Kiyoko F Aoki-Kinoshita

Publications of Kiyoko F Aoki-Kinoshita

• Identification of proteasome components required for apical localization of chaoptin using functional genomics.

  Authors: Hiroyuki Yano, Miki Yamamoto-Hino, Wakae Awano, Kiyoko F Aoki-Kinoshita, Kayoko Tsuda-Sakurai, Hideyuki Okano, Satoshi Goto

  Journal of neurogenetics. 03/2012; 26(1):53-63.

  Abstract: the distinct localization of membrane proteins with regard to cell polarity is crucial for the structure and function of various organs in multicellular organisms. However, the moleculesAbstract: the distinct localization of membrane proteins with regard to cell polarity is crucial for the structure and function of various organs in multicellular organisms. However, the molecules and mechanisms that regulate protein localization to particular subcellular domains are still largely unknown. To identify the genes involved in regulation of protein localization, the authors performed a large-scale screen using a Drosophila RNA interference (RNAi) library, by which Drosophila genes could be knocked down in a tissue- and stage-specific manner. Drosophila photoreceptor cells have a morphologically distinct apicobasal polarity, along which Chaoptin (Chp), a glycosylphosphatidylinositol (GPI)-anchored membrane protein, and the Na (+) , K(+) -ATPase are localized to the apical and basolateral domains, respectively. By examining the subcellular localization of these proteins, the authors identified 106 genes whose knockdown resulted in mislocalization of Chp and Na(+) , K(+) -ATPase. Gene ontology analysis revealed that the knockdown of proteasome components resulted in mislocalization of Chp to the basolateral plasma membrane. These results suggest that the proteasome is involved, directly or indirectly, in selective localization of Chp to the apical plasma membrane of Drosophila photoreceptor cells.

• The 2nd DBCLS BioHackathon: interoperable bioinformatics Web services for integrated applications.

  Authors: Toshiaki Katayama, Mark D Wilkinson, Rutger Vos, Takeshi Kawashima, Shuichi Kawashima, Mitsuteru Nakao, Yasunori Yamamoto, Hong-Woo Chun, Atsuko Yamaguchi, Shin Kawano [......] Martin Senger, Jessica Severin, Yasumasa Shigemoto, Hideaki Sugawara, James Taylor, Oswaldo Trelles, Chisato Yamasaki, Riu Yamashita, Noriyuki Satoh, Toshihisa Takagi

  Journal of biomedical semantics. 08/2011; 2:4.

  ABSTRACT: The interaction between biological researchers and the bioinformatics tools they use is still hampered by incomplete interoperability between such tools. To ensure interoperabilityABSTRACT: The interaction between biological researchers and the bioinformatics tools they use is still hampered by incomplete interoperability between such tools. To ensure interoperability initiatives are effectively deployed, end-user applications need to be aware of, and support, best practices and standards. Here, we report on an initiative in which software developers and genome biologists came together to explore and raise awareness of these issues: BioHackathon 2009. Developers in attendance came from diverse backgrounds, with experts in Web services, workflow tools, text mining and visualization. Genome biologists provided expertise and exemplar data from the domains of sequence and pathway analysis and glyco-informatics. One goal of the meeting was to evaluate the ability to address real world use cases in these domains using the tools that the developers represented. This resulted in i) a workflow to annotate 100,000 sequences from an invertebrate species; ii) an integrated system for analysis of the transcription factor binding sites (TFBSs) enriched based on differential gene expression data obtained from a microarray experiment; iii) a workflow to enumerate putative physical protein interactions among enzymes in a metabolic pathway using protein structure data; iv) a workflow to analyze glyco-gene-related diseases by searching for human homologs of glyco-genes in other species, such as fruit flies, and retrieving their phenotype-annotated SNPs. Beyond deriving prototype solutions for each use-case, a second major purpose of the BioHackathon was to highlight areas of insufficiency. We discuss the issues raised by our exploration of the problem/solution space, concluding that there are still problems with the way Web services are modeled and annotated, including: i) the absence of several useful data or analysis functions in the Web service "space"; ii) the lack of documentation of methods; iii) lack of compliance with the SOAP/WSDL specification among and between various programming-language libraries; and iv) incompatibility between various bioinformatics data formats. Although it was still difficult to solve real world problems posed to the developers by the biological researchers in attendance because of these problems, we note the promise of addressing these issues within a semantic framework.

