The Computational Biology group at UCSC is dedicated to the discovery and implementation of algorithms that facilitate the understanding of biological processes. Our work emphasises the application of statistical and machine learning techniques. Because these methods are often compute-intensive, we strive to create algorithms and heuristics that are computationally efficient on serial and parallel computers. Members of the group study the primary (sequence), secondary (folding), and tertiary (3-dimensional) structures of DNA, RNA and protein sequences.

We are part of the UCSC Center for Biomolecular Science & Engineering

• People
• Research
• Documentation
• Bioinformatics programs of study We have a frequently-asked-questions (FAQ) page about our bioinformatics programs.
  • BS in Bioinformatics
  • proposed MS/Phd in Bioinformatics (not approved yet---this longer version of the proposal posted Jan 2002) Until our MS/PhD programs in bioinformatics are approved, we recommend that students interested in bioinformatics apply to the computer science graduate programs.
• UCSC bioinformatics classes
  • Introduction to Bioinformatics
  • Bioinformatics I (Computational Analysis of Proteins)
  • Bioinformatics II (Computational Genomics)
  • Bioinformatics seminar
• Karplus' selection of useful WWW pointers.
• ISMB99 tutorial on using hidden Markov models.
• UCSC Computational Biology FTP site (not recently updated)
• Fellowship Opportunities for Computational Biology Graduate Students
• Fellowship Opportunities for Computational Biology Postdoctoral Students & Researchers

• UCSC work on the Human Genome Project, includes downloadable files as a whole data set or by individual clone contigs.
• HMM applications, such as sequence query against a database or model library (includes SAM-T98).
• SAM hidden Markov modeling suite.
• Human gene prediction with the UCSC/LBL Genie project.
• E. coli gene prediction with EcoParse hidden Markov models.
• Small subunit ribosomal RNA secondary structure prediction with RNACAD a stochastic context free grammar modeling system.
• G-protein Coupled Receptor Classification, a GPCR subfamily classifier that uses HMMs and support vector machines.

• The Intronerator, cDNA alignments, gene predictions, sequence data and literature links in C. elegans.
• Support Vector Machine Classification of Microarray Gene Expression Data A link to the SVM technical report and results.
• Ares Lab Intron Site, a searchable Database of spliceosomal class of introns in Saccharomyces cerevisiae (Yeast).
• Potential SECIS elements in HIV-1. Full data about potential SECIS elements in HIV-1.
• A preliminary site for information about DNA repair proteins. This site is mainly a mock-up now, since the project is not funded.

• gen_sequence a program for generating random sequences of amino acids with lengths and compositions typical of those found in real protein databases. This package also includes random number generators for normal, beta, Dirichlet, and mixture of Dirichlet distributions.

Read an overview of our research from UCSC's Review magazine including the main bioinformatics article that includes pictures from the Kestrel sequence analysis engine, and a sidebar on protein folding.

We had an informal post-CASP Bioinformatics Workshop on Fri December 8 and Sat Dec 9, 2000. This workshop replaces the Bay Area Bioinformatics meeting for December.

The Computation Biology group is supported in part by NSF grant DBI-9808007, NSF grant MIP-9488395, DOE grant DE-FG03-99ER62849, LACOR grant 4158U0015-3A-01, and by GANN and NSF graduate fellowships.

Acquisition of Alpha workstations and AlphaServers was made possible by the above grants, NSF grant CDA-9115268, and a donation from