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MBGD: Microbial Genome database for Comparative Analysis Featuring Enhanced Functionality to Characterize Gene and Genome Functions Through Large-scale Orthology Analysis

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Journal of Molecular Biology 2025年第15期437卷 168957页

作者： Uchiyama, Ikuo Mihara, Motohiro Nishide, Hiroyo Chiba, Hirokazu Takayanagi, Masahiko Kawai, Mikihiko Takami, Hideto National Institute for Basic Biology National Institutes of Natural Sciences Okazaki Japan Dynacom Co. Ltd. Kobe Japan Database Center for Life Science Joint Support-Center for Data Science Research Research Organization of Information and Systems Kashiwa Japan Web Brain Co. Ltd. Tokyo Japan Tokyo University of Agriculture and Technology Fuchu Japan Center for Mathematical Science and Advanced Technology Japan Agency for Marine-Earth Science and Technology (JAMSTEC) Yokohama Japan

Microbial Genome database for Comparative Analysis (MBGD) is a comprehensive ortholog database encompassing published complete microbial genomes. The ortholog tables in MBGD are constructed in a hierarchical manner. The top-level ortholog table is now constructed from 1,812 genus-level pan-genomes, 6,268 species-level pan-genomes, and 34,079 genomes in total. To support analyses of newly sequenced genomes, MBGD updates MyMBGD functionality, which offers two analysis modes: assignment mode and clustering mode. Assignment mode rapidly classifies genes in the query genomes into existing MBGD ortholog groups, while clustering mode performs de novo clustering of query genomes using the DomClust program. In assignment mode, users can evaluate the presence of genomic functions, as defined in the KEGG Module database, in each query genome using the Genomaple software and compare the results across multiple genomes. To enhance this analysis, we developed a method to subdivide MBGD ortholog groups as needed to improve cross-references to the KEGG Orthology groups. Another notable feature is the phylogenetic profile search interface, which enables users to specify a set of organisms in which orthologs are present or absent (i.e., a phylogenetic profile), and search for ortholog groups with similar phylogenetic profiles. To construct a phylogenetic profile, users can search organisms by specifying phenotype, environment, taxonomy, or a particular ortholog group. MBGD is available at https://***/. © 2025 The Author(s)

关键词： comparative genomics function prediction microbial genomes ortholog

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Comparison of genotypes and phenotypes for von Willebrand factor gene variants using Japanese genome database

Blood Vessels, Thrombosis & Hemostasis

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Blood Vessels, Thrombosis & Hemostasis 2025年

作者： Takafumi Akimoto Hiroshi Inaba Soichi Ogishima Kazuki Kumada Ayano Mitsuhashi Ryui Miyashita Tomoko Yamaguchi Masato Bingo Yushi Chikasawa Keiko Shinozawa Takeshi Hagiwara Kagehiro Amano Eiichi N. Kodama Ei Kinai Department of Laboratory Medicine Tokyo Medical University Tokyo Japan Department of Informatics for Genomic Medicine Group of Integrated Database Systems Tohoku Medical Megabank Organization Tohoku University Japan Advanced Research Center for Innovations in Next-Generation Medicine Tohoku University Japan Department of Biobank Group of Biobank Tohoku Medical Megabank Organization Tohoku University Japan Department of Infectious disease Graduate School of Medicine International Research Institute of Disaster Science Tohoku Medical Megabank Organization Tohoku University Japan