• The RINGS resource for glycome informatics analysis and data mining on the Web.

  Authors: Yukie Akune, Masae Hosoda, Sakiko Kaiya, Daisuke Shinmachi, Kiyoko F Aoki-Kinoshita

  Omics : a journal of integrative biology. 08/2010; 14(4):475-86.

  In the bioinformatics field, many computer algorithmic and data mining technologies have been developed for gene prediction, protein-protein interaction analysis, sequence analysis, and proteinIn the bioinformatics field, many computer algorithmic and data mining technologies have been developed for gene prediction, protein-protein interaction analysis, sequence analysis, and protein folding predictions, to name a few. This kind of research has branched off from the genomics field, creating the transcriptomics, proteomics, metabolomics, and glycomics research areas in the postgenomic age. In the glycomics field, given the complexity of glycan structures with their branches of monosaccharides in various conformations, new data mining and algorithmic methods have been developed in an attempt to gain a better understanding of glycans. However, these methods have not all been implemented as tools such that the glycobiology community may utilize them in their research. Thus, we have developed RINGS (Resource for INformatics of Glycomes at Soka) as a freely available Web resource for glycobiologists to analyze their data using the latest data mining and algorithmic techniques. It provides a number of tools including a 2D glycan drawing and querying interface called DrawRINGS, a Glycan Pathway Predictor (GPP) tool for dynamically computing the N-glycan biosynthesis pathway from a given glycan structure, and data mining tools Glycan Miner Tool and Profile PSTMM. These tools and other utilities provided by RINGS will be described. The URL for RINGS is http://rings.t.soka.ac.jp/.

• Identification of genes required for neural-specific glycosylation using functional genomics.

  Authors: Miki Yamamoto-Hino, Yoshimi Kanie, Wakae Awano, Kiyoko F Aoki-Kinoshita, Hiroyuki Yano, Shoko Nishihara, Hideyuki Okano, Ryu Ueda, Osamu Kanie, Satoshi Goto

  PLoS genetics. 01/2010; 6(12):e1001254.

  Glycosylation plays crucial regulatory roles in various biological processes such as development, immunity, and neural functions. For example, α1,3-fucosylation, the addition of a fucose moietyGlycosylation plays crucial regulatory roles in various biological processes such as development, immunity, and neural functions. For example, α1,3-fucosylation, the addition of a fucose moiety abundant in Drosophila neural cells, is essential for neural development, function, and behavior. However, it remains largely unknown how neural-specific α1,3-fucosylation is regulated. In the present study, we searched for genes involved in the glycosylation of a neural-specific protein using a Drosophila RNAi library. We obtained 109 genes affecting glycosylation that clustered into nine functional groups. Among them, members of the RNA regulation group were enriched by a secondary screen that identified genes specifically regulating α1,3-fucosylation. Further analyses revealed that an RNA-binding protein, second mitotic wave missing (Swm), upregulates expression of the neural-specific glycosyltransferase FucTA and facilitates its mRNA export from the nucleus. This first large-scale genetic screen for glycosylation-related genes has revealed novel regulation of fucTA mRNA in neural cells.

• The DBCLS BioHackathon: standardization and interoperability for bioinformatics web services and workflows. The DBCLS BioHackathon Consortium*.

