Friday, October 27, 2006

Alterbative Splicing--Christopher Lee, Jacek Majewski

Profossor C. Lee and professor J. Majewski conduct research in alterbative splicing using bioinformatics method.

Professor Lee : http://www.uclaaccess.ucla.edu/UCLAACCESS/Web/Faculty.aspx?ri=434
Professor J. Majewski: http://genomequebec.mcgill.ca/majewski/

Need a review of their method and focus.
Professor Black, Doug also engage research in alternative splicing, from a more traditional chemical and biological perspective

Sunday, October 22, 2006

Bioinformatics -- Andy Baxevanis Ouellette BFF

Baxevanis, A.D and Ouellette B.F.F coauthored a book Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins. This book is updated to the 3rd edition in 2005.

Baxevanis's previous work focus on computation analyis of disease-causing mutations from a structural standpoint, using innovative approaches to deduce the prisece structure change in protein cause by a specific genetic mutation. (What method?)

During the early development of microarray, Baxevanis's group developed the first publicly available program to restore and analyze microarray data.

Now, Baxevanis's group the group developed a software program known as GeneLink, which enables researchers to analyze large data sets from studies of complex-trait genetic disorders, such as cancer, diabetes, and hypertension, which involve many genes along with environmental factors.

Quelette is the head of UBC Bioinformatics Centre (UBiC) and this graduate program is worth of time to have a look.

Saturday, October 21, 2006

Bioinformatics -- Philip E. Bourne , Helge Weissig

This post is about Philip E. Bourne , Helge Weissig, two pioneer in structural bioinformatics. They coauthored a book Structural Bioinformatics. P.E.Bourne sumerize his lab's goal as follows in UCSD.

"Our goal is to undertake in silico bioinformatics-related research and education. Along the way we develop resources, for example, the RCSB Protein Data Bank(PDB) and the Immune Epitope Database (IEDB), for use by the community. We view these resources as being as important as disseminating our science through the scientific literature. We firmly support open access to the scientific literature through our work with the Public Library of Science and free access to our software"

P.E.Burne's group develop and maintain several databases

Biological Structure


  • The Protein Data Bank (PDB)

The single worldwide source of primary structural data on biological macromolecules determined experimentally. Developed in collaboration with Rutgers University our partner in the Research Collaboratory for Structural Bioinformatics (RCSB).

The main goal of this resource is to better understand principles behind structural domains identified from 3D coordinates ref .

  • Structure Comparison Database (CE)

Pair-wise structure comparisons based on the Combinatorial Extension (CE).

Compilation of recurring protein substructures.

Use of structure comparison to extend the coverage of GO terms in the PDB.

Automated classification of protein-DNA complexes of known structure.

  • Multiple Structure Alignment CE-MC

Starting from CE pair wise alignments a multi-structure alignment is computed using a Monte Carlo optimization technique.

Signal Transduction


  • The Protein Kinase Resource (PKR)

A compilation of structures, structure alignments, sequences and sequence alignments for the protein kinase family.

Apoptosis


Known domains involved in apoptosis and associated sequence alignments.

Immunology


  • Immune Epitope Database (IEDB)

Information that facilitates the dissemination of immune epitope information, the generation of new research tools, diagnostic techniques, vaccines and therapeutics for emerging and re-emerging diseases.


Helge Weissig's work centers around the research and education in strutural bioinformatics. His personal wedsite provide good directions on resoures in this field and a serise introductory courses
http://www.bioinformaticscourses.com/


Friday, October 20, 2006

Bioinformatics -- Sean Eddy

Sean Eddy's most significant contribution is that he suggests and developed many tools based on probabilistic models of biological sequence and structure. Hidden Markov models (stochastic regular grammars) are useful for primary structure analysis of proteins and DNA. Stochastic context-free grammars are ideal for analysis of RNA secondary structure.

His work include include the HMMER profile HMM search software and the Pfam protein domain database; the Infernal structural profile SCFG search software for RNAs and the Rfam RNA domain database; and the QRNA genefinding program for ncRNA genes.

He also apply probabilistic modeling and other computational algorithms to identify interesting genetic features in large-scale DNA sequence.

His work in this area is summerized his book
image
Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids
by Richard Durbin, Sean R. Eddy, Anders Krogh, Graeme Mitchison



Now, he focus on identifying novel structural and catalytic RNAs. He proposed the "modern RNA hypothesis" stating that: far from being a few scattered relics, RNAs are in fact in widespread use in modern organisms in a variety of roles. We now argue for a “modern RNA world” hypothesis: many of the RNAs we see today are modern inventions, highly adapted to regulatory roles in complex organisms.