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CSE-953 Advanced Computational Biology
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Campus
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RCMS
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Programs
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PG
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Session
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Spring Semester 2017
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Course Title
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Advanced Computational Biology
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Course Code
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CSE-953
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Credit Hours
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3-0
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Pre-Requisutes
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Course Objectives
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This course is beneficial for computational and experimental biologists to understand the principles of analyzing biological data, building models and testing hypotheses using computer science paradigms. This course is a survey of algorithms and mathematical methods in biological sequence analysis, protein structures and system biology. Sequence analysis topics include introduction to probability, hidden Markov models, gene prediction, sequence alignment, and identification of trancommention-factor binding sites. Systems biology topics include gene regulatory networks, quantitative and qualitative modeling of gene regulatory networks.
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Detail Content
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Details of course contents are as follows: Introduction to DNA & Proteins, Intro. to Databases and biological Databases, String Matching Algo. for Sequence Alignment, Multiple Sequence Alignment, Phylogenies Trees, Protein Structure Prediction & Analysis, Protein-Protein Interactions, Molecular Docking, Molecular Dynamics, Gene Regulatory Networks, Modeling of Gene Regulatory Networks(GRN), Modeling GRN with Kinetic Logic, Modeling GRN with Ordinary Differential Equations, Modeling GRN with Piece-wise Linear Differential Equations, Signaling Transduction Pathways, Pathway Logic.
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Text/Ref Books
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Baxevanis, A.D. and Ouellette (eds.) Bioinformatics. A Practical Guide to the Analysis of Genes and Proteins. (2004) Third Edition Rene Thomas and Richard D’Ari. Biological Feedback.
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Time Schedule
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Spring Semester 2017
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Faculty/Resource Person
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Dr. Rehan Zafar Paracha
PhD (National University of Science and Technology (NUST))
Discipline: Virology & Immunology
Specialization: Drug Discovery and Development
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