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Course Criteria
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3.00 Credits
Credits: 3 Mathematical and computational methods for analysis of cellular and subcellular processes. Topics may include ion channels, whole cell models, intracellular signaling, biochemical oscillations, pathway modeling, parameter estimation, and sensitivity analysis. Prerequisites Calculus and knowledge of a computer programming language; and BINF 690 and 701; or permission of instructor. Notes Course in differential equations is recommended. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
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
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3.00 Credits
Credits: 3 Reading and research on specific topic in computational sciences and informatics under direction of faculty member. Notes May be repeated. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Project chosen and completed under guidance of graduate faculty member that results in acceptable technical report. Prerequisites 12 graduate credits and permission of instructor. Hours of Lecture or Seminar per week 0 Hours of Lab or Studio per week 0
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1.00 - 6.00 Credits
Credits: 1-6 Project chosen and completed under guidance of graduate faculty member that results in acceptable technical report (master's thesis) and oral defense. Prerequisites 12 graduate credits and permission of instructor. Hours of Lecture or Seminar per week 0 Hours of Lab or Studio per week 0 Grading S/IP
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3.00 Credits
Credits: 3 Topics may include cell structure, biomembranes and cell architecture, cell signaling, receptor activation, gene expression and control, protein targeting and trafficking, and cell cycle regulation. Prerequisites BINF 631 or equivalent. Notes Advanced molecular and cellular biology foundation for BINF students. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Covers knowledge-based, large-scale protein structure analysis; classification and prediction of protein structure and function; and other current research topics in structural genomics. Projects address entire research enterprise from developing and defending proposal to peer-reviewed publication. Prerequisites BINF 731, or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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3.00 Credits
Credits: 3 Research-oriented course combining lectures and work on individual projects in biomolecular simulations. Topics include protein and peptide aggregation, binding, and unfolding and folding. Prerequisites BINF 741, or permission of instructor. Hours of Lecture or Seminar per week 3 Hours of Lab or Studio per week 0
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1.00 - 12.00 Credits
Credits: 1-12 Reading and research on specific topic in computational sciences and informatics under direction of faculty member. Prerequisites Admission to doctoral program and permission of instructor. Notes May be repeated. Hours of Lecture or Seminar per week 0 Hours of Lab or Studio per week 0
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1.00 - 12.00 Credits
Credits: 1-12 Covers development of research proposal, which forms basis for doctoral dissertation, under guidance of dissertation director and doctoral committee. Prerequisites Permission of advisor. Notes May be repeated. Hours of Lecture or Seminar per week 0 Hours of Lab or Studio per week 0 Grading S/IP
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