Hideaki Umeyama

发表

Fams‐ace: A combined method to select the best model after remodeling all server models

Genki Terashi, Mayuko Takeda-Shitaka, Kazuhiko Kanou, 2007, Proteins.

Heuristic principal component analysis based unsupervised feature extraction and its application to bioinformatics

Yoshiki Murakami, Y-h. Taguchi, Akira Okamoto, 2014 .

Structure Prediction with FAMS for Proteins Screened Critically to Autoimmune Diseases based upon Bioinformatics

Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, 2012, BIOINFORMATICS.

Shape and conformation : Predictive contribution of computer graphics for protein engineering and drug design

Hideaki Umeyama, 1992 .

Molecular dynamics simulation of a rhinovirus capsid under rotational symmetry boundary conditions

Hideaki Umeyama, Shigetaka Yoneda, Masako Kitazawa, 1996, J. Comput. Chem..

The SKE‐DOCK server and human teams based on a combined method of shape complementarity and free energy estimation

Genki Terashi, Mayuko Takeda-Shitaka, Kazuhiko Kanou, 2007, Proteins.

Genes associated with genotype-specific DNA methylation in squamous cell carcinoma as candidate drug targets

Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, 2014, BMC Systems Biology.

Heuristic principal component analysis-based unsupervised feature extraction and its application to gene expression analysis of amyotrophic lateral sclerosis data sets

Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, 2015, 2015 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology (CIBCB).

FAMSBASE: Modeling Database of 161 Genomes

Kazuhiko Kanou, Mitsuo Iwadate, Daisuke Takaya, 2003 .

Enlarged FAMSBASE: protein 3D structure models of genome sequences for 41 species

Akihiro Yamaguchi, Kei Yura, Mitsuo Iwadate, 2003, Nucleic Acids Res..

[Modeling of all genome and database].

Hideaki Umeyama, 2002, Nihon yakurigaku zasshi. Folia pharmacologica Japonica.

FAMS and FAMSBASE: Modeling of All the Genomes and Database

Mitsuo Iwadate, Hideaki Umeyama, Shigetsugu Kawakita, 2002 .

FAMSBASE: Modeling Database of 277 Genomes

Genki Terashi, Kazuhiko Kanou, Mitsuo Iwadate, 2005 .

Algorithm for normal mode analysis with general internal coordinates

Hideaki Umeyama, Kenshu Kamiya, Yoko Sugawara, 2003, J. Comput. Chem..

Principal component analysis-based unsupervised feature extraction applied to in silico drug discovery for posttraumatic stress disorder-mediated heart disease

Y-h. Taguchi, Mitsuo Iwadate, Hideaki Umeyama, 2015, BMC Bioinformatics.

Principal component analysis based unsupervised feature extraction applied to bioinformatics analysis

Yoshiki Murakami, Y-h. Taguchi, Mitsuo Iwadate, 2017 .

FAMS and FAMSBASE for Protein Structure

Hideaki Umeyama, Mitsuo Iwadate, M. Iwadate, 2003, Current protocols in bioinformatics.

Achievement of Protein 3D structure Prediction by advanced FAMS in CASP4

Hideaki Umeyama, Mayuko Takeda-Shitaka, Mitsuo Iwadate, 2001 .

Model Quality Assessment Using a Statistical Program that Adopts a Side Chain Environment Viewpoint

Genki Terashi, Mayuko Takeda-Shitaka, Kazuhiko Kanou, 2010 .

Bioinformatic Screening of Autoimmune Disease Genes and Protein Structure Prediction with FAMS for Drug Discovery

Mitsuo Iwadate, Hideaki Umeyama, Shigeharu Ishida, 2013, Protein and peptide letters.

Dynamic character of human growth hormone and its receptor: normal mode analysis.

Hideaki Umeyama, Mayuko Takeda-Shitaka, Kenshu Kamiya, 2003, Chemical & pharmaceutical bulletin.

Free energy perturbation calculations on multiple mutation bases

Hideaki Umeyama, Shigetaka Yoneda, 1992 .

Protein structure prediction in structure based drug design.

Daisuke Takaya, Hideaki Umeyama, Mayuko Takeda-Shitaka, 2004, Current medicinal chemistry.

An iterative compound screening contest method for identifying target protein inhibitors using the tyrosine-protein kinase Yes

Daisuke Kihara, Takashi Ishida, Masakazu Sekijima, 2017, Scientific Reports.

TINAGL1 and B3GALNT1 are potential therapy target genes to suppress metastasis in non-small cell lung cancer

Mitsuo Iwadate, Hideaki Umeyama, Y-h. Taguchi, 2014, BMC Genomics.

A new method for induced fit docking (GENIUS) and its application to virtual screening of novel HCV NS3-4A protease inhibitors.

Masahiko Ito, Daisuke Takaya, Hideaki Umeyama, 2011, Bioorganic & Medicinal Chemistry.

Bioinformatics based Ligand-Docking and in-silico screening.

Genki Terashi, Mitsuo Iwadate, Daisuke Takaya, 2008, Chemical & pharmaceutical bulletin.

Dynamic interaction among the platform domain and two membrane-proximal immunoglobulin-like domains of class I major histocompatibility complex: normal mode analysis.

Hideaki Umeyama, Mayuko Takeda-Shitaka, Kenshu Kamiya, 2008, Chemical & pharmaceutical bulletin.

The Study of Partition Coefficients. The Prediction of Log P Value Based on Molecular Structure

Hideaki Umeyama, Atsushi Tomonaga, Kenji Kasai, 1988 .

Evaluation of the third solvent clusters fitting procedure for the prediction of protein–protein interactions based on the results at the CAPRI blind docking study

Mitsuo Iwadate, Hideaki Umeyama, Katsuichiro Komatsu, 2003, Proteins.

Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target

Kun-Yi Hsin, Hiroaki Kitano, Y-h. Taguchi, 2015, Scientific Reports.

Visualization of electrostatic recognition by enzymes for their ligands and cofactors

Haruki Nakamura, Hideaki Umeyama, Setsuko Nakagawa, 1985 .

The origin of hydrogen bonding. An energy decomposition study

Hideaki Umeyama, Keiji Morokuma, K. Morokuma, 1977 .

Protein structure prediction in CASP6 using CHIMERA and FAMS

Genki Terashi, Mitsuo Iwadate, Daisuke Takaya, 2005, Proteins.

FAMS complex: a fully automated homology modeling system for protein complex structures.

Genki Terashi, Daisuke Takaya, Hideaki Umeyama, 2006, Medicinal chemistry (Shariqah (United Arab Emirates)).

FAMSD: A powerful protein modeling platform that combines alignment methods, homology modeling, 3D structure quality estimation and molecular dynamics.

Genki Terashi, Mitsuo Iwadate, Hideaki Umeyama, 2009, Chemical & pharmaceutical bulletin.

Searching for protein–protein interaction sites and docking by the methods of molecular dynamics, grid scoring, and the pairwise interaction potential of amino acid residues

Genki Terashi, Daisuke Takaya, Hideaki Umeyama, 2005, Proteins.