BM6005 BIO INFORMATICS | syllabus (ELECTIVE-II)

BM6005    BIO INFORMATICS L T P C  3 0 0 3

                                                         

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    (9)

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    (9)

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    (9)

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    (9)

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    (9)

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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