BINF 760 - Machine Learning for Bioinformatics

Institution:

George Mason University

Subject:

Description:

Credits: 3 Machine learning and data mining methods relevant to application to problems in computational biology. Methods include decision trees, random forests, rule learning methods, support vector machines, neural networks, genetic algorithms, instance-based learning, Bayesian networks, and evaluation metrics for learning systems. Applications include cancer prediction, gene finding, protein function classification, gene regulation network inference, and other recent bioinformatics applications selected from the literature. Prerequisites Familiarity with bioinformatics methods and databases (e.g., BINF 630), molecular cell biology (e.g., BINF 631), bioinformatics programming (e.g., BINF 634), or permission of the instructor. Notes In addition to lectures from the instructor, students will present papers from the literature and complete a machine learning project. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0

Credits:

3.00

Credit Hours:

Prerequisites:

Corequisites:

Exclusions:

Level:

Instructional Type:

Lecture

Notes:

Additional Information:

Historical Version(s):

Institution Website:

www.gmu.edu

Phone Number:

(703) 993-1000

Regional Accreditation:

Southern Association of Colleges and Schools

Calendar System:

Semester

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