Foundations of Computational and Systems Biology

Course Description

This course is an introduction to computational biology emphasizing the fundamentals of nucleic acid and protein sequence and structural analysis; it also includes an introduction to the analysis of complex biological systems. Topics covered in the course include principles and methods used for sequence alignment, motif finding, structural modeling, structure prediction and network modeling, as well as currently emerging research areas. This course is designed for advanced undergraduates and graduate students with strong backgrounds in either molecular biology or computer science, but not necessarily both. The scripting language Python—which is widely used for bioinformatics and computational biology—will be used; foundational material covering basic programming skills will be provided by the teaching assistants. Graduate versions of the course involve an additional project component.

Instructors: Christopher Burge, David Gifford, Ernest Fraenkel

Copyright Information

Christopher Burge, David Gifford, and Ernest Fraenkel. 7.91J Foundations of Computational and Systems Biology, Spring 2014. (Massachusetts Institute of Technology: MIT OpenCourseWare), (Accessed 16 Feb, 2015). License: Creative Commons BY-NC-SA
Foundations of Computational and Systems Biology
Splice signal motifs of five species, created using the PICTOGRAM program. The height of each letter is proportional to the frequency of the corresponding base at the given position, and bases are listed in descending order of frequency from top to bottom. Source: Figure 2 of Lim, Lee P., and Christopher B. Burge. "A Computational Analysis of Sequence Features Involved in Recognition of Short Introns." (Courtesy of National Academy of Sciences)
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Video Lectures & Study Materials

Visit the official course website for more study materials:

# Lecture Play Lecture Notes & Slides
1 Introduction to Computational and Systems Biology (1:06:11) Play Video Lecture Slides
I. Genomic Analysis
2 Local Alignment (BLAST) and Statistics (1:16:48) Play Video Lecture Slides
3 Global Alignment of Protein Sequences (NW, SW, PAM, BLOSUM) (1:20:01) Play Video Lecture Slides
4 Comparative Genomic Analysis of Gene Regulation (1:22:38) Play Video Lecture Slides
II. Genomic Analysis—Next Gen Sequencing
5 Library Complexity and Short Read Alignment (Mapping) (1:20:06) Play Video Lecture Slides
6 Genome Assembly (1:08:14) Play Video Lecture Slides
7 ChIP-seq Analysis; DNA-protein Interactions (1:21:28) Play Video Lecture Slides
8 RNA-sequence Analysis: Expression, Isoforms (1:20:28) Play Video Lecture Slides
III. Modeling Biological Function
9 Modeling and Discovery of Sequence Motifs (1:22:06) Play Video Lecture Slides
10 Markov and Hidden Markov Models of Genomic and Protein Features (1:18:26) Play Video Lecture Slides
11 RNA Secondary Structure; Biological Functions and Predictions (1:22:40) Play Video Lecture Slides
IV. Proteomics
12 Introduction to Protein Structure; Structure Comparison and Classification (1:05:51) Play Video Lecture Slides
13 Predicting Protein Structure (1:04:22) Play Video Lecture Slides
14 Predicting Protein Interactions (1:11:38) Play Video Lecture Slides
V. Regulatory Networks
15 Gene Regulatory Networks (1:19:19) Play Video Lecture Slides
16 Protein Interaction Networks (1:20:50) Play Video Lecture Slides
17 Logic Modeling of Cell Signaling Networks (1:14:15) Play Video Lecture Slides
18 Analysis of Chromatin Structure (1:20:30) Play Video Lecture Slides
VI. Computational Genetics
19 Discovering Quantitative Trait Loci (QTLs) (1:22:13) Play Video Lecture Slides
20 Human Genetics, SNPs, and Genome Wide Associate Studies (1:17:57) Play Video Lecture Slides
21 Synthetic Biology: From Parts to Modules to Therapeutic Systems (1:21:46) Play Video
22 Causality, Natural Computing, and Engineering Genomes (51:47) Play Video


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