TOPICS IN
COMPUTATIONAL MOLECULAR BIOLOGY
18.418
Home
Lectures
Resources
Staff
Progamming
Although there is no programming requirement for this class, here are some useful pointers to places that might be of interest to folks undertaking computational biology related projects.
Cran R
An R Tutorial
Bioconductor
Weka
Biopython
GenePattern
Biology
Branden and Tooze, "Introduction to Protein Structure"
Kohane, Kho and Butte, "Microarrays for an Integrative Genomics"
6.874 Computational Systems Biology Lecture Notes
Rothman, Greenland and Lash "Modern Epidemiology"
Purves, Sadava, Orians and Heller, "Life: The Science of Biology"
Chuaqui, et al. "Post-analysis follow-up and validation of microarray experiments"
Machine Learning
6.867 Machine Learning Lecture Material
18.05 Introduction to Probability and Statistics
6.041 / 6.431 Probabilistic Systems Analysis and Applied Probability
Daphne Koller and Nir Friedman, "Probabilistic Graphical Models"
Ian H. Witten and Eibe Frank, "Data Mining: Practical Machine Learning Tools and Techniques"
David MacKay, "Information Theory, Inference, and Learning Algorithms"
© MIT 2015