M Kanehisa

Summary

Affiliation: Kyoto University
Country: Japan

Publications

  1. ncbi Molecular Network Analysis of Diseases and Drugs in KEGG
    Minoru Kanehisa
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Japan
    Methods Mol Biol 939:263-75. 2013
  2. ncbi MUCHA: multiple chemical alignment algorithm to identify building block substructures of orphan secondary metabolites
    Masaaki Kotera
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    BMC Bioinformatics 12:S1. 2011
  3. ncbi KEGG for integration and interpretation of large-scale molecular data sets
    Minoru Kanehisa
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 40:D109-14. 2012
  4. ncbi Observing metabolic functions at the genome scale
    Jean Marc Schwartz
    Bioinformatics Center, Kyoto University, Uji, Kyoto 611 0011, Japan
    Genome Biol 8:R123. 2007
  5. ncbi Evolutionary history and functional implications of protein domains and their combinations in eukaryotes
    Masumi Itoh
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Genome Biol 8:R121. 2007
  6. ncbi Characterization of relationships between transcriptional units and operon structures in Bacillus subtilis and Escherichia coli
    Shujiro Okuda
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    BMC Genomics 8:48. 2007
  7. ncbi MIMOX: a web tool for phage display based epitope mapping
    Jian Huang
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    BMC Bioinformatics 7:451. 2006
  8. ncbi Mining prokaryotic genomes for unknown amino acids: a stop-codon-based approach
    Masashi Fujita
    Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan
    BMC Bioinformatics 8:225. 2007
  9. ncbi Regulation of metabolic networks by small molecule metabolites
    Alex Gutteridge
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Kyoto, Japan 611 0011
    BMC Bioinformatics 8:88. 2007
  10. ncbi Quantitative elementary mode analysis of metabolic pathways: the example of yeast glycolysis
    Jean Marc Schwartz
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    BMC Bioinformatics 7:186. 2006

Detail Information

Publications88

  1. ncbi Molecular Network Analysis of Diseases and Drugs in KEGG
    Minoru Kanehisa
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Japan
    Methods Mol Biol 939:263-75. 2013
    ..Here we give an introduction to the KEGG Mapper tools, especially for understanding disease mechanisms and adverse drug interactions...
  2. ncbi MUCHA: multiple chemical alignment algorithm to identify building block substructures of orphan secondary metabolites
    Masaaki Kotera
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    BMC Bioinformatics 12:S1. 2011
    ..However, they are optimized for ligand binding and are not suitable for metabolomic studies...
  3. ncbi KEGG for integration and interpretation of large-scale molecular data sets
    Minoru Kanehisa
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 40:D109-14. 2012
    ..Finally, we describe recent enhancements to the KEGG content, especially the incorporation of disease and drug information used in practice and in society, to support translational bioinformatics...
  4. ncbi Observing metabolic functions at the genome scale
    Jean Marc Schwartz
    Bioinformatics Center, Kyoto University, Uji, Kyoto 611 0011, Japan
    Genome Biol 8:R123. 2007
    ....
  5. ncbi Evolutionary history and functional implications of protein domains and their combinations in eukaryotes
    Masumi Itoh
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Genome Biol 8:R121. 2007
    ..To elucidate the characteristics and evolutionary mechanisms that underlie such domain combinations, it is essential to examine the different types of domains and their combinations among different groups of eukaryotes...
  6. ncbi Characterization of relationships between transcriptional units and operon structures in Bacillus subtilis and Escherichia coli
    Shujiro Okuda
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    BMC Genomics 8:48. 2007
    ..Information about such complicated operons is helpful for predicting and analyzing operon structures, as well as understanding gene functions and transcriptional regulation...
  7. ncbi MIMOX: a web tool for phage display based epitope mapping
    Jian Huang
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    BMC Bioinformatics 7:451. 2006
    ..Most of the existing tools have not been implemented as an online service until now however, making it less convenient for the community to access, utilize, and evaluate them...
  8. ncbi Mining prokaryotic genomes for unknown amino acids: a stop-codon-based approach
    Masashi Fujita
    Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan
    BMC Bioinformatics 8:225. 2007
    ..A protein-level study will provide independent insight into the novel amino acid...