  Authors: Toshiaki Katayama, Kazuharu Arakawa, Mitsuteru Nakao, Keiichiro Ono, Kiyoko F Aoki-Kinoshita, Yasunori Yamamoto, Atsuko Yamaguchi, Shuichi Kawashima, Hong-Woo Chun, Jan Aerts [......] Daron M Standley, Hideaki Sugawara, Toshiyuki Tashiro, Oswaldo Trelles, Rutger A Vos, Mark D Wilkinson, William York, Christian M Zmasek, Kiyoshi Asai, Toshihisa Takagi

  Journal of biomedical semantics. 01/2010; 1(1):8.

  Web services have become a key technology for bioinformatics, since life science databases are globally decentralized and the exponential increase in the amount of available data demands forWeb services have become a key technology for bioinformatics, since life science databases are globally decentralized and the exponential increase in the amount of available data demands for efficient systems without the need to transfer entire databases for every step of an analysis. However, various incompatibilities among database resources and analysis services make it difficult to connect and integrate these into interoperable workflows. To resolve this situation, we invited domain specialists from web service providers, client software developers, Open Bio* projects, the BioMoby project and researchers of emerging areas where a standard exchange data format is not well established, for an intensive collaboration entitled the BioHackathon 2008. The meeting was hosted by the Database Center for Life Science (DBCLS) and Computational Biology Research Center (CBRC) and was held in Tokyo from February 11th to 15th, 2008. In this report we highlight the work accomplished and the common issues arisen from this event, including the standardization of data exchange formats and services in the emerging fields of glycoinformatics, biological interaction networks, text mining, and phyloinformatics. In addition, common shared object development based on BioSQL, as well as technical challenges in large data management, asynchronous services, and security are discussed. Consequently, we improved interoperability of web services in several fields, however, further cooperation among major database centers and continued collaborative efforts between service providers and software developers are still necessary for an effective advance in bioinformatics web service technologies.

• [An introduction to glycome informatics]

  Authors: Kiyoko F Aoki-Kinoshita

  Seikagaku. The Journal of Japanese Biochemical Society. 12/2008; 80(11):1038-41.

• An introduction to bioinformatics for glycomics research.

  Authors: Kiyoko F Aoki-Kinoshita

  PLoS computational biology. 06/2008; 4(5):e1000075.

• A new efficient probabilistic model for mining labeled ordered trees applied to glycobiology.

  Authors: Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhisa Ueda, Minoru Kanehisa, Hiroshi Mamitsuka

  TKDD. 01/2008; 2.

• An Efficient Unordered Tree Kernel and Its Application to Glycan Classification.

  Authors: Tetsuji Kuboyama, Kouichi Hirata, Kiyoko F. Aoki-Kinoshita

  Advances in Knowledge Discovery and Data Mining, 12th Pacific-Asia Conference, PAKDD 2008, Osaka, Japan, May 20-23, 2008 Proceedings; 01/2008

• Gene annotation and pathway mapping in KEGG.

  Authors: Kiyoko F Aoki-Kinoshita, Minoru Kanehisa

  Methods in molecular biology (Clifton, N.J.). 02/2007; 396:71-91.

  KEGG is a database resource (http://www.genome.jp/kegg/) that provides all knowledge about genomes and their relationships to biological systems such as cells and whole organisms as well as theirKEGG is a database resource (http://www.genome.jp/kegg/) that provides all knowledge about genomes and their relationships to biological systems such as cells and whole organisms as well as their interactions with the environment. KEGG is categorized in terms of building blocks in the genomic space, known as KEGG GENES, the chemical space, KEGG LIGAND, as well as wiring diagrams of interaction and reaction networks, known as KEGG PATHWAY. A fourth database called KEGG BRITE was also recently incorporated to provide computerized annotations and pathway reconstruction based on the current KEGG knowledgebase. KEGG BRITE contains KEGG Orthology (KO), a classification of ortholog and paralog groups based on highly confident sequence similarity scores, and the reaction classification system for biochemical reaction classification, along with other classifications for compounds and drugs. BRITE is also the basis for the KEGG Automatic Annotation Server (KAAS), which automatically annotates a given set of genes and correspondingly generates pathway maps. This chapter introduces KEGG and its various tools for genomic analyses, focusing on the usage of the KEGG GENES, PATHWAY, and BRITE resources and the KAAS tool (see Note 1).