von Willebrand disease (VWD) is a common inherited bleeding disorder. The aim of this study was to determine the predicted disease states associated with various pathogenic VW factor (VWF) variants and their phenotypes using the largest Japanese whole-genome database. Of the 5,857 VWF gene variants registered in the Japanese Multi-Omics Reference Panel (jMorp), variants with the following criteria were extracted; 1) caused protein abnormalities due to genetic alterations, 2) have already been detected and included in a database, including known association with VWD, and 3) highly-likely pathogenic by in silico analysis. We measured VWF activity, antigen, propeptide, and collagen binding activity in stored plasma samples obtained from heterozygous carriers of the selected variants. A total of 29 VWF variants (26 single nucleotide and 3 small insertions/deletions) were detected and six of these were found in Leiden Open Mutation database. We obtained 43 plasma samples from individuals carrying these 29 variants as heterozygous. For the 43 variant-carriers, their mean age was 43.0 and blood group was type O in 17 (39.5%). Analysis of these plasma samples showed low VWF levels (<50%) in 6 (14.0%). Low VWF levels were found in 2/8 (25%) of the nonsense and 4/31 (12.9%) of the missense variants. Taking into consideration the limitation of using stored plasma samples, analysis of the jMorp indicated that most VWF gene variants with predicted pathogenic potential did not correlate with phenotypic expression. Our results supported incomplete penetrance and variable expressivity of the VWF gene variants.

关键词： Von Willebrand disease Prevalence Pathogenic variant Genotype Phenotype

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Protein Data Bank Japan: Computational Resources for Analysis of Protein Structures

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Journal of Molecular Biology 2025年第15期437卷 169013页

作者： Bekker, Gert-Jan Nagao, Chioko Shirota, Matsuyuki Nakamura, Tsukasa Katayama, Toshiaki Kihara, Daisuke Kinoshita, Kengo Kurisu, Genji Institute for Protein Research Osaka University 3-2 Yamadaoka Osaka Suita 565-0871 Japan Tohoku Medical Megabank Organization Tohoku University Miyagi Sendai 980-8573 Japan Advanced Research Center for Innovations in Next-Generation Medicine Tohoku University Miyagi Sendai 980-8573 Japan of Information Sciences Tohoku University Miyagi Sendai 980-8579 Japan Department of Biological Sciences Purdue University West Lafayette 47907 IN United States Structural Biology Research Center Institute of Material Structure Science High Energy Accelerator Research Organization 1-1 Oho Ibaraki Tsukuba 305-0801 Japan Database Center for Life Science Joint Support-Center for Data Science Research Research Organization of Information and Systems Chiba Kashiwa 277-0871 Japan Department of Computer Science Purdue University West Lafayette 47907 IN United States Protein Research Foundation Ina 4-1-2 Osaka Minoh 562-8686 Japan

Protein Data Bank Japan (PDBj, https://***/) is the Asian hub of three-dimensional macromolecular structure data, and a founding member of the worldwide Protein Data Bank. We have accepted, processed, and distributed experimentally determined biological macromolecular structures for over two decades. Although we collaborate with RCSB PDB and BMRB in the United States, PDBe and EMDB in Europe and recently PDBc in China for our data-in activities, we have developed our own unique services and tools for searching, exploring, visualizing, and analyzing protein structures. We have also developed novel archives for computational data and raw crystal diffraction images. Recently, we introduced the Sequence Navigator Pro service to explore proteins using experimental and computational approaches, which enables experimental structural biologists to increase their insight to help them to design their experimental studies more efficiently. In addition, we also introduced a new UniProt-integrated portal to provide users with a quick overview of their target protein and it shows a recommended structure and integrates data from various internal and external resources. With these new additions, we have enhanced our service portfolio to benefit both experimental as computational structural biologists in their search to interpret protein structures, their dynamics and function. © 2025 The Author(s)

关键词： data archives PDB protein structure sequence analyses UniProt

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Recording provenance of workflow runs with RO-Crate

