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B.Tech. Degree Programme Computer Science & Engineering

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B.<strong>Tech</strong>. <strong>Computer</strong> <strong>Science</strong> & <strong>Engineering</strong> (Regular)6. UML: Why we model, types of models, principlesof modelling, object oriented modelling, objectoriented concepts, UML notation, object orientedanalysis: use case diagrams, interaction diagrams,activity diagrams, object oriented design: classdiagrams, object diagrams, state diagrams,collaboration diagrams, post-testing: deploymentdiagrams, patterns, frameworks7. USING UML FOR OOD: UML object constraintlanguage, designing classes: the process, classvisibility, refining attributes, designing methods adprotocols, packages and managing classes,designing interface objects, view layer interfacedesign, macro and micro level interface designprocessTEXT BOOKJacobson Ivar, “Object Oriented Software <strong>Engineering</strong>”,Addison Wesley, 1997.REFERENCE BOOKS1. Bennett, “Object Oriented System Analysis andDesign using UML”, Tata McGraw Hill, 20092. Deacon,” Object Oriented Analysis and Design”,Pearson Education, 20093. Ali Bahrami, “Object Oriented SystemsDevelopment”, McGraw Hill, 19994. Rumbaugh et al, ”Object Oriented Modeling andDesign”, Prentice Hall of India, 20075. Booch Grady, “Object Oriented Analysis andDesign with applications”, 3rd edition, AddisonWesley, 20076. Mehta Subhash and Basandra Suresh K., “ObjectOriented Software <strong>Engineering</strong>”, GalgotiaPublications,1995WEB REFERENCES1. www.objectmentor.com/resources/articles/umlClassDiagrams.pdf2. uml-tutorials.trireme.com3. www.smartdraw.com/tutorials/software/oose/tutorial_01.htm4. www.iconixsw.com5. www.rspa.com/spi/analysismodeling.htmlIT-431BIOINFORMATICSL T P Cr5 0 0 3OBJECTIVEBioinformatics is a rapidly growing field that integratesmolecular biology, biophysics, statistics, and computerscience. Fundamentally it is a field focused oncomparison: how similar are two given proteins? Whatare the differences between various DNA sequences?How is the data from one microarray assay differentfrom another? Furthermore, bioinformatics is concernedwith quantifying the significance of these differences. Inany of the examples above, once a metric for similarityis obtained, it must also be statistically characterized todetermine the likelihood that such a relationship couldoccur by chance. In this course, you will learn many ofthe popular tools for performing bioinformatics analysisand you will be introduced to the thinking that drives thealgorithms.PRE-REQUISITESKnowledge of fundamentals of biology, genetics, datastructures and statistics1. INTRODUCTION TO MOLECULAR BIOLOGY:Gene structure and information content; molecularbiology tools, genomic information content2. COMPUTATIONAL BIOLOGY: Data searches andpairwise alignments; gaps; scoring matrices;Needleman and Wunsch algorithm; global andlocal alignments; database searches.3. PHYLOGENETICS: Molecular phylogenetics;phylogenetic trees; distance matrix methods;character-based methods of phylogenetics;parsimony.4. GENOMICS: Patterns of substitution within genes;estimating substitution numbers; molecular clocks;ancestral sequences; searches; consensus trees;tree confidence; genomics; prokaryotic genestructure; gene density; eukariotic genomes; geneexpression.5. PROTEOMICS: Protein and RNA structureprediction, polypeptic composition, secondary andtertiary structure; algorithms for modeling proteinfolding; structure prediction; proteomics; proteinclassification; experimental techniques; ligandscreening; post-translational modificationprediction.6. GENE EXPRESSION DATA: Microarrays andgene expression data; microarray design; analysisof data; application; microarray standards;clustering (SOM, PCA/SVD, k-means,hierarchical); classification (LVQ, SVM);processing gene expression data using decisiontree based methods (ID3, ASSISTANT, C5.0)7. NEW AREAS OF BIOINFORMATICS:Metabolmics: metabolic pathways; drug targetidentification; biological systems: systems ofmolecular network; eco-systems, elements ofsystems modeling; nutrigenomics;palenteoinformatics; toxicogenomics, systemsbiology; pharmacogenomics, synthetic biology, bioterrorism,biological and chemical warefare, datasecurity issues in bioinformatics, bio-ethics,cloning, transgenic organisms, bio-ethics inagriculture, ontology, standardsTEXT BOOKMount David, “Bioinformatics: Sequence and GenomeAnalysis”, 2008REFERENCE BOOKS1. Attwood T. K. and Parry-Smith D. J., “Introductionto Bioinformatics”, Pearson Education, 20032. Krane D. E. and Raymer M. L., “FundamentalConcepts of Bioinformatics”, Pearson Education,2003.3. Gibas Cynthia, Jambeck Per, “DevelopingBioinformatics Computing Skills”, O’Reilly, 20014. Zar J. H., “Biostatistical Analysis”, 4th edition,Pearson Education, 1999.5. Baldi Pierre and Brunak Søren, “Bioinformatics:The Machine Learning Approach”, 2nd edition, MITPress, 20016. Westhead D. R. et al, “Instant Notes Series:Bioinformatics”, Viva Books Pvt. Ltd., 200362

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