• Bioinformatics approaches in glycomics and drug discovery.

  Authors: Kiyoko F Aoki-Kinoshita, Minoru Kanehisa

  Current opinion in molecular therapeutics. 01/2007; 8(6):514-20.

  Within the field of bioinformatics, interest in glycan structures has increased steadily since the start of the 21st century, with several databases worldwide accumulating data. The most notableWithin the field of bioinformatics, interest in glycan structures has increased steadily since the start of the 21st century, with several databases worldwide accumulating data. The most notable publicly available databases are KEGG GLYCAN in Japan, glycoSCIENCES.de in Germany and that of the Consortium for Functional Glycomics in the US. With this increasing abundance of data, there are greater possibilities for applying tree-based models and algorithms to glycan structure data. Research in this area of glycome informatics is reviewed. The combination of these datasets and informatics techniques to enable extraction of the most important (and perhaps the most interesting) information--the links between glycans and diseases, and the identification of biomarkers and drug targets--is discussed.

• Improving MHC binding peptide prediction by incorporating binding data of auxiliary MHC molecules.

  Authors: Shanfeng Zhu, Keiko Udaka, John Sidney, Alessandro Sette, Kiyoko F Aoki-Kinoshita, Hiroshi Mamitsuka

  Bioinformatics (Oxford, England). 08/2006; 22(13):1648-55.

  MOTIVATION: Various computational methods have been proposed to tackle the problem of predicting the peptide binding ability for a specific MHC molecule. These methods are based on known bindingMOTIVATION: Various computational methods have been proposed to tackle the problem of predicting the peptide binding ability for a specific MHC molecule. These methods are based on known binding peptide sequences. However, current available peptide databases do not have very abundant amounts of examples and are highly redundant. Existing studies show that MHC molecules can be classified into supertypes in terms of peptide-binding specificities. Therefore, we first give a method for reducing the redundancy in a given dataset based on information entropy, then present a novel approach for prediction by learning a predictive model from a dataset of binders for not only the molecule of interest but also for other MHC molecules. RESULTS: We experimented on the HLA-A family with the binding nonamers of A1 supertype (HLA-A*0101, A*2601, A*2902, A*3002), A2 supertype (A*0201, A*0202, A*0203, A*0206, A*6802), A3 supertype (A*0301, A*1101, A*3101, A*3301, A*6801) and A24 supertype (A*2301 and A*2402), whose data were collected from six publicly available peptide databases and two private sources. The results show that our approach significantly improves the prediction accuracy of peptides that bind a specific HLA molecule when we combine binding data of HLA molecules in the same supertype. Our approach can thus be used to help find new binders for MHC molecules.

• ProfilePSTMM: capturing tree-structure motifs in carbohydrate sugar chains.

  Authors: Kiyoko F Aoki-Kinoshita, Nobuhisa Ueda, Hiroshi Mamitsuka, Minoru Kanehisa

  Bioinformatics (Oxford, England). 08/2006; 22(14):e25-34.

  MOTIVATION: Carbohydrate sugar chains, or glycans, are considered the third major class of biomolecules after DNA and proteins. They consist of branching monosaccharides, starting from a singleMOTIVATION: Carbohydrate sugar chains, or glycans, are considered the third major class of biomolecules after DNA and proteins. They consist of branching monosaccharides, starting from a single monosaccharide. They are extremely vital to the development and functioning of multicellular organisms because they are recognized by various proteins to allow them to perform specific functions. Our motivation is to study this recognition mechanism using informatics techniques from the data available. Previously, we introduced a probabilistic sibling-dependent tree Markov model (PSTMM), which we showed could be efficiently trained on sibling-dependent tree structures and return the most likely state paths. However, it had some limitations in that the extra dependency between siblings caused overfitting problems. The retrieval of the patterns from the trained model also involved manually extracting the patterns from the most likely state paths. Thus we introduce a profilePSTMM model which avoids these problems, incorporating a novel concept of different types of state transitions to handle parent-child and sibling dependencies differently. RESULTS: Our new algorithms are more efficient and able to extract the patterns more easily. We tested the profilePSTMM model on both synthetic (controlled) data as well as glycan data from the KEGG GLYCAN database. 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.