  9. ncbi Regulation of metabolic networks by small molecule metabolites
    Alex Gutteridge
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Kyoto, Japan 611 0011
    BMC Bioinformatics 8:88. 2007
    ..We look at the network properties of this regulatory system and the relationship between the chemical properties of regulatory molecules...
  10. ncbi Quantitative elementary mode analysis of metabolic pathways: the example of yeast glycolysis
    Jean Marc Schwartz
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    BMC Bioinformatics 7:186. 2006
    ....
  11. ncbi Clustering under the line graph transformation: application to reaction network
    Jose C Nacher
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, 611 0011, Japan
    BMC Bioinformatics 5:207. 2004
    ..While the chemical compound network has been classified as hierarchical network, a detailed study of the chemical reaction network had not been carried out...
  12. ncbi Extraction of phylogenetic network modules from the metabolic network
    Takuji Yamada
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, 611 0011, Japan
    BMC Bioinformatics 7:130. 2006
    ..Although each organism has its individual network, some organisms contain common sub-networks based on function. Given a certain sub-network, the distribution of organisms common to it represents the diversity of its function...
  13. ncbi The KEGG resource for deciphering the genome
    Minoru Kanehisa
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 32:D277-80. 2004
    ..New efforts are being made to abstract knowledge, both computationally and manually, about ortholog clusters in the KO (KEGG Orthology) database, and to collect and analyze carbohydrate structures in the GLYCAN database...
  14. ncbi Representation and analysis of molecular networks involving diseases and drugs
    Minoru Kanehisa
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Genome Inform 23:212-3. 2009
    ....
  15. ncbi From genomics to chemical genomics: new developments in KEGG
    Minoru Kanehisa
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 34:D354-7. 2006
    ..Additionally, drug information is now stored separately and linked to new KEGG DRUG structure maps...
  16. ncbi KEGG for representation and analysis of molecular networks involving diseases and drugs
    Minoru Kanehisa
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 38:D355-60. 2010
    ..The new disease/drug information resource named KEGG MEDICUS can be used as a reference knowledge base for computational analysis of molecular networks, especially, by integrating large-scale experimental datasets...
  17. ncbi Bioinformatics in the post-sequence era
    Minoru Kanehisa
    Bioinformatics Center, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nat Genet 33:305-10. 2003
    ....
  18. ncbi Prediction of higher order functional networks from genomic data
    M Kanehisa
    Bioinformatics Centre, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Pharmacogenomics 2:373-85. 2001
    ..e., the biological systems. Bioinformatics provides basic concepts as well as practical methods to integrate this view with the traditional view and to analyse complex interactions among building blocks and with dynamic environments...
  19. ncbi The KEGG databases at GenomeNet
    Minoru Kanehisa
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 30:42-6. 2002
    ..The KEGG databases are updated daily and made freely available (http://www.genome.ad.jp/kegg/)...
  20. ncbi KEGG: kyoto encyclopedia of genes and genomes
    M Kanehisa
    Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 28:27-30. 2000
    ..The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/)...
  21. ncbi Extraction of correlated gene clusters by multiple graph comparison
    A Nakaya
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Genome Inform 12:44-53. 2001
    ..cerevisiae, and estimated the possibility of utilizing our method for screening the datasets that are likely to contain many false positive relations...
  22. ncbi Protein network inference from multiple genomic data: a supervised approach
    Y Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan
    Bioinformatics 20:i363-70. 2004
    ..In this context, the problem of inferring a global protein network for a given organism, using all available genomic data about the organism, is quickly becoming one of the main challenges in current computational biology...
  23. ncbi Prediction of glycan structures from gene expression data based on glycosyltransferase reactions
    Shin Kawano
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan
    Bioinformatics 21:3976-82. 2005
    ..Using expression profiles from the human carcinoma cell, glycan structures with sialic acid and sialyl Lewis X epitope were predicted, which corresponded well with experimental results...
  24. ncbi Prediction of drug-target interaction networks from the integration of chemical and genomic spaces
    Yoshihiro Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 24:i232-40. 2008
    ..Therefore, there is a strong incentive to develop new methods capable of detecting these potential drug-target interactions efficiently...
