Machine Learning in Genomics - Fall 2019
Offered By: Massachusetts Institute of Technology via YouTube
Course Description
Overview
Syllabus
MIT CompBio Lecture 01 - Introduction (Fall'19).
MIT CompBio Lecture 02 - Dynamic Programming (Fall'19).
MIT CompBio Lecture 03 - Hashing BLAST Database Search (Fall'19).
MIT CompBio Lecture 04 - HMMs Hidden Markov Models I (Fall'19).
MIT CompBio Lecture 05 - HMMs Hidden Markov Models II (Fall'19).
MIT CompBio Lecture 06 - Expression Analysis Clustering Classification (Fall '19).
MIT CompBio Lecture 07 - RNA world, RNA-seq, RNA folding (Fall '19).
MIT CompBio Lecture 08 - Epigenomics I (Fall '19).
MIT CompBio Lecture 09 - Epigenomics II (Fall '19).
MIT CompBio Lecture 10 - Regulatory Genomics (Fall '19).
MIT CompBio Lecture 11 - Network inference and analysis (Fall '19).
MIT Compbio Lecture 12 - Deep Learning (Fall '19).
MIT Compbio Lecture 13 - Population Genetics (Fall 2019).
MIT CompBio Lecture 14 - GWAS (Fall 2019).
MIT CompBio Lecture 15 - eQTLs Mediation (Fall 2019).
MIT CompBio Lecture 16 - Systems Genetics (Fall 2019).
MIT CompBio Lecture 17 - Comparative Genomics (Fall 2019).
MIT CompBio Lecture 18 - Genome Evolution (Fall 2019).
MIT CompBio Lecture 19 - Phylogenetics (Fall 2019).
MIT CompBio Lecture 20 - Phylogenomics (Fall 2019).
MIT CompBio Lecture 21 - Single-cell genomics (Fall 2019).
MIT CompBio Lecture 22 - Cancer Genomics (Fall 2019).
MIT CompBio Lecture 23 - Multi-Phenotype analyses.
MIT CompBio Lecture 24 - Genome Engineering (Fall 2019).
MIT CompBio Lecture 25 - How to Present - Papers, Figures, Presentations.
MIT Compbio Lecture 11 1/2 - 6047 Buzzword Recitation (Fall '19).
Taught by
Manolis Kellis
Tags
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