CMSC702

Computational Systems Biology

An introduction to the fundamental concepts in the computational analysis of biological systems with applications to: functional genomics, population genetics, interaction networks, epigenetics. Computational concepts convered: network and graph algorithms, machine learning, large data/network visualization, statistical modeling and inference, probabilistic graphical models, sparse methods in data analysis, numerical optimization. No prior knowledge of biology required.

Fall 2025

1 review
Average rating: 5.00

Past Semesters

1 review
Average rating: 5.00

0 reviews
Average rating: N/A

0 reviews
Average rating: N/A

During the Spring 2020 and Spring 2021 semesters, students could choose to take some of their courses pass-fail mid-semester which skews grade data aggregated across multiple semesters.

Average GPA of 3.68 between 151 students*

CMSC702 Grade Distribution+-0510152025303540455055606570758085% of studentsABCDFWother
A-: 21.19%
A: 34.44%
A+: 25.83%
B-: 1.99%
B: 2.65%
B+: 6.62%
C+: 0.66%
F: 0.66%
W: 2.65%
other: 3.31%
* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.