  25. ncbi LIGAND database for enzymes, compounds and reactions
    S Goto
    Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 27:377-9. 1999
    ..The LIGAND database can be accessed through the WWW (http://www.genome.ad.jp/dbget/ligand.html) or may be downloaded by anonymous FTP (ftp://kegg.genome.ad. jp/molecules/ligand)...
  26. ncbi KEGG for linking genomes to life and the environment
    Minoru Kanehisa
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan
    Nucleic Acids Res 36:D480-4. 2008
    ..KEGG DRUG contains all approved drugs in the US and Japan, and KEGG DISEASE is a new database linking disease genes, pathways, drugs and diagnostic markers...
  27. ncbi The evolutionary repertoires of the eukaryotic-type ABC transporters in terms of the phylogeny of ATP-binding domains in eukaryotes and prokaryotes
    Yoshinobu Igarashi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University Uji, Kyoto, Japan
    Mol Biol Evol 21:2149-60. 2004
    ....
  28. ncbi ProfilePSTMM: capturing tree-structure motifs in carbohydrate sugar chains
    Kiyoko F Aoki-Kinoshita
    Bioinformatics Center, Institute for Chemical Research, Kyoto University
    Bioinformatics 22:e25-34. 2006
    ..Additionally, we tested it on glycans which are known to be recognized and bound to proteins at various binding affinities, and we show that our results correlate with results published in the literature...
  29. ncbi Application of a new probabilistic model for recognizing complex patterns in glycans
    Kiyoko F Aoki
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, Japan
    Bioinformatics 20:i6-14. 2004
    ..This extension on the usage of PSTMM may be a major step forward for not only the structural analysis of glycans, but it may consequently prove useful for discovering clues into their function...
  30. ncbi Prediction of protein subcellular locations by support vector machines using compositions of amino acids and amino acid pairs
    Keun-Joon Park
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan
    Bioinformatics 19:1656-63. 2003
    ..Results obtained through 5-fold cross-validation tests showed an improvement in prediction accuracy over the algorithm based on the amino acid composition only. This prediction method is available via the Internet...
  31. ncbi KAAS: an automatic genome annotation and pathway reconstruction server
    Yuki Moriya
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 35:W182-5. 2007
    ..The method is based on sequence similarities, bi-directional best hit information and some heuristics, and has achieved a high degree of accuracy when compared with the manually curated KEGG GENES database...
  32. ncbi Using the KEGG database resource
    Kiyoko F Aoki
    Bioinformatics Center, Kyoto University, Japan
    Curr Protoc Bioinformatics . 2005
    ..All of these many protocols enable the user to take advantage of the full breadth of the functionality provided by KEGG...
  33. ncbi LIGAND: chemical database for enzyme reactions
    S Goto
    Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Bioinformatics 14:591-9. 1998
    ..LIGAND chemical database is our attempt to solve these problems, at least for enzymatic reactions...
  34. ncbi LIGAND: chemical database of enzyme reactions
    S Goto
    Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 28:380-2. 2000
    ..The LIGAND database can be accessed through the WWW (http://www.genome.ad.jp/dbget/ligand.html ) or may be downloaded by anonymous FTP (ftp://kegg.genome.ad.jp/molecules/ligand/ )...
  35. ncbi KEGG as a glycome informatics resource
    Kosuke Hashimoto
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan
    Glycobiology 16:63R-70R. 2006
    ..In all the KEGG resources, various objects including KEGG pathways, chemical compounds, as well as carbohydrate structures are commonly represented as graphs, which are widely studied and utilized in the computer science field...
  36. ncbi Mining significant tree patterns in carbohydrate sugar chains
    Kosuke Hashimoto
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji 611 0011, Japan
    Bioinformatics 24:i167-73. 2008
    ..Finding these glycan tree motifs is an important issue, but there have been no computational methods to capture these motifs efficiently...
  37. ncbi Development of a chemical structure comparison method for integrated analysis of chemical and genomic information in the metabolic pathways
    Masahiro Hattori
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan
    J Am Chem Soc 125:11853-65. 2003
    ..Furthermore, it was found that the pathway modules identified by similar compound structures sometimes overlap with the pathway modules identified by genomic contexts, namely, by operon structures of enzyme genes...
