Bio

Professional Education


  • Diplom, Fachhochschule Hamburg (2003)
  • Doctor of Philosophy, University of Manchester (2009)

Research & Scholarship

Lab Affiliations


Publications

Journal Articles


  • BioHackathon series in 2011 and 2012: penetration of ontology and linked data in life science domains JOURNAL OF BIOMEDICAL SEMANTICS Katayama, T., Wilkinson, M. D., Aoki-Kinoshita, K. F., Kawashima, S., Yamamoto, Y., Yamaguchi, A., Okamoto, S., Kawano, S., Kim, J., Wang, Y., Wu, H., Kano, Y., Ono, H., Bono, H., Kocbek, S., Aerts, J., Akune, Y., Antezana, E., Arakawa, K., Aranda, B., Baran, J., Bolleman, J., Bonnal, R. J., Buttigieg, P. L., Campbell, M. P., Chen, Y., Chiba, H., Cock, P. J., Cohen, K. B., Constantin, A., Duck, G., Dumontier, M., Fujisawa, T., Fujiwara, T., Goto, N., Hoehndorf, R., Igarashi, Y., Itaya, H., Ito, M., Iwasaki, W., Kalas, M., Katoda, T., Kim, T., Kokubu, A., Komiyama, Y., Kotera, M., Laibe, C., Lapp, H., Luetteke, T., Marshall, M. S., Mori, T., Mori, H., Morita, M., Murakami, K., Nakao, M., Narimatsu, H., Nishide, H., Nishimura, Y., Nystrom-Persson, J., Ogishima, S., Okamura, Y., Okuda, S., Oshita, K., Packer, N. H., Prins, P., Ranzinger, R., Rocca-Serra, P., Sansone, S., Sawaki, H., Shin, S., Splendiani, A., Strozzi, F., Tadaka, S., Toukach, P., Uchiyama, I., Umezaki, M., Vos, R., Whetzel, P. L., Yamada, I., Yamasaki, C., Yamashita, R., York, W. S., Zmasek, C. M., Kawamoto, S., Takagi, T. 2014; 5

    Abstract

    The application of semantic technologies to the integration of biological data and the interoperability of bioinformatics analysis and visualization tools has been the common theme of a series of annual BioHackathons hosted in Japan for the past five years. Here we provide a review of the activities and outcomes from the BioHackathons held in 2011 in Kyoto and 2012 in Toyama. In order to efficiently implement semantic technologies in the life sciences, participants formed various sub-groups and worked on the following topics: Resource Description Framework (RDF) models for specific domains, text mining of the literature, ontology development, essential metadata for biological databases, platforms to enable efficient Semantic Web technology development and interoperability, and the development of applications for Semantic Web data. In this review, we briefly introduce the themes covered by these sub-groups. The observations made, conclusions drawn, and software development projects that emerged from these activities are discussed.

    View details for DOI 10.1186/2041-1480-5-5

    View details for Web of Science ID 000343707900001

    View details for PubMedID 24495517

  • WormBase 2014: new views of curated biology. Nucleic acids research Harris, T. W., Baran, J., Bieri, T., Cabunoc, A., Chan, J., Chen, W. J., Davis, P., Done, J., Grove, C., Howe, K., Kishore, R., Lee, R., Li, Y., Muller, H., Nakamura, C., Ozersky, P., Paulini, M., Raciti, D., Schindelman, G., Tuli, M. A., Van Auken, K., Wang, D., Wang, X., Williams, G., Wong, J. D., Yook, K., Schedl, T., Hodgkin, J., Berriman, M., Kersey, P., Spieth, J., Stein, L., Sternberg, P. W. 2014; 42 (Database issue): D789-93

    Abstract

    WormBase (http://www.wormbase.org/) is a highly curated resource dedicated to supporting research using the model organism Caenorhabditis elegans. With an electronic history predating the World Wide Web, WormBase contains information ranging from the sequence and phenotype of individual alleles to genome-wide studies generated using next-generation sequencing technologies. In recent years, we have expanded the contents to include data on additional nematodes of agricultural and medical significance, bringing the knowledge of C. elegans to bear on these systems and providing support for underserved research communities. Manual curation of the primary literature remains a central focus of the WormBase project, providing users with reliable, up-to-date and highly cross-linked information. In this update, we describe efforts to organize the original atomized and highly contextualized curated data into integrated syntheses of discrete biological topics. Next, we discuss our experiences coping with the vast increase in available genome sequences made possible through next-generation sequencing platforms. Finally, we describe some of the features and tools of the new WormBase Web site that help users better find and explore data of interest.

