BM6005 Bio Informatics Syllabus Semester VIII Elective IT BTECH Anna University

NotesKhan





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.



OUTCOMES:
Upon Completion of the course, ?the students will be able to

• Develop models for biological data

TOTAL: 45 PERIODS

• 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