Bioinformatics & Computational Biology

BCB 1003. EXPLRNG BIOINFMTCS & COMPU BIO

BCB 100X. EXPLORING BIOINFORMATICS AND COMPUTATIONAL BIOLOGY

Life scientists are generating huge amounts of data on many different scales, from DNA and protein sequence, to information on biological systems such as protein interaction networks, brain circuitry, and ecosystems. Analyzing these kinds of data requires quantitative knowledge and approaches using computer science and mathematics. In this project-based course, students will use case studies to learn about both important biological problems and the computational tools and algorithms used to study them. Students will study a sampling of topics in the field, including such areas as complex disease genetics, analysis of a flu epidemic, investigating antibiotic resistance, and understanding the behavior of swarms, such as schooling fish. Computational tools explored will include both freely-available web-based tools as well as guided programming using Python.
Recommended background: High school biology. Programming experience is not required.

BCB 3010. SIMULATION IN BIOLOGY

Cat. II
Computer simulations are becoming increasingly important in understanding and predicting the behavior of a wide variety of biological systems, ranging from metastasis of cancer cells, to spread of disease in an epidemic, to management of natural resources such as fisheries and forests. In this course, students will learn to use a graphical programming language to simulate biological systems. Most of the classroom time will be spent working individually or in groups, first learning the language, and then programming simulation projects. We will also discuss several papers on biological simulations from the primary scientific literature. In constructing and comparing their simulations, students will demonstrate for
themselves how relatively simple behavioral rules followed by individual molecules, cells, or organisms can result in complex system behaviors.
Recommended background: Students taking this course must have a solid background in a biological area they would like to simulate, at about the depth provided by a BB 3000 level class. No programming experience is assumed. This course will be offered in 2016-2017, and in alternating years therafter.

BCB 4001. BIOINFORMATICS

Cat. II
In an age when the amount of new biological data generated each year is exploding, it has become essential to use bioinformatics tools to explore biological questions. This class will provide and understanding of how we organize, catalog, analyze, and compare biological data across whole genomes, covering a broad selection of important databases and techniques. Students will acquire a working knowledge of bioinformatics applications through hands-on use of software to ask and answer biological questions in such areas as genetic sequence and protein structure comparisons, phylogenetic tree analysis, and gene expression and biological pathway analysis. In addition, the course will provide students with an introduction to some of the theory underlying the software (for example, how alignments are made and scored).
Recommended background: a working knowledge of concepts in genetics and molecular biology (BB2920 and BB2950 or equivalent), and statistics (MA2610 or MA2611 or equivalent)
This course will be offered in 2016-17, and in alternating years thereafter.

BCB 4002. BIOVISUALIZATION

Cat. II
This course will use interactive visualization to model and analyze biological
information, structures, and processes. Topics will include the fundamental
principles, concepts, and techniques of visualization (both scientific and
information visualization) and how visualization can be used to study
bioinformatics data at the genomic, cellular, molecular, organism, and
population levels. Students will be expected to write small to moderate programs
to experiment with different visual mappings and data types.

Recommended background: CS 2102, CS 2223, and one or more biology
courses.
This course will be offered in2016-17. and in alternating years thereafter.

BCB 4003. BIOLOGICAL AND BIOMEDICAL DATABASE MINING

Cat. II
This course will investigate computational techniques for discovering patterns in
and across complex biological and biomedical sources including genomic and
proteomic databases, clinical databases, digital libraries of scientific articles, and
ontologies. Techniques covered will be drawn from several areas including
sequence mining, statistical natural language processing and text mining, and
data mining.

Recommended Background: CS 2102, CS 2223, MA 2610 or MA 2611, and
one or more biology courses.
This course will be offered in 2015-16, and in alternating years thereafter.

BCB 4004. STATISTICAL METHODS IN GENETICS AND BIOINFORMATICS

Cat. II

This course provides students with knowledge and understanding of the
applications of statistics in modern genetics and bioinformatics. The course
generally covers population genetics, genetic epidemiology, and statistical models
in bioinformatics. Specific topics include meiosis modeling, stochastic models
for recombination, linkage and association studies (parametric vs. nonparametric
models, family-based vs. population-based models) for mapping genes of
qualitative and quantitative traits, gene expression data analysis, DNA and
protein sequence analysis, and molecular evolution. Statistical approaches
include log-likelihood ratio tests, score tests, generalized linear models, EM
algorithm, Markov chain Monte Carlo, hidden Markov model, and classification
and regression trees.

Recommended background: MA 2612, MA 2631 (or MA 2621), and one or
more biology courses.
This course is offered in 2015-16, and in alternating years thereafter.