    View details for DOI 10.1093/nar/gkt1063

    View details for PubMedID 24194605

  • The Semanticscience Integrated Ontology (SIO) for biomedical research and knowledge discovery Journal of Biomedical Semantics Dumontier, M., Baker, C. J., Baran, J., Callahan, A., Chepelev, L., Cruz-Toledo, J., Del Rio, N. R., Duck, G., Furlong, L. I., Keath, N., Klassen, D., McCusker, J. P., Queralt-Rosinach, N., Samwald, M., Villanueva-Rosales, N., Wilkinson, M. D., Hoehndort, R. 2014; 5 (14)

    View details for DOI 10.1186/2041-1480-5-14

  • pubmed2ensembl: A Resource for Mining the Biological Literature on Genes PLOS ONE Baran, J., Gerner, M., Haeussler, M., Nenadic, G., Bergman, C. M. 2011; 6 (9)

    Abstract

    The last two decades have witnessed a dramatic acceleration in the production of genomic sequence information and publication of biomedical articles. Despite the fact that genome sequence data and publications are two of the most heavily relied-upon sources of information for many biologists, very little effort has been made to systematically integrate data from genomic sequences directly with the biological literature. For a limited number of model organisms dedicated teams manually curate publications about genes; however for species with no such dedicated staff many thousands of articles are never mapped to genes or genomic regions.To overcome the lack of integration between genomic data and biological literature, we have developed pubmed2ensembl (http://www.pubmed2ensembl.org), an extension to the BioMart system that links over 2,000,000 articles in PubMed to nearly 150,000 genes in Ensembl from 50 species. We use several sources of curated (e.g., Entrez Gene) and automatically generated (e.g., gene names extracted through text-mining on MEDLINE records) sources of gene-publication links, allowing users to filter and combine different data sources to suit their individual needs for information extraction and biological discovery. In addition to extending the Ensembl BioMart database to include published information on genes, we also implemented a scripting language for automated BioMart construction and a novel BioMart interface that allows text-based queries to be performed against PubMed and PubMed Central documents in conjunction with constraints on genomic features. Finally, we illustrate the potential of pubmed2ensembl through typical use cases that involve integrated queries across the biomedical literature and genomic data.By allowing biologists to find the relevant literature on specific genomic regions or sets of functionally related genes more easily, pubmed2ensembl offers a much-needed genome informatics inspired solution to accessing the ever-increasing biomedical literature.

    View details for DOI 10.1371/journal.pone.0024716

    View details for Web of Science ID 000295939600005

    View details for PubMedID 21980353

  • BioMart Central Portal: an open database network for the biological community DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION Guberman, J. M., Ai, J., Arnaiz, O., Baran, J., Blake, A., Baldock, R., Chelala, C., Croft, D., Cros, A., Cutts, R. J., di Genova, A., Forbes, S., Fujisawa, T., Gadaleta, E., Goodstein, D. M., Gundem, G., Haggarty, B., Haider, S., Hall, M., Harris, T., Haw, R., Hu, S., Hubbard, S., Hsu, J., Iyer, V., Jones, P., Katayama, T., Kinsella, R., Kong, L., Lawson, D., Liang, Y., Lopez-Bigas, N., Luo, J., Lush, M., Mason, J., Moreews, F., Ndegwa, N., Oakley, D., Perez-Llamas, C., Primig, M., Rivkin, E., Rosanoff, S., Shepherd, R., Simon, R., Skarnes, B., Smedley, D., Sperling, L., Spooner, W., Stevenson, P., Stone, K., Teague, J., Wang, J., Wang, J., Whitty, B., WONG, D. T., Wong-Erasmus, M., Yao, L., Youens-Clark, K., Yung, C., Zhang, J., Kasprzyk, A. 2011

    Abstract

    BioMart Central Portal is a first of its kind, community-driven effort to provide unified access to dozens of biological databases spanning genomics, proteomics, model organisms, cancer data, ontology information and more. Anybody can contribute an independently maintained resource to the Central Portal, allowing it to be exposed to and shared with the research community, and linking it with the other resources in the portal. Users can take advantage of the common interface to quickly utilize different sources without learning a new system for each. The system also simplifies cross-database searches that might otherwise require several complicated steps. Several integrated tools streamline common tasks, such as converting between ID formats and retrieving sequences. The combination of a wide variety of databases, an easy-to-use interface, robust programmatic access and the array of tools make Central Portal a one-stop shop for biological data querying. Here, we describe the structure of Central Portal and show example queries to demonstrate its capabilities.

