential - Signal transmission - Signal reception – Photoreceptors.

UNIT 5 NEURODEGENERATIVE DISORDERS 12 Hrs. Neurodegenerative disorders – Alzheimer’s disease – targets - Neuropsychiatric disorders – Alzheimer’s disease - Parkinson’s disease - Huntington’s disease - Amyotrophic lateral sclerosis (ALS) - Genetic basis of disease – three major classes of genetic disease-OMIM – Programmed cell death - Apoptosis (type I) - Autophagic (type II) - Cytoplasmic (type III) - PCD and neurodegeneration - amyloid disease – prion disease

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Michael A. Arbib (Editor), Jeffrey S. Grethe (Editor), Computing the Brain: A Guide to Neuroinformatics, San Diego, CA,

USA, 2001. 2. Steven H. Koslow, Databasing the Brain: From Data to Knowledge (Neuroinformatics), John Wiley & Sons, 2005. 3. Rolf Kotter, Neuroscience Databases: A Practical Guide, Springer Verlag, New York, 2002. 4. Stephen H.Koslow (Editor), Neuroinformatics: An Overview of the Human Brain Project, Lawrence Erlbaum Associates,

Inc. 1997. END SEMESTER EXAMINATION QUESTION PAPER PATTERN

Max. Marks : 80 Exam Duration : 3 Hrs. PART A : 6 Questions of 5 Marks each – No Choice 30 Marks PART B : 2 Questions from each unit of internal choice, carrying 10 Marks each 50 Marks

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SBI5610 COMPUTATIONAL CHEMISTRY L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE Students are allowed to apply various mathematical models to solve the chemical and physical problems with the

help of scientific programming.

UNIT 1 FOUNDATIONS OF MOLECULAR ORBITAL THEORY 12 Hrs. Quantum Mechanics and the Wave Function - The Hamiltonian Operator - General Features- The Variational Principle - The Born–Oppenheimer Approximation - Construction of Trial Wave Functions - The LCAO Basis Set Approach - The Secular Equation.

UNIT 2 HUCKEL THEORY 12 Hrs. Fundamental Principles - Application to the Allyl System Many-electron Wave Functions - Hartree-product Wave Functions -The Hartree Hamiltonian - Electron Spin and Antisymmetry - Slater Determinants - The Hartree-Fock Self-consistent Field Method.

UNIT 3 SEMIEMPIRICAL METHODS 12 Hrs. . Introduction - The basic principles of SCF SE methods - the Neglect of DifferentialOverlapMethod -Complete Neglect of Differential Overlap Method- Modified Neglect of the Diatomic Overlap Method- AustinModel 1 Method Parametric Method 3 Model - The Pairwize Distance Directed Gaussian Method - The Zero Differential Overlap Approximation Method- Software Used for Semiempirical Calculations.

UNIT 4 BASIS SETS 12 Hrs. Introduction -The Energy Calculation from the STO Function - The Energy Calculation of Multielectron - Gaussian -Differences Between STOs and GTOs -Classification of Basis Sets-Minimal Basis -A Comparison of Energy Calculations of the Hydrogen Atom Based on STO-nGBasis Sets -STO-2G - STO-3G - STO-6G – Contracted Gaussian Type Orbitals - Double- and Triple-Zeta Basis Sets and the Split-Valence Basis Sets -Polarized Basis Sets -Basis Set Truncation Errors - Basis Set Superposition Error - Methods to Overcome -The Chemical Hamiltonian Approach -The Counterpoise Method -The Intermolecular Interaction Energy of Ion Water Clusters - A List of Commonly Available Basis Sets -Internet Resources for Generating Basis Sets.

UNIT 5 DENSITY FUNCTIONAL THEORY 12 Hrs. Introduction - The basic principles of density functional theory – electron Density -Pair Density -The Development of DFT- The Functional - The Hohenberg and Kohn Theorem -The Kohn and Sham Method - Density Functionals -The Dirac-Slater Exchange Energy Functional and the Potential -DFT Methods - Applications of -The Performance of DFT - Advantages of DFT in Biological Chemistry.

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Ramachandran K. I., Deepa G., Namboori K.- Computational Chemistry and Molecular Modeling Principles and Applications

-, Springer-Verlag Berlin Heidelberg, 2008. 2. Jensen F., Introduction to Computational Chemistry, Wiley, New York, 1999. 3. Errol Lewars - Computational chemistry, Kluwer Academic Publishers, 2003


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SBI5611 IMMUNOINFORMATICS & COMPUTATIONAL VACCINOLOGY


3 1 0 4 100

COURSE OBJECTIVE Students are allowed to understand the immunological foundations of a biological system with the help of

computational techniques.

UNIT 1 INTRODUCTION TO IMMUNOINFORMATICS 12 Hrs. Definition of Immunoinformatics – overview of the Immune system- Brief introduction to immunoformatics and computational vaccinology-Immunogenecity a brief primer-Epitopes and Epitology – Immunoinformatics databases-IMGT – IMGT-GENE-DB– IMGT-HLA ,IMGT/LIGM-DB - HaptenDB – EPITOME – dbMHC – JenPep. Monoclonal antibodies database.