arXiv

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arXiv 2023年

作者： Leo, Simone Crusoe, Michael R. Rodríguez-Navas, Laura Sirvent, Raül Kanitz, Alexander De Geest, Paul Wittner, Rudolf Pireddu, Luca Garijo, Daniel Fernández, José M. Colonnelli, Iacopo Gallo, Matej Ohta, Tazro Suetake, Hirotaka Capella-Gutierrez, Salvador de Wit, Renske Kinoshita, Bruno P. Soiland-Reyes, Stian CA Pula Italy Vrije Universiteit Amsterdam Amsterdam Netherlands DTL Projects Netherlands Forschungszentrum Jülich Germany Barcelona Supercomputing Center Barcelona Spain Biozentrum University of Basel Basel Switzerland Swiss Institute of Bioinformatics Lausanne Switzerland VIB Data Core Gent Belgium Faculty of Informatics Masaryk University Brno Czech Republic Institute of Computer Science Masaryk University Brno Czech Republic BBMRI-ERIC Graz Austria Ontology Engineering Group Universidad Politécnica de Madrid Madrid Spain Computer Science Department Università degli Studi di Torino Torino Italy Database Center for Life Science Joint Support-Center for Data Science Research Research Organization of Information and Systems Shizuoka Japan Institute for Advanced Academic Research Chiba University Chiba Japan Sator Incorporated Tokyo Japan Department of Computer Science The University of Manchester Manchester United Kingdom Informatics Institute University of Amsterdam Amsterdam Netherlands

Recording the provenance of scientific computation results is key to the support of traceability, reproducibility and quality assessment of data products. Several data models have been explored to address this need, providing representations of workflow plans and their executions as well as means of packaging the resulting information for archiving and sharing. However, existing approaches tend to lack interoperable adoption across workflow management systems. In this work we present Workflow Run RO-Crate, an extension of RO-Crate (Research Object Crate) and *** to capture the provenance of the execution of computational workflows at different levels of granularity and bundle together all their associated objects (inputs, outputs, code, etc.). The model is supported by a diverse, open community that runs regular meetings, discussing development, maintenance and adoption aspects. Workflow Run RO-Crate is already implemented by several workflow management systems, allowing interoperable comparisons between workflow runs from heterogeneous systems. We describe the model, its alignment to standards such as W3C PROV, and its implementation in six workflow systems. Finally, we illustrate the application of Workflow Run RO-Crate in two use cases of machine learning in the digital image analysis domain. © 2023, CC BY.

关键词： Workflow management

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Relational-metric based new-generation network application

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Journal of the National Institute of Information and Communications Technology 2015年第2期62卷 113-118页

作者： Shinkuma, Ryoichi Kasai, Hiroyuki Yamaguchi, Kazuhiro Kyoto University Network Design and Control Japan University of Electro-Communications Media Processing Japan Advanced Technology Development Division Kobe Digital Labo Inc Architecture for Communication Network and Database Systems Japan

The background, the proposed concept and design, and the result of the research and development work on the "relational-metric based new generation network" will be presented. The relational metric technique enables numerically modeling social distance between people, things and places from various types of life-log and sensor data. The integration of this and network virtualization enables us to control 'social distance of information for people' as people desire, which has been validated from experiment results.

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Global, regional, and national sex-specific burden and control of the HIV epidemic, 1990–2019, for 204 countries and territories: the Global Burden of Diseases Study 2019

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The Lancet HIV 2021年第10期8卷 e633-e651页

