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Language of Instruction
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English
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Level of Course Unit
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Master's Degree
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Department / Program
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ELECTRICAL AND COMPUTER ENGINEERING
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Type of Program
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Formal Education
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Type of Course Unit
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Elective
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Course Delivery Method
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Face To Face
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Objectives of the Course
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O1. Learn different types and sources of big data (-omics data) available in biology,
O2. Learn the computational methodologies for the analysis of various biological high throughput datasets, massively parallel sequencing datasets,
O3. Learn a core set of widely used algorithms in computational genomics,
O4. Learn a set of algorithms that have important applications in computational genomics, but which have key applications outside of biology as well.
O5. Apply the concepts learned to a real problem and convert the data into biological, genomic or medical knowledge.
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Course Content
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W1 Introduction to Computational Genomics, description of the basic concepts such as the organization of DNA, proteins, cells; in silico biology.
W2 Description of -omics data, big data in molecular biology and genetics
W3 Description of the Human Genome Project, How to sequence the Human Genome
W4 Description of the Computational Challenges in Genome Sequencing, Next Generation Sequencing (NGS) Data Analysis
W5 Description of the Suffix Trees, Suffix Arrays for Read Mapping in NGS
W6 Description of the Gene discovery algorithms using Hidden Markov Models (HMMs), metagenomics
W7 Description of the Functional Enrichment Methods for -omics Data Analysis, Hypergeometric Test, Pathway Based Genomics
W8 Description of Network Based Genomics, Sub-network identification in protein-protein interaction (PPI) networks using simulated annealing (SA) and genetic algorithms (GA)
W9 Analysis of Genome-wide Association Study (GWAS) Datasets
W10 Description of Epigenomics, Cancer Genomics, Metagenomics studies LO1, LO2
W11 Description of regression, applications of regression in genomics problems
W12 Discovering Gene Regulatory Signals: Expectation Maximization, Gibbs sampling and related approaches
W13 Description and review of the trans-omic data analysis, Personalized Medicine, Pharmacogenomics
W14 Description of Artificial Intelligence Based Methods for Precision Medicine
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Course Methods and Techniques
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Prerequisites and co-requisities
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None
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Course Coordinator
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None
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Name of Lecturers
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None
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Assistants
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None
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Work Placement(s)
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No
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Recommended or Required Reading
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