Anna University Tiruchirappalli - 620 024
Regulations 2007 Syllabus
M.E. COMPUTER SCIENCE AND ENGINEERING
ELECTIVES CS5007 – BIO INFORMATICS
UNIT I FUNDAMENTALS 7
The Central Dogma – Killer Application – Parallel Universes – Watson’s Definition – Top Down Vs Bottom Up Approach – Information Flow – Conversance – Communications.
UNIT II DATABASE AND NETWORKS 9
Definition – Data Management – Data Life Cycle – Database Technology – Interfaces – Implementation – Networks Communication Models – Transmission Technology – Protocols – Bandwidth – Topology – Contents – Security – Ownership – Implementation.
UNIT III SEARCH ENGINES AND DATA VISUALIZATION 10
Search Process – Technologies – Searching and Information Theory – Computational Methods –
Knowledge Management – Sequence Visualizations – Structure Visualizations – User Interfaces – Animation Vs Simulation.
UNIT IV STATISTICS– DATA MINING AND PATTERN MATCHING 11
Statistical Concepts – Micro Arrays – Imperfect Data – Basics – Quantifying – Randomness – Data Analysis – Tools Selection – Alignment – Clustering – Classification – Data Mining Methods – Technology – Infrastructure Pattern Recognition – Discovery – Machine Learning – Text Mining – Pattern Matching Fundamentals – Dot Matrix Analysis – Substitution Matrix – Dynamic Programming – Word Method – Bayesian Method – Multiple Sequence Alignment Tools.
UNIT V MODELING SIMULATION AND COLLABORATION 8
Drug Discovery Fundamentals – Protein Structure – System Biology Tools – Collaboration and
Communication – Standards – Issues – Case Study.
Total: 45
TEXT BOOK
1. Bryan Bergeron, “Bio Informatics Computing”, Prentice Hall, 2003.
REFERENCES
1. T.K. Affward, D.J. Parry Smith, “Introduction to Bio Informatics”, Pearson Education, 2001.
2. Pierre Baldi, Soren Brunak, “Bio Informatics The Machine Learning Approach”, 2nd
Edition, First East West Press, 2003
Regulations 2007 Syllabus
M.E. COMPUTER SCIENCE AND ENGINEERING
ELECTIVES CS5007 – BIO INFORMATICS
UNIT I FUNDAMENTALS 7
The Central Dogma – Killer Application – Parallel Universes – Watson’s Definition – Top Down Vs Bottom Up Approach – Information Flow – Conversance – Communications.
UNIT II DATABASE AND NETWORKS 9
Definition – Data Management – Data Life Cycle – Database Technology – Interfaces – Implementation – Networks Communication Models – Transmission Technology – Protocols – Bandwidth – Topology – Contents – Security – Ownership – Implementation.
UNIT III SEARCH ENGINES AND DATA VISUALIZATION 10
Search Process – Technologies – Searching and Information Theory – Computational Methods –
Knowledge Management – Sequence Visualizations – Structure Visualizations – User Interfaces – Animation Vs Simulation.
UNIT IV STATISTICS– DATA MINING AND PATTERN MATCHING 11
Statistical Concepts – Micro Arrays – Imperfect Data – Basics – Quantifying – Randomness – Data Analysis – Tools Selection – Alignment – Clustering – Classification – Data Mining Methods – Technology – Infrastructure Pattern Recognition – Discovery – Machine Learning – Text Mining – Pattern Matching Fundamentals – Dot Matrix Analysis – Substitution Matrix – Dynamic Programming – Word Method – Bayesian Method – Multiple Sequence Alignment Tools.
UNIT V MODELING SIMULATION AND COLLABORATION 8
Drug Discovery Fundamentals – Protein Structure – System Biology Tools – Collaboration and
Communication – Standards – Issues – Case Study.
Total: 45
TEXT BOOK
1. Bryan Bergeron, “Bio Informatics Computing”, Prentice Hall, 2003.
REFERENCES
1. T.K. Affward, D.J. Parry Smith, “Introduction to Bio Informatics”, Pearson Education, 2001.
2. Pierre Baldi, Soren Brunak, “Bio Informatics The Machine Learning Approach”, 2nd
Edition, First East West Press, 2003
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