  38. ncbi SIMCOMP/SUBCOMP: chemical structure search servers for network analyses
    Masahiro Hattori
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 38:W652-6. 2010
    ..The obtained links to PATHWAY or BRITE databases can be used to interpret as the biological meanings of chemical structures from the viewpoint of the various biological functions including metabolic networks...
  39. ncbi The repertoire of desaturases and elongases reveals fatty acid variations in 56 eukaryotic genomes
    Kosuke Hashimoto
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    J Lipid Res 49:183-91. 2008
    ..This study provides an example of a potent strategy to bridge the gap from genomic knowledge to chemical knowledge...
  40. ncbi The KEGG database
    Minoru Kanehisa
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611-0011, Japan
    Novartis Found Symp 247:91-101; discussion 101-3, 119-28, 244-52. 2002
    ..I will review the current status of KEGG and report on new developments in graph representation and graph computations...
  41. ncbi Generalized reaction patterns for prediction of unknown enzymatic reactions
    Yugo Shimizu
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Genome Inform 20:149-58. 2008
    ..Thus we will be able to define the similarity between enzymatic reactions by using this cluster information...
  42. ncbi Characterization and classification of adverse drug interactions
    Masataka Takarabe
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Genome Inform 22:167-75. 2010
    ..The merged data of drug interactions indicated drug properties that are related to drug interaction mechanisms or symptoms. We investigated the relationships between the drug groups and drug interaction mechanisms or symptoms...
  43. ncbi New amino acid indices based on residue network topology
    Jian Huang
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho Uji, Kyoto 611 0011, Japan
    Genome Inform 18:152-61. 2007
    ..75. It indicates that the network property based amino acid indices can be useful complements to the existing physicochemical property based amino acid indices...
  44. ncbi Analysis of a lipid biosynthesis protein family and phospholipid structural variations
    Michihiro Tanaka
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Genome Inform 22:191-201. 2010
    ..These findings may provide clues to understanding structural variations and distributions of glycerophospholipids in different organisms...
  45. ncbi Systematic survey for novel types of prokaryotic retroelements based on gene neighborhood and protein architecture
    Kenji K Kojima
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan
    Mol Biol Evol 25:1395-404. 2008
    ..In addition, we found 8 RT genes were associated with clustered regularly interspaced short palindrome repeats (CRISPRs) of the CRISPR-Cas system. These RT genes are likely to work in immunity against RNA phages via cDNA synthesis...
  46. ncbi Tools for investigating mechanisms of antigenic variation: new extensions to varDB
    C Nelson Hayes
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Genome Inform 23:46-59. 2009
    ..We believe that the new sequence analysis tools will improve the usefulness and range of varDB...
  47. ncbi E-zyme: predicting potential EC numbers from the chemical transformation pattern of substrate-product pairs
    Yoshihiro Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan
    Bioinformatics 25:i179-86. 2009
    ..There are numerous reactions known to be present in various pathways but without any official EC numbers, most of which have no hope to be given ones because of the lack of the published articles on enzyme assays...
  48. ncbi Network analysis of adverse drug interactions
    Masataka Takarabe
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto, Japan
    Genome Inform 20:252-9. 2008
    ..To characterize other interactions without interaction factors, we used the ATC classification system and found an association between interaction mechanisms and pharmacological/chemical subgroups...
  49. ncbi varDB: a pathogen-specific sequence database of protein families involved in antigenic variation
    C Nelson Hayes
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Bioinformatics 24:2564-5. 2008
    ..AVAILABILITY: varDB is freely accessible at http://www.vardb.org/..
  50. ncbi [Integrated drug information resource]
    Minoru Kanehisa
    Tanpakushitsu Kakusan Koso 52:1486-91. 2007
  51. ncbi Predicting B cell epitope residues with network topology based amino acid indices
    Jian Huang
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho Uji, Kyoto 611 0011, Japan
    Genome Inform 19:40-9. 2007
    ..It is suggested that the performance in surface residue prediction might form a theoretical upper limit for the performance of B cell epitope residue prediction methods...