作者： Jahagirdar, Deepa Walters, Magdalene K. Novotney, Amanda Brewer, Edmond D. Frank, Tahvi D. Carter, Austin Biehl, Molly H. Abbastabar, Hedayat Abhilash, E.S. Abu-Gharbieh, Eman Abu-Raddad, Laith Jamal Adekanmbi, Victor Adeyinka, Daniel Adedayo Adnani, Qorinah Estiningtyas Sakilah Afzal, Saira Aghababaei, Soodabeh Ahinkorah, Bright Opoku Ahmad, Sajjad Ahmadi, Keivan Ahmadi, Sepideh Ahmadpour, Ehsan Ahmed, Muktar Beshir Rashid, Tarik Ahmed Salih, Yusra Ahmed Aklilu, Addis Akram, Tayyaba Akunna, Chisom Joyqueenet Al Hamad, Hanadi Alahdab, Fares Alanezi, Fahad Mashhour Aleksandrova, Ekaterina A. Alene, Kefyalew Addis Ali, Liaqat Alipour, Vahid Almustanyir, Sami Alvis-Guzman, Nelson Ameyaw, Edward Kwabena Amu, Hubert Andrei, Catalina Liliana Andrei, Tudorel Anvari, Davood Arabloo, Jalal Aremu, Olatunde Arulappan, Judie Atnafu, Desta Debalkie Quintanilla, Beatriz Paulina Ayala Ayza, Muluken Altaye Azari, Samad Darshan, B.B. Banach, Maciej Bärnighausen, Till Winfried Barra, Fabio Barrow, Amadou Basu, Sanjay Bazargan-Hejazi, Shahrzad Belay, Habtamu Gebrehana Berheto, Tezera Moshago Bezabhe, Woldesellassie Mequanint Bezabih, Yihienew Mequanint Bhagavathula, Akshaya Srikanth Bhardwaj, Nikha Bhardwaj, Pankaj Bhattacharyya, Krittika Bibi, Sadia Bijani, Ali Bisignano, Catherine Bolarinwa, Obasanjo Afolabi Boloor, Archith Boltaev, Azizbek A. Briko, Nikolay Ivanovich Buonsenso, Danilo Burkart, Katrin Butt, Zahid A. Cao, Chao Charan, Jaykaran Chatterjee, Souranshu Chattu, Soosanna Kumary Chattu, Vijay Kumar Choudhari, Sonali Gajanan Chu, Dinh-Toi Couto, Rosa A.S. Cowden, Richard G. Dachew, Berihun Assefa Dadras, Omid Dagnew, Amare Belachew Dahlawi, Saad M.A. Dai, Xiaochen Dandona, Lalit Dandona, Rakhi das Neves, José Degenhardt, Louisa Demeke, Feleke Mekonnen Desta, Abebaw Alemayehu Deuba, Keshab Dhamnetiya, Deepak Dhungana, Govinda Prasad Dianatinasab, Mostafa Diaz, Daniel Djalalinia, Shirin Doan, Linh Phuong Dorostkar, Fariba Edinur, Hisham Atan Effiong, Andem Eftekharzadeh, Sahar El Sayed Zaki, Maysaa Elayedath, Rajesh Elhadi, Institute for Health Metrics and Evaluation University of Washington Seattle WA United States Department of Health Metrics Sciences School of Medicine University of Washington Seattle WA United States Division of Allergy and Infectious Diseases University of Washington Seattle WA United States Department of Global Health University of Washington Seattle WA United States School of Social Work University of Washington Seattle WA United States Department of Medicine University of Washington Seattle WA United States Vagelos College of Physicians and Surgeones Columbia University Medical Center New York NY United States Division of Data Analytics and Delivery for Impact WHO Geneva Switzerland Advanced Diagnostic and Interventional Radiology Research Centre Tehran University of Medical Sciences Tehran Iran Multiple Sclerosis Research Centre Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Paediatric Chronic Kidney Disease Research Centre Tehran University of Medical Sciences Tehran Iran Department of Psychiatry Tehran University of Medical Sciences Tehran Iran Metabolomics and Genomics Research Centre Tehran University of Medical Sciences Tehran Iran Sina Trauma and Surgery Research Centre Tehran University of Medical Sciences Tehran Iran Research Centre for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Centre Tehran University of Medical Sciences Tehran Iran Department of Botany Sree Narayana Guru College Chelannur Kozhikode India Clinical Sciences Department University of Sharjah Sharjah United Arab Emirates Mass Communication Department University of Sharjah Sharjah United Arab Emirates Department of Health-Care Policy and Research Weill Cornell Medical College in Qatar Doha Qatar Department of Population Medicine Ca

