Yukimitsu Yabuki

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Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amino acid residues in membrane proteins that perform major functions, such as channels/pores, electrochemical potential-driven transporters and primary active transporters. We observed that the(More)
We describe a novel system, GRIFFIN (G-protein and Receptor Interaction Feature Finding INstrument), that predicts G-protein coupled receptor (GPCR) and G-protein coupling selectivity based on a support vector machine (SVM) and a hidden Markov model (HMM) with high sensitivity and specificity. Based on our assumption that whole structural segments of(More)
We have developed the database TMFunction, which is a collection of more than 2900 experimentally observed functional residues in membrane proteins. Each entry includes the numerical values for the parameters IC50 (measure of the effectiveness of a compound in inhibiting biological function), V(max) (maximal velocity of transport), relative activity of(More)
We have developed the database, TMBETA-GENOME, for annotated beta-barrel membrane proteins in genomic sequences using statistical methods and machine learning algorithms. The statistical methods are based on amino acid composition, reside pair preference and motifs. In machine learning techniques, the combination of amino acid and dipeptide compositions has(More)
GENIUS II is an automated database system in which open reading frames (ORFs) in complete genomes are assigned to known protein three-dimensional (3D) structures. The system uses the multiple intermediate sequence search method in which query and target sequences are linked by intermediate sequences gathered by PSI-BLAST search. By applying the system to(More)
We have developed a novel approach for dissecting transmembrane beta-barrel proteins (TMBs) in genomic sequences. The features include (i) the identification of TMBs using the preference of residue pairs in globular, transmembrane helical (TMH) and TMBs, (ii) elimination of globular/TMH proteins that show sequence identity of more than 70% for the coverage(More)
We describe a novel method for predicting G-protein coupled receptor (GPCR) G-protein coupling selectivity using amino acid properties of specific residues in GPCR sequences. We have evaluated various amino acid properties obtained with experimental or theoretical studies. The GPCRs having reliable G-protein binding information were collected from Guide to(More)
Takatsugu Hirokawa Hidetoshi Mukai t-hirokawa@aist.go.jp mukaih@libra.ls.m-kagaku.co.jp 1 Computational Biology Research Center, 2-43 Aomi, Koto-ku, Tokyo 135-0064, Japan . Information and Mathematical Science Laboratory, Inc, 2-43-1, Ikebukuro, Toshima-ku, Tokyo, 171-0014, Japan 3 Nara Institute of Science and Technology, 8916-5 Takayama-cho, Ikoma-shi,(More)
We have developed the database, TMBETAGENOME, for annotated b-barrel membrane proteins in genomic sequences using statistical methods and machine learning algorithms. The statistical methods are based on amino acid composition, reside pair preference and motifs. In machine learning techniques, the combination of amino acid and dipeptide compositions has(More)