CMSE 491/890: Bioinformatics & Computational Biology

CMSE 491/890: Bioinformatics & Computational Biology

January 7th, 11:00AM to May 3rd, 12:15PM

Instructor: Dr. Arjun Krishnan

An introduction to contemporary topics, discussing the major biological/biomedical questions, exploring the relevant datasets, and understanding the underlying analytical approaches (from probability/statistics, applied mathematics, algorithms/data-structures, and data-science/machine-learning).

Event Categories:  Trainings

Note this course is open to both undergraduate (400-level) and graduate (800-level) students and counts towards the CMSE minor, garduate certificates, and dual PhD.

Through discussions of primary literature and a class project, students will also have the opportunity to learn how to: Formulate problems for quantitative inquiry • Design computational projects • Think critically about data & methods • Perform reproducible research • Communicate research findings.

Topics

Genome assembly & annotation • Sequence alignment & pattern finding • Comparative genomics • Genetic variation & quantitative genetics • Regulatory genomics • Functional genomics • Molecular & digital evolution • Molecular dynamics • Protein residue coupling & structure prediction • Modeling cellular pathways • Metabolomics & modeling metabolic flux • Large-scale biological networks

For more information visit the course website: https://github.com/krishnanlab/teaching/tree/master/2019-spring_compbio

Course Flyer

Prerequisites

CMSE 201 or CMSE 301-305 or equivalent with programming; Two semesters of introductory biology; Statistics at the level of STT 231 is strongly recommended.