  52. ncbi Analysis of common substructures of metabolic compounds within the different organism groups
    Ai Muto
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Genome Inform 18:299-307. 2007
    ..These results will help us to better comprehend the architecture of metabolic pathways and the relationships between organisms...
  53. ncbi KEGG Atlas mapping for global analysis of metabolic pathways
    Shujiro Okuda
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 36:W423-6. 2008
    ..Once chemical compounds are converted to the C number identifiers in KEGG, metabolomics data can also be displayed in the global map. KEGG Atlas is available at http://www.genome.jp/kegg/atlas/...
  54. ncbi An improved scoring scheme for predicting glycan structures from gene expression data
    Akitsugu Suga
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Genome Inform 18:237-46. 2007
    ....
  55. ncbi The repertoire of desaturases for unsaturated fatty acid synthesis in 397 genomes
    Kosuke Hashimoto
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Genome Inform 17:173-83. 2006
    ..In this study, we performed a systematic analysis of fatty acid desaturases found in the genomic data of 397 organisms. We obtained a set of desaturases clustered by regioselectivity using a hierarchal clustering analysis...
  56. ncbi Extraction of organism groups from phylogenetic profiles using independent component analysis
    Yoshihiro Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Genome Inform 13:61-70. 2002
    ..The 9 extracted components out of 18 predefined components well represented the organism groups as categorized in KEGG. Furthermore, we performed the cluster analysis and obtained the hierarchy of organism groups...
  57. ncbi The inference of protein-protein interactions by co-evolutionary analysis is improved by excluding the information about the phylogenetic relationships
    Tetsuya Sato
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 21:3482-9. 2005
    ..The incentive of our study was to solve this problem by improving the method of extracting the co-evolutionary information regarding the protein pairs...
  58. ncbi Supervised enzyme network inference from the integration of genomic data and chemical information
    Yoshihiro Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 21:i468-77. 2005
    ..There is, therefore, an incentive to develop methods to reconstruct the unknown parts of the metabolic network and to identify genes coding for missing enzymes...
  59. ncbi LIGAND: database of chemical compounds and reactions in biological pathways
    Susumu Goto
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 30:402-4. 2002
    ..genome.ad.jp/ligand/). LIGAND may be also downloaded by anonymous FTP (ftp://ftp.genome.ad.jp/pub/kegg/ligand/)...
  60. ncbi Clustering of database sequences for fast homology search using upper bounds on alignment score
    Masumi Itoh
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Genome Inform 15:93-104. 2004
    ..The results suggest that our method is efficient for redundant databases that include multiple closely related species...
  61. ncbi Extraction of species-specific glycan substructures
    Yoshiyuki Hizukuri
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Genome Inform 15:69-81. 2004
    ..We confirmed that the characteristic substructures extracted by our method correspond to the substructures which are known as the species-specific sugar chain of gamma-glutamyltranspeptidases in the kidney...
  62. ncbi Heuristics for chemical compound matching
    Masahiro Hattori
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Genome Inform 14:144-53. 2003
    ..Finally, we showed the effectiveness of our heuristics for compound pairs along metabolic pathways...
  63. ncbi Fast and accurate database homology search using upper bounds of local alignment scores
    Masumi Itoh
    Bioinformatics Center, Institute for Chemical Research, Kyoto University Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 21:912-21. 2005
    ..Results of computational experiments suggest that the method is dozens of times faster than SSEARCH if genome sequence data of closely related species are available...
  64. ncbi KCaM (KEGG Carbohydrate Matcher): a software tool for analyzing the structures of carbohydrate sugar chains
    Kiyoko F Aoki
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 32:W267-72. 2004
    ..Analogously to BLAST, users are thus able to compare glycan structures of interest with glycans from different glycan databases using a variety of tree-alignment options. KCaM is currently available at http://glycan.genome.ad.jp...
  65. ncbi A quadratic programming approach for decomposing steady-state metabolic flux distributions onto elementary modes
    Jean Marc Schwartz
    Bioinformatics Center, Institute for Chemical Research, Kyoto University Uji, Kyoto, Japan
    Bioinformatics 21:ii204-5. 2005
    ..However, little understanding has been achieved so far in how individual elementary modes contribute to the reconstruction of actual physiological flux distributions...