UNIT 2 GENOTYPING METHODS AND DISEASE ASSOCIATION 12 Hrs. Genotyping of SNPs, classical HLA typing, MHV haplotypes, Molecular haplotyping, microhaplotyping. HLA and disease associations, Identifying Major Histocompatibility Complex Supertypes.

UNIT 3 ALLERGEN BIOINFORMATICS 12 Hrs. Introduction- allergen database-need for allergen database-existing allergen database: IUIS, UniProt, SDAP, ALLERGOME, Allergenicity prediction-sequence similarity search, FAO and WHO guidelines, current status of allergenicity prediction.

UNIT 4 COMPUTATIONAL VACCINOLOGY 12 Hrs. Vaccines –types- Conventional methods used for Preparation of vaccines -From immunome to vaccine- epitope mapping,-vaccine design tools-Prediction of cytotoxic T cells (MHC CLASS I) epitopes-Antigen processing in the MHC –I pathway, Prediction of T helper cells(MHC-II) epitopes-processing of MHC-II epitopes.B cell Epitopes. B cell epitope prediction tools , Tools in immunoinformatics for the prediction binding affinity between peptide: TAP: MHC: TCR- MHC:Peptide Binding Prediction - SYFPEITHI, BIMAS, MHCPred, TEPITOPE, NetMHC, BLEEP Proteasomal Cleavage Prediction : PAProC, NetChop - TAP Binding:TAPPred T-cell Binding: EpiJen.

UNIT 5 IMMUNOGENETICS TO IMMUNOMICS 12 Hrs. Biomolecular structure prediction using Immune inspired algorithsm- overview of discrete models-discrete models for HIV infection-simulation of HIV-1 infections-simulation of HIV -1 Molecular evolution in response to chemokine receptors and antibodies- Integration of immune models using Petri Nets.

Max. 60 Hours TEXT / REFERENCE BOOKS 1. Darren R. Flower, Immunoinformatics: Predicting Immunogenicity In Silico (Methods in Molecular Biology), 2010. 2. Flower, Darren D.R., Timmis, In Silico Immunology, Jon (Eds.) XVIII, 450 pages.In Silico Immunology, 2007 3. Immunoinformatics: Bioinformatic Strategies for Better Understanding of Immune Function, No. 254 -Novartis

Foundation,2011.


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SBI5612 CHEMINFORMATICS L T P Credits Total Marks

3 1 0 4 100

COURSE OBJECTIVE Students are allowed to apply the methods for studying complex interactions in chemical and biological systems

for discovering the emerging properties.

UNIT 1 INTRODUCTION TO CHEMINFORMATICS 12 Hrs. Introduction to Cheminformatics - History and evolution of Cheminformatics - Chemical representation - Sequence, 2D, 3D structure, Types of chemical representation - linear notation, tabular storage, graphical representation – Chemical data management - Chemical mark up languages.

UNIT 2 CHEMICAL DATABASES 12 Hrs. Chemical Databases - CHEMDB, KEGG LIGAND, CSD, CAS REGISTRY, BIOMETA DB, National Cancer Institute Database(NCI) - Chemical searching methods - exact searching, sub structure searching, similarity searching, reaction searching.

UNIT 3 COMBINATORIAL CHEMISTRY 12 Hrs. Combinatorial chemistry: Introduction, Liquid Phase synthesis, Solid phase synthesis, Designing Combinatorial Synthesis, High through put screening.

UNIT 4 COMBINATORIAL LIBRARY DESIGN 12 Hrs. Combinatorial library design - Rational principles of compound selection for combinatorial library design and optimization approach, Descriptor Analysis, Modeling toxicity, Computer Assisted Synthesis design and structure based library design.

UNIT 5 APPLICATION OF CHEMINFORMATICS 12 Hrs. Application of cheminformatics - QSPR Drug design - Target identification and Validation, lead finding and optimization - Pharmacophore-Based Drug Design - Structure-Based Drug design - Application of Cheminformatics in Drug Design.

Max. 60 Hours

TEXT / REFERENCE BOOKS 1. Andrew R. Leach & Valerie J.Gillet, An Introduction to Cheminformatics, Revised Edition, Springer Publication, 2007. 2. Johann Gasteiger, Dr. Thomas Engel, Cheminformatics, Wiley-VCH Press, 2003. 3. Jurgen Bajorath, Cheminformatics: Concepts, Methods and Tools for Drug Discovery, Humana Press, 2004. 4. Tudor. L.Oprea, Cheminformatics in Drug Discovery, Wiley-VCH Press, 2005.

WEBSITES 1. http://cdb.ics.uci.edu/ 2. http://www.cas.org/. 3. http://www.combichemistry.com/ 4. http://www.wiziq.com/tutorial/2967-Combinatorial-Chemistry-and-Library-Design. 5. http://www.vuw.ac.nz/staff/paul_teesdale-spittle/peptide-synthesis/pep-syn-files/solid-phase.htm


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