CMSC498Y

Selected Topics in Computer Science; Statistical Inference and Machine Learning Methods for Genomics Data

Covers statistical inference and machine learning methods for analyzing genomic data. Examples of topics covered will include maximum likelihood (including composite and pseudo-likelihood functions), expectation-maximization, clustering algorithms, hidden markov models, statistical testing, MCMC and variational inference. Our focus will be on how these techniques are utilized to solve biological problems and the practical challenges that arise when analyzing large genomic data sets.

Sister Courses: CMSC498A, CMSC498B, CMSC498C, CMSC498D, CMSC498E, CMSC498F, CMSC498I, CMSC498J, CMSC498L, CMSC498N, CMSC498O, CMSC498P, CMSC498Q, CMSC498R, CMSC498T, CMSC498V, CMSC498W, CMSC498X, CMSC498Z

Spring 2024

4 reviews
Average rating: 5.00

Spring 2023

4 reviews
Average rating: 5.00

Past Semesters

0 reviews
Average rating: N/A

4 reviews
Average rating: 5.00

* "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.