  66. ncbi Conservation of gene co-regulation between two prokaryotes: Bacillus subtilis and Escherichia coli
    Shujiro Okuda
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Genome Inform 16:116-24. 2005
    ..As a result, we also found that many conserved co-regulated gene pairs share the same functions. These observations would help to predict gene co-regulation and protein functions...
  67. ncbi Identification of metabolic units induced by environmental signals
    Jose C Nacher
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji Kyoto 611 0011, Japan
    Bioinformatics 22:e375-83. 2006
    ..They reveal significant discrepancies from random networks, and in particular exhibit a high connectivity, allowing them to be mapped back to complete metabolic routes...
  68. ncbi Comprehensive analysis and prediction of synthetic lethality using subcellular locations
    Takuji Yamada
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Genome Inform 16:150-8. 2005
    ..The prediction is based on the hierarchical aspect model (HAM) which learns from a data set of cellular location to estimate a likelihood value indicating the synthetic lethality between genes...
  69. ncbi Autoimmune diseases and peptide variations
    Wataru Honda
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho Uji, Kyoto 611 0011, Japan
    Genome Inform 16:272-80. 2005
    ..This result supports the fact that viral infection is a speculative cause of the disease in some subjects...
  70. ncbi Utilizing evolutionary information and gene expression data for estimating gene networks with bayesian network models
    Yoshinori Tamada
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto, 611 0011, Japan
    J Bioinform Comput Biol 3:1295-313. 2005
    ..Supplementary information is available at http://bonsai.ims.u-tokyo.ac.jp/~tamada/bayesnet/...
  71. ncbi ODB: a database of operons accumulating known operons across multiple genomes
    Shujiro Okuda
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 34:D358-62. 2006
    ..In addition, it provides an operon prediction tool, which make the system useful for both bioinformatics researchers and experimental biologists. Our database is accessible at http://odb.kuicr.kyoto-u.ac.jp/...
  72. ncbi Prediction of missing enzyme genes in a bacterial metabolic network. Reconstruction of the lysine-degradation pathway of Pseudomonas aeruginosa
    Yoshihiro Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Japan
    FEBS J 274:2262-73. 2007
    ..We observed that the predicted gene products catalyzed the expected reactions; no activity was seen when both gene products were omitted from the reaction...
  73. ncbi Partial correlation coefficient between distance matrices as a new indicator of protein-protein interactions
    Tetsuya Sato
    Bioinformatics Center, Institute for Chemical Research, Kyoto University Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 22:2488-92. 2006
    ..In this study, we introduced a partial correlation coefficient as a new measure for the degree of co-evolution between proteins, and proposed its use to predict protein-protein interactions...
  74. ncbi Extracting sequence motifs and the phylogenetic features of SNARE-dependent membrane traffic
    Akiyasu C Yoshizawa
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Traffic 7:1104-18. 2006
    ....
  75. ncbi Extraction of correlated gene clusters from multiple genomic data by generalized kernel canonical correlation analysis
    Y Yamanishi
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Bioinformatics 19:i323-30. 2003
    ....
  76. ncbi AAindex: amino acid index database
    S Kawashima
    Institute for Chemical Research, Kyoto University, Uji, Kyoto 611 0011, Japan
    Nucleic Acids Res 28:374. 2000
    ..The database may be accessed through the DBGET/LinkDB system at GenomeNet (http://www. genome.ad.jp/aaindex/ ) or may be downloaded by anonymous FTP (ftp://ftp.genome.ad.jp/db/genomenet/aaindex/ )...
  77. ncbi The role of log-normal dynamics in the evolution of biochemical pathways
    J C Nacher
    Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611 0011, Japan
    Biosystems 83:26-37. 2006
    ..e., gamma > or = 3/2). Finally, our model is also applied to the chemical compounds network of biochemical pathways and the Internet network...
  78. ncbi Large-scale cDNA analysis of the maternal genetic information in the egg of Halocynthia roretzi for a gene expression catalog of ascidian development
    K W Makabe
    Department of Zoology, Graduate School of Science, Kyoto University, Kyoto 606 8502, Japan
    Development 128:2555-67. 2001
    ..9% of the clones were exclusively maternal, while 40.6% of the maternal clones showed expression in the later stages. This study provides global insights about the genes expressed during early development...