Background: The sustainable development goals (SDGs) aim to end HIV/AIDS as a public health threat by 2030. Understanding the current state of the HIV epidemic and its change over time is essential to this effort. This study assesses the current sex-specific HIV burden in 204 countries and territories and measures progress in the control of the epidemic. Methods: To estimate age-specific and sex-specific trends in 48 of 204 countries, we extended the Estimation and Projection Package Age-Sex Model to also implement the spectrum paediatric model. We used this model in cases where age and sex specific HIV-seroprevalence surveys and antenatal care-clinic sentinel surveillance data were available. For the remaining 156 of 204 locations, we developed a cohort-incidence bias adjustment to derive incidence as a function of cause-of-death data from vital registration systems. The incidence was input to a custom Spectrum model. To assess progress, we measured the percentage change in incident cases and deaths between 2010 and 2019 (threshold >75% decline), the ratio of incident cases to number of people living with HIV (incidence-to-prevalence ratio threshold <0·03), and the ratio of incident cases to deaths (incidence-to-mortality ratio threshold <1·0). Findings: In 2019, there were 36·8 million (95% uncertainty interval [UI] 35·1–38·9) people living with HIV worldwide. There were 0·84 males (95% UI 0·78–0·91) per female living with HIV in 2019, 0·99 male infections (0·91–1·10) for every female infection, and 1·02 male deaths (0·95–1·10) per female death. Global progress in incident cases and deaths between 2010 and 2019 was driven by sub-Saharan Africa (with a 28·52% decrease in incident cases, 95% UI 19·58–35·43, and a 39·66% decrease in deaths, 36·49–42·36). Elsewhere, the incidence remained stable or increased, whereas deaths generally decreased. In 2019, the global incidence-to-prevalence ratio was 0·05 (95% UI 0·05–0·06) and the global incidence-to-mortality ratio was

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Maximum entropy models for iteratively identifying subjectively interesting structure in real-valued data

Maximum entropy models for iteratively identifying subjectiv...

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European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in databases, ECML PKDD 2013

作者： Kontonasios, Kleanthis-Nikolaos Vreeken, Jilles De Bie, Tijl Intelligent Systems Laboratory University of Bristol Bristol United Kingdom Advanced Database Research and Modelling University of Antwerp Antwerp Belgium

ISBN: (纸本)9783642409905

In exploratory data mining it is important to assess the significance of results. Given that analysts have only limited time, it is important that we can measure this with regard to what we already know. That is, we want to be able to measure whether a result is interesting from a subjective point of view. With this as our goal, we formalise how to probabilistically model real-valued data by the Maximum Entropy principle, where we allow statistics on arbitrary sets of cells as background knowledge. As statistics, we consider means and variances, as well as histograms. The resulting models allow us to assess the likelihood of values, and can be used to verify the significance of (possibly overlapping) structures discovered in the data. As we can feed those structures back in, our model enables iterative identification of subjectively interesting structures. To show the flexibility of our model, we propose a subjective informativeness measure for tiles, i.e. rectangular sub-matrices, in real-valued data. The Information Ratio quantifies how strongly the knowledge of a structure reduces our uncertainty about the data with the amount of effort it would cost to consider it. Empirical evaluation shows that iterative scoring effectively reduces redundancy in ranking candidate tiles-showing the applicability of our model for a range of data mining fields aimed at discovering structure in real-valued data. © 2013 Springer-Verlag.

关键词： Data mining

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25th Annual Computational Neuroscience Meeting CNS-2016, Seogwipo City, South Korea, July 2-7, 2016 Abstracts

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BMC NEUROSCIENCE 2016年第1期17卷 1-112页

作者： [Anonymous] Computational Neurobiology Laboratory The Salk Institute for Biological Studies San Diego USA UNIC CNRS Gif sur Yvette France The European Institute for Theoretical Neuroscience (EITN) Paris France ATR Computational Neuroscience Laboratories Kyoto Japan Krembil Research Institute University Health Network Toronto Canada Department of Physiology University of Toronto Toronto Canada Department of Medicine (Neurology) University of Toronto Toronto Canada Department of Physics University of New Hampshire Durham USA Department of Neurophysiology Nencki Institute of Experimental Biology Warsaw Poland Department of Theory Wigner Research Centre for Physics of the Hungarian Academy of Sciences Budapest Hungary Department of Mathematical Sciences KAIST Daejoen Republic of Korea Department of Mathematics University of Houston Houston USA Department of Biochemistry & Cell Biology and Institute of Biosciences and Bioengineering Rice University Houston USA Department of Biology and Biochemistry University of Houston Houston USA Grupo de Neurocomputación Biológica Dpto. de Ingeniería Informática Escuela Politécnica Superior Universidad Autónoma de Madrid Madrid Spain Department of Biological Sciences University of Southern California Los Angeles USA Center for Neuroscience Korea Institute of Science and Technology Seoul South Korea Department of Neurology Albert Einstein College of Medicine Bronx USA Center for Neuroscience KIST Seoul South Korea Department of Neuroscience University of Science and Technology Daejon South Korea Systems Neuroscience Group QIMR Berghofer Medical Research Institute Herston Australia Department of Psychology Yonsei University Seoul South Korea Department of Psychiatry Kyung Hee University Hospital at Gangdong Seoul South Korea Department of Psychiatry Veterans Administration Boston Healthcare System and Harvard Medical School Brockton USA Department of Electrical and Electronic Engineering The University of Melbourne Parkvil

