IF7002 BIO INFORMATICS SYLLABUS FOR ME 3RD SEM CSE - Anna University Internal marks 2018

IF7002 BIO INFORMATICS SYLLABUS FOR ME 3RD SEM CSE

ANNA UNIVERSITY, CHENNAI
REGULATIONS - 2013
IF7002 BIO INFORMATICS SYLLABUS
ME 3RD SEM COMPUTER SCIENCE AND ENGINEERING SYLLABUS
IF7002 BIO INFORMATICS SYLLABUS
IF7002 BIO INFORMATICS SYLLABUS
OBJECTIVES:
 To get exposed to the domain of bioinformatics
 To understand the role of data warehousing and data mining for bioinformatics
 To learn to model bioinformatics based applications
 To understand how to deploy the pattern matching and visualization techniques in bioinformatics
 To study the Microarray technologies for genome expression

UNIT I INTRODUCTION
Need for Bioinformatics technologies – Overview of Bioinformatics technologies – Structural bioinformatics – Data format and processing – secondary resources- Applications – Role of Structural bioinformatics - Biological Data Integration System.

UNIT II DATAWAREHOUSING AND DATAMINING IN BIOINFORMATICS
Bioinformatics data – Data ware housing architecture – data quality – Biomedical data analysis – DNA data analysis – Protein data analysis – Machine learning – Neural network architecture- Applications in bioinformatics

UNIT III MODELING FOR BIOINFORMATICS
Hidden markov modeling for biological data analysis – Sequence identification – Sequence classification – multiple alignment generation – Comparative modeling – Protein modeling –genomic modeling – Probabilistic modeling – Bayesian networks – Boolean networks - Molecular modeling – Computer programs for molecular modeling

UNIT IV PATTERN MATCHING AND VISUALIZATION
Gene regulation – motif recognition and motif detection – strategies for motif detection – Visualization – Fractal analysis – DNA walk models – one dimension – two dimension – higher dimension – Game representation of Biological sequences – DNA, Protein, Amino acid sequences

UNIT V MICROARRAY ANALYSIS
Microarray technology for genome expression study – image analysis for data extraction – preprocessing – segmentation – gridding , spot extraction , normalization, filtering – cluster analysis – gene network analysis – Compared Evaluation of Scientific Data Management Systems – Cost Matrix – Evaluation model ,Benchmark , Tradeoffs

TOTAL: 45 PERIODS

OUTCOMES:
Upon Completion of the course, the students will be able to
 Deploy the data warehousing and data mining techniques in Bioinformatics
 Model bioinformatics based applications
 Deploy the pattern matching and visualization techniques in bioinformatics
 Work on the protein sequences
 Use the Microarray technologies for genome expression

REFERENCES:
1. Yi-Ping Phoebe Chen (Ed), “Bio Informatics Technologies”, First Indian Reprint, Springer Verlag, 2007.
2. N.J. Chikhale and Virendra Gomase, "Bioinformatics- Theory and Practice", Himalaya Publication House, India, 2007
3. Zoe lacroix and Terence Critchlow, “Bio Informatics – Managing Scientific data”, First Indian Reprint, Elsevier, 2004
4. Bryan Bergeron, “Bio Informatics Computing”, Second Edition, Pearson Education, 2003.
5. Arthur M Lesk, “Introduction to Bioinformatics”, Second Edition, Oxford University Press, 2005
6. Burton. E. Tropp, “Molecular Biology: Genes to Proteins “, 4th edition, Jones and Bartlett Publishers, 2011
7. Dan Gusfield, “Algorithms on Strings Trees and Sequences”, Cambridge University Press, 1997.
8. P. Baldi, S Brunak , Bioinformatics, “A Machine Learning Approach “, MIT Press, 1998.

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