Given the functional interdependencies between the molecular components in a human cell, a disease is rarely a consequence of an abnormality in a single gene, but reflects the perturbations of the complex intracellular and intercellular network that links tissue and organ systems. The emerging tools of network medicine offer a platform to explore systematically not only the molecular complexity of a particular disease, leading to the identification of disease modules and pathways, but also the molecular relationships among apparently distinct (patho)phenotypes. Advances in this direction are essential for identifying new disease genes, for uncovering the biological significance of disease-associated mutations identified by genome-wide association studies and full-genome sequencing, and for identifying drug targets and biomarkers for complex diseases.

Network Medicine: A Network-Based Approach to Human Disease

Complete knowledge of all direct and indirect interactions between proteins in a given cell would represent an important milestone towards a comprehensive description of cellular mechanisms and functions. Although this goal is still elusive, considerable progress has been made-particularly for certain model organisms and functional systems. Currently, protein interactions and associations are annotated at various levels of detail in online resources, ranging from raw data repositories to highly formalized pathway databases. For many applications, a global view of all the available interaction data is desirable, including lower-quality data and/or computational predictions. The STRING database (http://string-db.org/) aims to provide such a global perspective for as many organisms as feasible. Known and predicted associations are scored and integrated, resulting in comprehensive protein networks covering >1100 organisms. Here, we describe the update to version 9.1 of STRING, introducing several improvements: (i) we extend the automated mining of scientific texts for interaction information, to now also include full-text articles; (ii) we entirely re-designed the algorithm for transferring interactions from one model organism to the other; and (iii) we provide users with statistical information on any functional enrichment observed in their networks.

/pdf/string-v9-1-protein-protein-interaction-networks-with-42hnvufk2o.pdf

STRING v9.1: protein-protein interaction networks, with increased coverage and integration

We describe the landscape of somatic genomic alterations based on multidimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors, including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.

The somatic genomic landscape of glioblastoma

The Arabidopsis Information Resource (TAIR, http://arabidopsisorg) is a genome database for Arabidopsis thaliana, an important reference organism for many fundamental aspects of biology as well as basic and applied plant biology research TAIR serves as a central access point for Arabidopsis data, annotates gene function and expression patterns using controlled vocabulary terms, and maintains and updates the A thaliana genome assembly and annotation TAIR also provides researchers with an extensive set of visualization and analysis tools Recent de- velopments include several new genome releases (TAIR8, TAIR9 and TAIR10) in which the A thaliana assembly was updated, pseudogenes and transposon genes were re-annotated, and new data from proteomics and next generation transcriptome sequencing were incorporated into gene models and splice variants Other highlights include progress on functional anno- tation of the genome and the release of sev- eral new tools including Textpresso for Arabidopsis which provides the capability to carry out full text searches on a large body of research literature

The Arabidopsis Information Resource (TAIR): improved gene annotation and new tools

The mission of the Universal Protein Resource (UniProt) (http://www.uniprot.org) is to provide the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequences and functional annotation. It integrates, interprets and standardizes data from literature and numerous resources to achieve the most comprehensive catalog possible of protein information. The central activities are the biocuration of the UniProt Knowledgebase and the dissemination of these data through our Web site and web services. UniProt is produced by the UniProt Consortium, which consists of groups from the European Bioinformatics Institute (EBI), the SIB Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is updated and distributed every 4 weeks and can be accessed online for searches or downloads.

Activities at the Universal Protein Resource (UniProt)

The Biological General Repository for Interaction Datasets (BioGRID) is a public database that archives and disseminates genetic and protein
 interaction data from model organisms and humans
 (http://www.thebiogrid.org). BioGRID currently holds 347 966
 interactions (170 162 genetic, 177 804 protein) curated from both
 high-throughput data sets and individual focused studies, as derived
 from over 23 000 publications in the primary literature. Complete
 coverage of the entire literature is maintained for budding yeast
 (Saccharomyces cerevisiae), fission yeast (Schizosaccharomyces pombe)
 and thale cress (Arabidopsis thaliana), and efforts to expand curation
 across multiple metazoan species are underway. The BioGRID houses 48
 831 human protein interactions that have been curated from 10 247
 publications. Current curation drives are focused on particular areas
 of biology to enable insights into conserved networks and pathways that
 are relevant to human health. The BioGRID 3.0 web interface contains
 new search and display features that enable rapid queries across
 multiple data types and sources. An automated Interaction Management
 System (IMS) is used to prioritize, coordinate and track curation
 across international sites and projects. BioGRID provides interaction
 data to several model organism databases, resources such as Entrez-Gene
 and other interaction meta-databases. The entire BioGRID 3.0 data
 collection may be downloaded in multiple file formats, including PSI MI
 XML. Source code for BioGRID 3.0 is freely available without any
 restrictions.

/pdf/the-biogrid-interaction-database-2011-update-4t23jtqdsl.pdf

The BioGRID Interaction Database: 2011 update

Since its release in 2000, WormBase (http://www.wormbase.org) has grown from a small resource focusing on a single species and serving a dedicated research community, to one now spanning 15 species essential to the broader biomedical and agricultural research fields. To enhance the rate of curation, we have automated the identification of key data in the scientific literature and use similar methodology for data extraction. To ease access to the data, we are collaborating with journals to link entities in research publications to their report pages at WormBase. To facilitate discovery, we have added new views of the data, integrated large-scale datasets and expanded descriptions of models for human disease. Finally, we have introduced a dramatic overhaul of the WormBase website for public beta testing. Designed to balance complexity and usability, the new site is species-agnostic, highly customizable, and interactive. Casual users and developers alike will be able to leverage the public RESTful application programming interface (API) to generate custom data mining solutions and extensions to the site. We report on the growth of our database and on our work in keeping pace with the growing demand for data, efforts to anticipate the requirements of users and new collaborations with the larger science community.

/pdf/wormbase-2012-more-genomes-more-data-new-website-33qjz5vwqg.pdf

Xiaoqi Shi

Papers

The BioGRID Interaction Database: 2011 update

WormBase 2012: more genomes, more data, new website