A1 Functional advantages of cell-type heterogeneity in neural circuits Tatyana O. Sharpee A2 Mesoscopic modeling of propagating waves in visual cortex Alain Destexhe A3 Dynamics and biomarkers of mental disorders Mitsuo Kawato F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons Vladislav Sekulić, Frances K. Skinner F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks. Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi O3 Modeling auditory stream segregation, build-up and bistability James Rankin, Pamela Osborn Popp, John Rinzel O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields Alejandro Tabas, André Rupp, Emili Balaguer-Ballester O5 A simple model of retinal response to multi-electrode stimulation Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer O7 Input-location dependent gain modulation in cerebellar nucleus neurons Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Ni

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Highlights from the 11th ISCB Student Council Symposium 2015. Dublin, Ireland. 10 July 2015

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BMC bioinformatics 2016年第3期17 Suppl 3卷 95页

作者： Katie Wilkins Mehedi Hassan Margherita Francescatto Jakob Jespersen R. Gonzalo Parra Bart Cuypers Dan DeBlasio Alexander Junge Anupama Jigisha Farzana Rahman Griet Laenen Sander Willems Lieven Thorrez Yves Moreau Nagarajan Raju Sonia Pankaj Chothani C. Ramakrishnan Masakazu Sekijima M. Michael Gromiha Paddy J Slator Nigel J Burroughs Przemysław Szałaj Zhonghui Tang Paul Michalski Oskar Luo Xingwang Li Yijun Ruan Dariusz Plewczynski Giulia Fiscon Emanuel Weitschek Massimo Ciccozzi Paola Bertolazzi Giovanni Felici Pieter Meysman Manu Vanaerschot Maya Berg Hideo Imamura Jean-Claude Dujardin Kris Laukens Westa Domanova James R. Krycer Rima Chaudhuri Pengyi Yang Fatemeh Vafaee Daniel J. Fazakerley Sean J. Humphrey David E. James Zdenka Kuncic Plant Pathology and Plant-Microbe Biology Section School of Integrative Plant Science Cornell University Ithaca USA Graduate Field of Computational Biology Cornell University Ithaca USA School of Computing & Mathematics University of South Wales Cardiff UK Department of Genome Biology for Neurodegenerative Diseases German Center for Neurodegenerative Diseases (DZNE) within the Helmholtz Association ᅟ Germany Department of Surgery Massachusetts General Hospital The Broad Institute of MIT and Harvard Boston USA Department of Systems Biology Technical University of Denmark Kemitorvet Denmark Protein Physiology Lab Facultad de Ciencias Exactas y Naturales Universidad de Buenos Aires Buenos Aires Argentina Molecular Parasitology Unit (MPU) Institute of Tropical Medicine Antwerp Belgium Advanced Database Research and Modeling (ADReM) research group University of Antwerp Antwerpen Belgium Department of Computer Science University of Arizona Tucson USA Department of Veterinary Clinical and Animal Sciences Center for non-coding RNA in Technology and Health University of Copenhagen Copenhagen Denmark University College Dublin Dublin Ireland Department of Electrical Engineering (ESAT) STADIUS Center for Dynamical Systems Signal Processing and Data Analytics KU Leuven Leuven Belgium Minds Medical IT Department Leuven Belgium Scientific Institute of Public Health (WIV-ISP) Platform of Biotechnology and Molecular Biology (PBB) Brussels Belgium Department of Development and Regeneration @ Kulak KU Leuven Kortrijk Belgium Department of Biotechnology Bhupat and Jyoti Metha School of Biosciences Indian Institute of Technology Madras Chennai India Philips Research North America Briarcliff Manor USA Global Scientific Information and Computing Center (GSIC) Tokyo Institute of Technology Tokyo Japan Systems Biology Centre University of Warwick Senate House Coventry UK Systems Biology Doctoral Training Centre University of Warwick Senate House Coventry UK Center for B