• KEGG as a glycome informatics resource.

  Authors: Kosuke Hashimoto, Susumu Goto, Shin Kawano, Kiyoko F Aoki-Kinoshita, Nobuhisa Ueda, Masami Hamajima, Toshisuke Kawasaki, Minoru Kanehisa

  Glycobiology. 06/2006; 16(5):63R-70R.

  Bioinformatics approaches to carbohydrate research have recently begun using large amounts of protein and carbohydrate data. In this field called glycome informatics, the foremost necessity is aBioinformatics approaches to carbohydrate research have recently begun using large amounts of protein and carbohydrate data. In this field called glycome informatics, the foremost necessity is a comprehensive resource for genome-scale bioinformatics analysis of glycan data. Although the accumulation of experimental data may be useful as a reference of biological and biochemical information on carbohydrates, this is insufficient for bioinformatics analysis. Thus, we have developed a glycome informatics resource (http://www.genome.jp/kegg/glycan/) in KEGG (Kyoto Encyclopedia of Genes and Genomes), an integrated knowledge base of protein networks, genomic information, and chemical information. This review describes three noteworthy features: (1) GLYCAN, a database of carbohydrate structures; (2) glycan-related pathways; and (3) Composite Structure Map (CSM), a map illustrating all possible variations of carbohydrate structures within organisms. GLYCAN includes two useful tools: an intuitive drawing tool called KegDraw, and an efficient glycan search and alignment tool called KEGG Carbohydrate Matcher (KCaM). KEGG's glycan biosynthesis and metabolism pathways, integrating carbohydrate structures, proteins, and reactions, are also a pivotal resource. CSM is constructed as a bridge between carbohydrate functions and structures. CSM is able to display, for example, expression data of glycosyltransferases in a compact manner. 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.

• A gram distribution kernel applied to glycan classification and motif extraction.

  Authors: Tetsuji Kuboyama, Kouichi Hirata, Kiyoko F Aoki-Kinoshita, Hisashi Kashima, Hiroshi Yasuda

  Genome informatics. International Conference on Genome Informatics. 02/2006; 17(2):25-34.

  We propose a novel general-purpose tree kernel and apply it to glycan structure analysis. Our kernel measures the similarity between two labeled trees by counting the number of common q-lengthWe propose a novel general-purpose tree kernel and apply it to glycan structure analysis. Our kernel measures the similarity between two labeled trees by counting the number of common q-length substrings (tree q-grams) embedded in the trees for all possible lengths q. We apply our tree kernel using a support vector machine (SVM) to classification and specific feature extraction from glycan structure data. Our results show that our kernel outperforms the layered trimer kernel of Hizukuri et al. which is well tailored to glycan data while we do not adjust our kernel to glycan-specific properties. In addition, we extract specific features from various types of glycan data using our trained SVM. The results show that our kernel is more flexible and capable of finding a wider variety of substructures from glycan data.

• From genomics to chemical genomics: new developments in KEGG.

  Authors: Minoru Kanehisa, Susumu Goto, Masahiro Hattori, Kiyoko F Aoki-Kinoshita, Masumi Itoh, Shuichi Kawashima, Toshiaki Katayama, Michihiro Araki, Mika Hirakawa

  Nucleic acids research. 02/2006; 34(Database issue):D354-7.

