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Computational Biology Virtual Internship
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Unit 1: Integrative Biology
Day 1: Introduction to computational biology and its applications in Life Sciences. (61:12)
Day 2: Understanding the basic principles and theories underlining computational biology. (60:29)
Unit 2: Decoding the Biomacromolecules
Day 3: Understanding the biophysics of Carbohydrates and Proteins. (64:03)
Day 4: Understanding biophysics Lipids and Nucleic acid. (67:58)
Day 5: Drug design, drug action, and stimulation. (17:03)
Day 6: Pharmacokinetics and Pharmacodynamics. (61:52)
Unit 3: Algorithms in Computing
Day 7: Biological and Computer algorithms, Fibonacci problem, Dynamic Programming, Time and space complexity of algorithms. (63:10)
Day 8: Laplace's Rule, Search Algorithms: Random walk, Hill climbing, simulated annealing. (67:20)
Day 9: Hidden Markov Model and their Applications in Proteomics and Genomics. (71:28)
Day 10: Support Vector Machines and Bayesian network. (73:27)
Day 11: Artificial Neural Network (ANN) and their application in biology. (59:33)
Unit 5: Big Data Analytics
Day 12: Cloud computing: features, advantages, applications. (71:41)
Day 13: Network Medicine and Personalization. (62:44)
Day 14: Pharmacogenomics and Microbiome analysis. (65:12)
Day 10: Support Vector Machines and Bayesian network.
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