MIT CompBio Lecture 02 - DynamicProgramming (Part1)
3
MIT CompBio Lecture 02 - DynamicProgramming (Part2)
4
MIT CompBio Lecture 03 - Database Search
5
MIT CompBio Lecture 04 - HMMs I
6
MIT CompBio Lecture 05 - HMMs II
7
MIT CompBio Lecture 06 - Gene Expression Analysis: Clustering and Classification
8
MIT CompBio Lecture 07 - RNA world, RNA-seq, RNA folding
9
MIT CompBio Lecture 08 - Epigenomics
10
MIT CompBio Lecture 09 - Three Dimensional Genome
11
MIT CompBio Lecture 10 - Regulatory Genomics
12
MIT CompBio Lecture 11 - Network Analysis
13
MIT CompBio Lecture 12 - Deep Learning
14
MIT CompBio Lecture 13 - Population Genomics
15
MIT CompBio Lecture 14 - GWAS (part 1)
16
MIT CompBio Lecture 14 - GWAS (part 2)
17
MIT CompBio Lecture 15 - eQTLs
18
MIT Compbio Lecture 16 - Heritability
19
MIT CompBio Lecture 17 - Comparative Genomics
20
MIT CompBio Lecture 18 - Genome Assembly, Evolution, Duplication
21
MIT CompBio Lecture 19 - Phylogenetics
22
MIT CompBio Lecture 20 - Phylogenomics
23
MIT CompBio Lecture 21 - Single-Cell Genomics
24
MIT CompBio Lecture 22 - Cancer Genomics
25
MIT CompBio Lecture 23 - Multi-Phenotype analyses
26
MIT CompBio Lecture 24 - Genome Engineering
Description:
Dive into a comprehensive lecture series on computational biology from MIT's Fall 2018 semester, covering a wide range of topics including genomes, networks, evolution, and health. Explore dynamic programming, database search, hidden Markov models, gene expression analysis, RNA biology, epigenomics, 3D genome structure, regulatory genomics, network analysis, deep learning, population genomics, genome-wide association studies, eQTLs, heritability, comparative genomics, genome assembly, phylogenetics, single-cell genomics, cancer genomics, multi-phenotype analyses, and genome engineering. Gain insights from expert instructors over the course of 24 lectures, totaling more than 31 hours of in-depth content. Note that a more recent version from Fall 2019 is also available for those seeking the most up-to-date information in this rapidly evolving field.
MIT Computational Biology - Genomes, Networks, Evolution, Health - Fall 2018