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CS 690: Computational Genomics


Familiarity with algorithms and data structures, probability and statistics and computer programming. Knowledge of machine learning is also helpful for the course.

About the Course

Computational genomics is a novel and very active application field of computer science where biological mechanisms are deciphered from genome sequencing data using computational and statistical analyses. In the past twenty years, an explosion of genomic data (from human and several other organisms) has revolutionized a number of subfields of biology – cell and molecular biology, developmental biology, disease biology and so on. Computer science plays a central role in genomics – from sequencing and assembling of DNA and RNA sequences to analyzing genomes (or transcriptomes) for elucidating diverse biological mechanisms through innovations in machine learning, data structure and algorithms. In this course, you will be introduced to some of the most seminal machine learning and algorithmic approaches for sequence analysis as well as the most recent advances in the field. The course will be structured as a combination of lectures and discussion of recent publications in the field. The lectures will introduce the topics and seminal algorithms followed by research paper discussions on advanced and most recent developments.


Tentative Topics


Recommended Books


The above books are recommended but not required. In addition, a number of research papers will be discussed.