BM6005 BIO INFORMATICS SYLLABUS FOR 7TH SEM CSE AND 8TH SEM IT REGULATION 2013 - Anna University Internal marks 2018

BM6005 BIO INFORMATICS SYLLABUS FOR 7TH SEM CSE AND 8TH SEM IT REGULATION 2013

ANNA UNIVERSITY CSE/IT SYLLABUS
BM6005 BIO INFORMATICS SYLLABUS
7TH SEM CSE / 8TH SEM IT
(Elective paper)
REGULATION 2013
 
OBJECTIVES:
The student should be made to:
-> Exposed to the need for Bioinformatics technologies
-> Be familiar with the modeling techniques
-> Learn microarray analysis
-> Exposed to Pattern Matching and Visualization

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

UNIT II DATAWAREHOUSING AND DATAMINING IN BIOINFORMATICS
Bioinformatics data – Data warehousing architecture – data quality – Biomedical data analysis – DNA data analysis – Protein data analysis – Machine learning – Neural network architecture and 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 – 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
-> Develop models for biological data.
-> Apply pattern matching techniques to bioinformatics data – protein data genomic data.
-> Apply micro array technology for genomic expression study.
 
TEXT BOOK:
1. Yi-Ping Phoebe Chen (Ed), “BioInformatics Technologies”, First Indian Reprint, Springer Verlag, 2007.
 
REFERENCES:
1. Bryan Bergeron, “Bio Informatics Computing”, Second Edition, Pearson Education, 2003.
2. Arthur M Lesk, “Introduction to Bioinformatics”, Second Edition, Oxford University Press, 2005

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