/>bmi core courses
The BMI curriculum requires all students to enroll in four core courses during their academic career.
BIOMEDIN 210. Introduction to Biomedical Informatics: Fundamental Methods; (Same as CS 270.)Issues in the modeling, design, and implementation of computational systems for use in biomedicine. Topics: basic knowledge representation, controlled terminologies in medicine and biological science, fundamental algorithms, information dissemination and retrieval, knowledge acquisition, and ontologies. Emphasis is on the principles of modeling data and knowledge in biomedicine and on translation of resulting models into useful automated systems. Recommended: principles of object-oriented systems.
Fall Quarter (Musen)
BIOMEDIN 211. Introduction to Biomedical Informatics: System Design; (Same as CS 271.)
Design and implementation of computational and information systems in complex
biomedical environments. Topics: requirements analysis, workflow and organizational
factors, functional specification, knowledge models, data heterogeneity and
standards, component-based architectures, human-computer interaction, and system
evaluation. Case studies illustrate challenges of system design for research
and clinical settings. Prerequisite: 210, or consent of instructor.
Winter Quarter (Das)
BIOMEDIN 212. Introduction to Biomedical Informatics Research Methodology;
(Same as CS 272.) Hands-on software building. Student teams conceive,
design, specify, implement, evaluate, and report on a software project in the
domain of biomedicine. Creating written proposals, peer review, providing status
reports, and preparing final reports. Guest lectures from professional biomedical
informatics systems builders on issues related to the process of project management.
Software engineering basics. Prerequisites: 210 or 214, or consent of instructor.
Fall Quarter (Altman, Cheng, Klein)
BIOMEDIN 214. Representations
and Algorithms for Computational Molecular Biology; (Same as CS 274.)
Topics: algorithms for alignment of biological sequences and structures, computing
with strings, phylogenetic tree construction, hidden Markov models, computing
with networks of genes, basic structural computations on proteins, protein structure
prediction, protein threading techniques, homology modeling, molecular dynamics
and energy minimization, statistical analysis of 3D biological data, integration
of data sources, knowledge representation and controlled terminologies for molecular
biology, graphical display of biological data, and genetic algorithms and programming
applied to biological problems. Prerequisites: four quarters/semesters of college-level biology (or an accelerated equivalent), programming skills and matrix
algebra.
Spring Quarter (Altman)
Biomedin 217. Translational Bioinformatics; (Same as CS 275.) Analytic, storage, and interpretive methods to optimize the transformation of genetic, genomic, and biological data into diagnostics and therapeutics for medicine. Topics: access and utility of publicly available data sources; types of genome-scale measurements in molecular biology and genomic medicine; analysis of microarray data; analysis of polymorphisms, proteomics, and protein interactions; linking genome-scale data to clinical data and phenotypes; and new questions in biomedicine using bioinformatics. Case studies. Prerequisites: programming ability at the level of CS 106A and familiarity with statistics and biology.