A1 Highlights from the eleventh ISCB Student Council Symposium 2015 Katie Wilkins, Mehedi Hassan, Margherita Francescatto, Jakob Jespersen, R. Gonzalo Parra, Bart Cuypers, Dan DeBlasio, Alexander Junge, Anupama Jigisha, Farzana Rahman O1 Prioritizing a drug’s targets using both gene expression and structural similarity Griet Laenen, Sander Willems, Lieven Thorrez, Yves Moreau O2 Organism specific protein-RNA recognition: A computational analysis of protein-RNA complex structures from different organisms Nagarajan Raju, Sonia Pankaj Chothani, C. Ramakrishnan, Masakazu Sekijima; M. Michael Gromiha O3 Detection of Heterogeneity in Single Particle Tracking Trajectories Paddy J Slator, Nigel J Burroughs O4 3D-NOME: 3D NucleOme Multiscale Engine for data-driven modeling of three-dimensional genome architecture Przemysław Szałaj, Zhonghui Tang, Paul Michalski, Oskar Luo, Xingwang Li, Yijun Ruan, Dariusz Plewczynski O5 A novel feature selection method to extract multiple adjacent solutions for viral genomic sequences classification Giulia Fiscon, Emanuel Weitschek, Massimo Ciccozzi, Paola Bertolazzi, Giovanni Felici O6 A systems Biology Compendium for Leishmania donovani Bart Cuypers, Pieter Meysman, Manu Vanaerschot, Maya Berg, Hideo Imamura, Jean-Claude Dujardin, Kris Laukens O7 Unravelling signal coordination from large scale phosphorylation kinetic data Westa Domanova, James R. Krycer, Rima Chaudhuri, Pengyi Yang, Fatemeh Vafaee, Daniel J. Fazakerley, Sean J. Humphrey, David E. James, Zdenka Kuncic

关键词： Visceral Leishmaniasis Feature Selection Method Frequent Itemset Mining Leishmania Donovani Student Council

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Towards a data hub for biodiversity with LOD

Towards a data hub for biodiversity with LOD

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2nd Joint International Conference on Semantic Technology, JIST 2012

作者： Minami, Yoshitaka Takeda, Hideaki Kato, Fumihiro Ohmukai, Ikki Arai, Noriko Jinbo, Utsugi Ito, Motomi Kobayashi, Satoshi Kawamoto, Shoko National Institute of Informatics Japan Graduate University for Advanced Studies Japan National Museum of Nature and Science Tokyo Japan Department of General Systems Studies Graduate School of Arts and Sciences University of Tokyo Japan Transdisciplinary Research Integration Center National Institute of Polar Research Japan Database Center for Life Science Research Organization of Information and Systems Japan

ISBN: (纸本)9783642379956

Because of a huge variety of biological studies focused on different targets, i.e., from molecules to ecosystem, data produced and used in each field is also managed independently so that it is difficult to know the relationship among them. We aim to build a data hub with LOD to connect data in different biological fields to enhance search and use of data across the fields. We build a prototype data hub on taxonomic information on species, which is a key to retrieve data and link to databases in different fields. We also demonstrate how the data hub can be used with an application to assist search on other database. © Springer-Verlag 2013.

关键词： Biodiversity

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