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Predicting Protein Function from Sequence using Machine Learning
Posted by: david on Saturday, May 19, 2001 - 10:31 PM
Protein News
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[excerpt] These are the rules generated to predict function of the Open Reading Frames (ORFs) in the genomes at the different levels in the functional hierarchies, and the predictions that these rules made on the unseen test data, and on the unclassified ORFs in the data. A dash ('-') by an ORF name indicates this prediction was wrong and the correct classification is given (except for the unclassified ORFs listed under "Application to new data", as their true function is unknown). Any ORFs listed under the "Application to new data" sections are our predictions for ORFs which do not yet have a good functional classification.
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Insight into the Catalytic Mechanism of DNA Polymerase Beta
Posted by: david on Saturday, May 19, 2001 - 10:25 PM
Protein News
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[excerpt] DNA replication is a fundamental biological process required for cellular reproduction. The central feature of DNA replication is the template-directed nucleotidyl transfer reaction mediated by DNA polymerases. In recent years, significant progress has been made in elucidating the mechanism of enzymatic polymerization, including the determination of the structures of several DNA polymerases and their complexes with substrates or substrate analogues. These structures support a two metal ion mechanism of nucleotide incorporation, a feature thought to be shared by all families of polynucleotide polymerases.
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IBM forms large protein folding team
Posted by: david on Saturday, May 19, 2001 - 06:04 PM
Protein News
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[excerpt - originally published in June 1999] IBM has formed what is probably the largest protein folding project teams ever assembled, to study how proteins fold. This will determine how polymers chains of amino acid residues, freshly made by genes, fold up to achieve their three dimensional structure as protein molecules, and then perform their activities as instructed by the genes. Understanding of this process would also represent understanding of the code in the one dimensional DNA molecules becomes the three dimensional form that we call life, would allow us to interpret the output of the human genome project and other genome projects, and improve our ability to design drugs by seeing the three dimensional molecular details of the proteins in our bodies (with which almost all kinds of drug interact). At present, such bottlenecks as the inability to read the human genome, and understand it in terms of protein structure and function, are prohibiting the development of major health care applications and pharmaceutical markets.
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Myriad, Hitachi, Oracle and Friedli Join Forces to Map the Entire Human Proteome
Posted by: david on Saturday, May 19, 2001 - 06:04 PM
Protein News
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[excerpt] Myriad Genetics, Inc. (Nasdaq: MYGN), Hitachi, Ltd. (NYSE: HIT) and Oracle (Nasdaq: ORCL,) today announced that they have formed a landmark alliance to map the human proteome in less than three years. The collaboration will combine Myriad's proteomics expertise with the leading information and electronics technologies of Hitachi and the leading software capabilities of Oracle, to analyze all proteins and their interactions within cells of the body. The alliance partners expect to collect this information in a proprietary database of all human protein interactions, all biochemical pathways and a comprehensive catalog of purified proteins by 2004.
The collaboration, valued at $185 million, will take place within the newly formed Myriad Proteomics, Inc., a 50% owned subsidiary of Myriad Genetics. Myriad Proteomics will market its proprietary database and set of proteomic materials to pharmaceutical and biotechnology companies for therapeutic and diagnostic product development.
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IBM ANNOUNCES $100 MILLION TO BUILD WORLD'S FASTEST SUPERCOMPUTER
Posted by: david on Saturday, May 19, 2001 - 06:04 PM
Protein News
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[excerpt - originally published December 6, 1999] Blue Gene's massive computing power will be initially used to model the folding of human proteins, making this fundamental study of biology the company's first computing "grand challenge" since Deep Blue defeated world chess champion Garry Kasparov in 1997. Learning more about how proteins fold is expected to give doctors better understanding of diseases, as well as potential cures.
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