• [Photo] Jason Skie May 25, 2002
    Genome Exploration Research Group in Yokohama is developing strategic technologies for high-throughput gene-function identification starting from the full-length cDNA technology and the derived mouse full-length cDNA collection of the Mouse Genome Encyclopedia.

    The Genome Function and Technology Exploration Team has proceeded high-throughput analysis of protein-protein interactions (PPI) and developed the PPI Network Viewer to grasp the major PPI networks visually, therefore other large-scale data of our group including sequencing information, chromosomal mapping information, and gene expression information, is closely linked. The team has also developed the Interaction Generality Method to estimate the reliability of each interaction computationally and also gives priority to discover and apply bioinformatics methods for the PPI analysis and the integrated data analysis. The following position is immediately available.

    [Researcher]: Bioinformatics (System Biology)

    The successful candidate will establish a key strategy and system for bioinformatics methods to analyze the PPI data and the PPI-based integrated data. He/She will develop the key programs and subsequently apply them broadly on biological problems selected from signal transduction, neurobiology, mouse model of human pathologies or structural biology. The qualifications required are Ph.D. (or equivalent) in Bioinformatics, Computational Biology, Computer Science or a related field with strong knowledge of Structural Biology, Molecular Biology, and Genomics. The applicants with experience in Natural Language Processing, Applied Mathematics and Physics, or a related field, who have intensive interest in Bioinformatics research, will also be considered. The ability of programming(Unix with programming skills in Perl, Java or C/C++ is required.), fluency in English will be essential. He/She should be proactive, highly motivated, and have a positive attitude, sense of humor in a stimulating, interactive, open communicative research environment.

    More information can be found at the following link:

    http://www.genesciences.com/cgi-bin/jobs/classifieds.cgi?db=biotech&website=&language=
    &session_key=&search_and_display_db_button=on&results_format=long&db_id=73&query=retrieval

    (You may need to cut-and-paste each line, of the URL, separately into your browser)

Discussion forums: Researcher: Bioinformatics (System Biology)

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system biology
Submitted by Nobody ; posted on Friday, May 2, 2003
what is system biology
Virtual Seminar on Genomics and Bioinformatic
Submitted by Nobody ; posted on Thursday, February 12, 2004
Virtual Seminar on Genomics and Bioinformatics www.virtualgenomics.org Thursday, March 04, 2004, Noon - 1PM US Eastern time Yang Zhang and Jeffrey Skolnick Center of Excellence in Bioinformatics, University at Buffalo Protein Structure Prediction on a Genomic Scale Despite considerable effort, the prediction of the native structure of a protein from its amino acid sequence remains an outstanding unsolved problem. In this postgenomic era, because protein structure can assist in functional annotation, the need for progress is even more crucial. In this talk, we present the recent structure prediction results by TASSER based on a large-scale benchmark test. TASSER is a new hierarchical approach to protein structure prediction that consists of template identification by threading, followed by the assembly of tertiary structures via rearranging continuous template fragments under the guide of an optimized C-alpha and side chain based potential. The benchmark set includes 1489 medium size proteins that cover the whole Protein Data Bank (PDB) library at the level of 35% sequence identity. Starting from the structure templates identified by our threading algorithm PROSPECTOR_3 where homology proteins are excluded, we can fold the proteins in two thirds (990/1489) of cases, which have at least one model among the top five with a root-mean-square-deviation to native below 6.5 Angstrom. When using the best possible templates identified by structurally aligning the native structure through the PDB, TASSER can fold almost all the proteins (except for 2/1489) with accuracy comparable to low-resolution experimental structures. With both templates from the threading and the structure alignment, TASSER models show improvement with respect to the initial templates. With the comparison of the quality of the final models in these two simulations, these data highlight the urgent need for progress in fold recognition alignment algorithms, which will lead to the eventual solution of the protein structure prediction problem.

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