Resources | Foundations of Computational and Systems Biology | Biology | MIT OpenCourseWare

Course Info

Instructors

Departments

As Taught In

Spring 2014

Level

Graduate

Topics

Engineering

Biological Engineering

Computational Biology

Systems Engineering

Computational Modeling and Simulation
Science

Biology

Computation and Systems Biology

Learning Resource Types

Lecture Videos

Lecture Notes

Projects

Programming Assignments with Examples

Presentation Assignments

Written Assignments

Instructor Insights

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This package contains the same content as the online version of the course, except for the audio/video materials. These can be downloaded below. For help downloading and using course materials, read our FAQs.

Lecture Videos

Lecture 1: Introduction to Computational and Systems Biology

Lecture 2: Local Alignment (BLAST) and Statistics

Lecture 3: Global Alignment of Protein Sequences (NW, SW, PAM, BLOSUM)

Lecture 4: Comparative Genomic Analysis of Gene Regulation

Lecture 5: Library Complexity and Short Read Alignment (Mapping)

Lecture 6: Genome Assembly

Leture 7: ChIP-seq Analysis; DNA-protein Interactions

Lecture 8: RNA-sequence Analysis: Expression, Isoforms

Lecture 9: Modeling and Discovery of Sequence Motifs

Lecture 10: Markov and Hidden Markov Models of Genomic and Protein Features

Assignments

Problem Set 1:Questions-Sequence search, global alignment, BLAST statistics

Problem Set 1:Solutions-Sequence search, global alignment, BLAST statistics

Problem Set 2:Questions- BWT, Library complexity, RNA-seq, Genome assembly, Motifs, Multiple hypothesis testing

Problem Set 2:Solutions- BWT, Library complexity, RNA-seq, Genome assembly, Motifs, Multiple hypothesis testing

pset_2_coding_portion.zip

Problem Set 3:Questions- Gibbs Sampler, RNA secondary structure, Protein Structure with PyRosetta, Connections

Problem Set 3:Solutions- Gibbs Sampler, RNA secondary structure, Protein Structure with PyRosetta, Connections

Problem_set_3.zip

Problem Set 4:Questions- Bayesian Networks, Refining Protein Structures in PyRosetta, Mutual information of protein residues

Problem Set 4:Solution- Bayesian Networks, Refining Protein Structures in PyRosetta, Mutual information of protein residues

Lecture Notes

Lecture1: Foundations of Computational and Systems Biology

Lecture2: Local Alignment (BLAST) and Statistics

Lecture3: Global Alignment of Protein Sequences

Lecture4: Comparative Genomics

Lecture 5: Library complexity and BWT

Lecture6: Genome Assembly

Lecture7: ChIP-Seq analysis; DNA-protein interactions

Lecture8: RNA-sequence analysis: expression, isoforms

Lecture 9: Modeling and Discovery of Sequence Motifs

Lecture 10: Markov and Hidden Markov Models of Genomic and Protein Features

Recitations

Recitaion 1: Review of topics covered in Lectures 2 and 3

Recitation 1: Statistics; Significance Testing; Bonferroni Correction

Recitation 2: Clustering, Model Selection, and BIC scores

Recitation 2: Review of topics covered in Lecture 4

Recitation 5: Gene Expression Program Discovery Using Topic Models

Recitation 5: Review of topics covered in Lectures 5 and 6

Recitation 5: Review of topics covered in Lectures 7 and 8

Recitation 6: Review of topics covered in Lecture 9 and 10

Recitation 7: Review of topics covered in Lecture 10

Recitation 8: Review of topics covered in Lectures 12 and 13

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