  The increasing amount of genomic and molecular information is the basis for understanding higher-order biological systems, such as the cell and the organism, and their interactions with theThe increasing amount of genomic and molecular information is the basis for understanding higher-order biological systems, such as the cell and the organism, and their interactions with the environment, as well as for medical, industrial and other practical applications. The KEGG resource (http://www.genome.jp/kegg/) provides a reference knowledge base for linking genomes to biological systems, categorized as building blocks in the genomic space (KEGG GENES) and the chemical space (KEGG LIGAND), and wiring diagrams of interaction networks and reaction networks (KEGG PATHWAY). A fourth component, KEGG BRITE, has been formally added to the KEGG suite of databases. This reflects our attempt to computerize functional interpretations as part of the pathway reconstruction process based on the hierarchically structured knowledge about the genomic, chemical and network spaces. In accordance with the new chemical genomics initiatives, the scope of KEGG LIGAND has been significantly expanded to cover both endogenous and exogenous molecules. Specifically, RPAIR contains curated chemical structure transformation patterns extracted from known enzymatic reactions, which would enable analysis of genome-environment interactions, such as the prediction of new reactions and new enzyme genes that would degrade new environmental compounds. Additionally, drug information is now stored separately and linked to new KEGG DRUG structure maps.

• A new efficient probabilistic model for mining labeled ordered trees.

  Authors: Kosuke Hashimoto, Kiyoko F. Aoki-Kinoshita, Nobuhisa Ueda, Minoru Kanehisa, Hiroshi Mamitsuka

  Proceedings of the Twelfth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Philadelphia, PA, USA, August 20-23, 2006; 01/2006

• A 6-Approximation Algorithm for Computing Smallest Common AoN-Supertree with Application to the Reconstruction of Glycan Trees.

  Authors: Kiyoko F. Aoki-Kinoshita, Minoru Kanehisa, Ming-Yang Kao, Xiang-Yang Li, Weizhao Wang

  Algorithms and Computation, 17th International Symposium, ISAAC 2006, Kolkata, India, December 18-20, 2006, Proceedings; 01/2006

• A global representation of the carbohydrate structures: a tool for the analysis of glycan.

  Authors: Kosuke Hashimoto, Shin Kawano, Susumu Goto, Kiyoko F Aoki-Kinoshita, Masayuki Kawashima, Minoru Kanehisa

  Genome informatics. International Conference on Genome Informatics. 02/2005; 16(1):214-22.

  Glycan resources have been developed of late, such as carbohydrate databases, analysis tools, and algorithms for analysis of carbohydrate features. With this background, bioinformatics approaches toGlycan resources have been developed of late, such as carbohydrate databases, analysis tools, and algorithms for analysis of carbohydrate features. With this background, bioinformatics approaches to carbohydrate research have recently begun using a large amount of protein and carbohydrate data. This paper introduces one of these projects that elucidates the range of carbohydrate structures. In this study, the variety of carbohydrate structures have been enumerated in a global tree structure called variation trees, using the KEGG GLYCAN database, which is a public-domain glycan resource for bioinformatics analysis. Additionally, a glycosyltransferase mapping list of glycosyltransferases and their catalyzing glycosidic linkages was constructed. From this, we present the composite structure map (CSM), which is a structural variation map integrating its variation trees and glycosyltransferase map list. CSM is able to display, for example, expression data of glycosyltransferases in a compact manner, illustrating its versatility as a new bioinformatics resource and tool capable of analyzing carbohydrate structures on a global scale. These resources are available at http://www.genome.jp/kegg/glycan/.

• A Probabilistic Model for Mining Labeled Ordered Trees: Capturing Patterns in Carbohydrate Sugar Chains.

  Authors: Nobuhisa Ueda, Kiyoko F. Aoki-Kinoshita, Atsuko Yamaguchi, Tatsuya Akutsu, Hiroshi Mamitsuka

  IEEE Trans. Knowl. Data Eng. 01/2005; 17:1051-1064.