    View details for DOI 10.1093/database/bar041

    View details for Web of Science ID 000299630600043

    View details for PubMedID 21930507

  • International Cancer Genome Consortium Data Portal-a one-stop shop for cancer genomics data DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION Zhang, J., Baran, J., Cros, A., Guberman, J. M., Haider, S., Hsu, J., Liang, Y., Rivkin, E., Wang, J., Whitty, B., Wong-Erasmus, M., Yao, L., Kasprzyk, A. 2011

    Abstract

    The International Cancer Genome Consortium (ICGC) is a collaborative effort to characterize genomic abnormalities in 50 different cancer types. To make this data available, the ICGC has created the ICGC Data Portal. Powered by the BioMart software, the Data Portal allows each ICGC member institution to manage and maintain its own databases locally, while seamlessly presenting all the data in a single access point for users. The Data Portal currently contains data from 24 cancer projects, including ICGC, The Cancer Genome Atlas (TCGA), Johns Hopkins University, and the Tumor Sequencing Project. It consists of 3478 genomes and 13 cancer types and subtypes. Available open access data types include simple somatic mutations, copy number alterations, structural rearrangements, gene expression, microRNAs, DNA methylation and exon junctions. Additionally, simple germline variations are available as controlled access data. The Data Portal uses a web-based graphical user interface (GUI) to offer researchers multiple ways to quickly and easily search and analyze the available data. The web interface can assist in constructing complicated queries across multiple data sets. Several application programming interfaces are also available for programmatic access. Here we describe the organization, functionality, and capabilities of the ICGC Data Portal.

    View details for DOI 10.1093/database/bar026

    View details for Web of Science ID 000299630600028

    View details for PubMedID 21930502

  • BioMart: a data federation framework for large collaborative projects DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION Zhang, J., Haider, S., Baran, J., Cros, A., Guberman, J. M., Hsu, J., Liang, Y., Yao, L., Kasprzyk, A. 2011

    Abstract

    BioMart is a freely available, open source, federated database system that provides a unified access to disparate, geographically distributed data sources. It is designed to be data agnostic and platform independent, such that existing databases can easily be incorporated into the BioMart framework. BioMart allows databases hosted on different servers to be presented seamlessly to users, facilitating collaborative projects between different research groups. BioMart contains several levels of query optimization to efficiently manage large data sets and offers a diverse selection of graphical user interfaces and application programming interfaces to ensure that queries can be performed in whatever manner is most convenient for the user. The software has now been adopted by a large number of different biological databases spanning a wide range of data types and providing a rich source of annotation available to bioinformaticians and biologists alike.

    View details for DOI 10.1093/database/bar038

    View details for Web of Science ID 000299630600040

    View details for PubMedID 21930506

  • An active registry for bioinformatics web services BIOINFORMATICS Pettifer, S., Thorne, D., McDermott, P., Attwood, T., Baran, J., BRYNE, J. C., HUPPONEN, T., Mowbray, D., Vriend, G. 2009; 25 (16): 2090-2091

    Abstract

    The EMBRACE Registry is a web portal that collects and monitors web services according to test scripts provided by the their administrators. Users are able to search for, rank and annotate services, enabling them to select the most appropriate working service for inclusion in their bioinformatics analysis tasks.Web site implemented with PHP, Python, MySQL and Apache, with all major browsers supported. (www.embraceregistry.net).

    View details for DOI 10.1093/bioinformatics/btp329

    View details for Web of Science ID 000268808600019

    View details for PubMedID 19460889

  • Forays into Sequential Composition and Concatenation in EAGLE RUNTIME VERIFICATION Baran, J., Barringer, H. 2008; 5289: 69-85
  • A grammatical representation of visibly pushdown languages LOGIC, LANGUAGE, INFORMATION AND COMPUTATION, PROCEEDINGS Baran, J., Barringer, H. 2007; 4576: 1-11

Footer Links:

Stanford Medicine Resources: