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Biomedical Signal Processing and Imaging
Clinical Decision Making
Computational Biophysics
Computational Genomics & Proteomics: Genomes, Networks, Evolution
Computational Neuroscience
Micro/Nanotechnology for Biology & Medicine
Quantitative Physiology
Sensory Communication
Synthetic Biology
Tissue Engineering

Computational Genomics & Proteomics

Courses: 6.047, 6.807, 6.874, 6.877J, 6.878

Robert Berwick
Erik Demaine
David Gifford
Piotr Indyk
Tommi Jaakkola
Manolis Kellis
Bruce Tidor


Computational genomics focuses on understanding the human genome, and more generally the principles of how DNA controls the biology of any species at the molecular level. With the current abundance of massive biological datasets, computational studies have become one of the most important means to biological discovery, and the skills developed in EECS are uniquely suited to such endeavors. We use algorithms and machine learning techniques to discover subtle biological signals in large genomes, reconstruct cellular networks, and reveal the mechanisms of genome evolution. For example, the computational analysis of several mammalian and vertebrate genomes enables us to pinpoint the precise locations of all human genes, recognize large conserved regions involved in early embryo development, discover repeated sequence motifs which govern tissue-specific gene usage, and reveal genes and regions under unusually rapid evolution.

 


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