  79. ncbi Identification of a new cryptochrome class. Structure, function, and evolution
    Ronald Brudler
    Department of Molecular Biology and Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA 92037, USA
    Mol Cell 11:59-67. 2003
    ..Whole genome transcriptional profiling together with experimental confirmation of DNA binding indicated that Synechocystis cryptochrome DASH functions as a transcriptional repressor...
  80. ncbi Extracting active pathways from gene expression data
    Jean Philippe Vert
    Centre de Géostatistique, Ecole des Mines de Paris, Fontainebleau Cedex, France
    Bioinformatics 19:ii238-44. 2003
    ..Searching for regularities in the set of gene expression profiles with respect to the topology of this gene network is a way to automatically extract active pathways and their associated patterns of activity...
  81. ncbi Screening for the target gene of cyanobacterial cAMP receptor protein SYCRP1
    Hidehisa Yoshimura
    Department of Life Sciences, Graduate School of Arts and Sciences, The University of Tokyo, Komaba, Meguro, Tokyo 153-8902, Japan
    Mol Microbiol 43:843-53. 2002
    ..It was concluded that SYCRP1 regulates the expression of the slr1667 gene directly by binding to a specific site in its promoter...
  82. ncbi A two-component Mn2+-sensing system negatively regulates expression of the mntCAB operon in Synechocystis
    Katsushi Yamaguchi
    Department of Regulation Biology, National Institute for Basic Biology, Okazaki 444-8585, Japan
    Plant Cell 14:2901-13. 2002
    ..At low concentrations of Mn(2+) ions, ManS does not generate a signal, with resulting inactivation of ManR and subsequent expression of the mntCAB operon...
  83. ncbi Using protein motif combinations to update KEGG pathway maps and orthologue tables
    Frederic Nikitin
    Geneva Bioinformatics, 25 avenue de Champel, 1206 Geneva, Switzerland
    Genome Inform 15:266-75. 2004
    ..It is shown how these results can be used to update KEGG pathways and orthologue tables...
  84. ncbi Comparative pair-wise domain-combinations for screening the clade specific domain-architectures in metazoan genomes
    Shuichi Kawashima
    Human Genome Center, Institute of Medical Science, University of Tokyo, 4 6 1 Shirokanedai, Minato ku, Tokyo 108 8639, Japan
    Genome Inform 19:50-60. 2007
    ..Such a small number of ecdysozoan-specific domain-combinations is consistent with the extensive gene-losses through the evolution of ecdysozoans...
  85. ncbi Global analysis of circadian expression in the cyanobacterium Synechocystis sp. strain PCC 6803
    Ken-ichi Kucho
    Center for Gene Research, Nagoya University, Furo-cho, Chikusa-ku, Nagoya 464-8602, Japan
    J Bacteriol 187:2190-9. 2005
    ..Our findings provided critical insights into the importance of the circadian clock on cellular physiology and the mechanism of clock-controlled gene regulation...
  86. ncbi Positive regulation of sugar catabolic pathways in the cyanobacterium Synechocystis sp. PCC 6803 by the group 2 sigma factor sigE
    Takashi Osanai
    Institute of Molecular and Cellular Biosciences, University of Tokyo, 1-1-1 Yayoi, Bunkyo-ku, Tokyo 113-0032, Japan
    J Biol Chem 280:30653-9. 2005
    ..Moreover, it was unable to proliferate under the light-activated heterotrophic growth conditions. These results indicate that SigE functions in the transcriptional activation of sugar catabolic pathways in Synechocystis sp. PCC 6803...
  87. ncbi VisANT 3.0: new modules for pathway visualization, editing, prediction and construction
    Zhenjun Hu
    Center for Advanced Genomic Technology, Boston University, Boston, MA 02215, USA
    Nucleic Acids Res 35:W625-32. 2007
    ..Pathways in the format of VisML can be securely shared within an interested group or published online using a simple Web link. VisANT is freely available at http://visant.bu.edu...
  88. ncbi Towards zoomable multidimensional maps of the cell
    Zhenjun Hu
    Program in Bioinformatics and Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, USA
    Nat Biotechnol 25:547-54. 2007
    ....