RBT603 BI-II Syllabus
AKTU Biotechnology (BT) RBT603 BI-II Syllabus for all 5 units are provided Below. Download link for BT 6th SEM RBT603 Bioinformatics-II Syllabus is listed down for students to make perfect utilization and score maximum marks with our study materials.
UP Technical University Biotechnology(BT) 6th SEM RBT603BI-II – Bioinformatics-II Syllabus
RBT603: Bioinformatics-II
Unit I
Inference problems and techniques for molecular biology. Overview of key inference problems
in biology: Homology identification, Genomic sequence annotation (Genes and ORFs
identification), Protein structure prediction (Secondary and Tertiary structure prediction), Protein
function prediction, Biological network identification, Next generation sequencing, Microarray
data analysis.
Unit II
Basics of RNA Structure prediction and its limitations, Features of RNA Secondary Structure,
RNA structure prediction methods: Based on self-complementary regions in RNA sequence,
Minimum free energy methods, Suboptimal structure prediction by MFOLD, Prediction based on
finding most probable structure and Sequence co-variance method. Application of RNA structure
modeling.
Unit III
Machine learning: Decision tree induction, Artificial Neural Networks, Hidden Markov Models,
Genetic Algorithms, Simulated Annealing, Support vector machines; The relation between
statistics and machine learning; Evaluation of prediction methods: Parametric and Nonparametric
tests, cross-validation and empirical significance testing (empirical cycle), Clustering
(Hierarchical and K-mean).
Unit IV
Basic concept of Force field in molecular modeling (Potential energy calculation); Overview of
key computational simulation techniques: Introduction to simulation, Computer simulation
techniques, Types of computer simulation (Continuous, Discrete-event and Hybrid simulation),
Differential equation solvers, Parameter estimation, and Sensitivity analysis.
Unit V
Overview of key techniques for the management of large document collections and the
biological literature: Document clustering, Information retrieval system; Natural Language
Processing: Introduction, Major areas of NLP, Natural language information extraction; Insilico
Drug Designing: Major steps in Drug Designing, Ligand and Structure based drug designing,
Protein-ligand docking, QSAR Modeling, Pharmacodynamics (Efficacy & Potency) &
Pharmacokinetics (ADME), Lipinski’s rule of five, Pharmacogenomics.
Text Books & References
1. Computational Methods in Biotechnology – Salzberg S. L. et al., Elsevier Science.
2. D.W.Mount; Bioinformatics- Sequence and genome analysis; Cold Spring Harbour Lab
press.
3. Statistical Methods in Bioinformatics-Evens & Grants, Springer-Verlag, NY.
4. Computational Molecular Biology- Setubal and Meidanis, PWS publishing Co., 1997. 18/ 24
5. Protein Structure Prediction-A Practical Approach, MJE Sternberg, Oxford University Press.
6. Purifing Protein for Protemics, Richard J. Sinpson, I.K. International Pvt. Ltd.
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RBT603 Syllabus, BI-II Unit-wise Syllabus – BT 6th Semester
