BioGRID

BioGRID: A general repository for interaction datasets. Access to unified datasets of protein and genetic interactions is critical for interrogation of gene/protein function and analysis of global network properties. BioGRID is a freely accessible database of physical and genetic interactions available at http://www.thebiogrid.org. BioGRID release version 2.0 includes >116 000 interactions from Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster and Homo sapiens. Over 30 000 interactions have recently been added from 5778 sources through exhaustive curation of the Saccharomyces cerevisiae primary literature. An internally hyper-linked web interface allows for rapid search and retrieval of interaction data. Full or user-defined datasets are freely downloadable as tab-delimited text files and PSI-MI XML. Pre-computed graphical layouts of interactions are available in a variety of file formats. User-customized graphs with embedded protein, gene and interaction attributes can be constructed with a visualization system called Osprey that is dynamically linked to the BioGRID.


References in zbMATH (referenced in 45 articles )

Showing results 21 to 40 of 45.
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  1. Kasabov, Nikola (ed.): Springer handbook of bio-/neuro-informatics (2014)
  2. Yang, Lei; Wang, Jizhe; Wang, Huiping; Lv, Yingli; Zuo, Yongchun; Jiang, Wei: Analysis and identification of toxin targets by topological properties in protein-protein interaction network (2014)
  3. Frasca, Marco; Bertoni, Alberto; Re, Matteo; Valentini, Giorgio: A neural network algorithm for semi-supervised node label learning from unbalanced data (2013)
  4. Panigrahi, Priya P.; Singh, Tiratha Raj: Computational studies on Alzheimer’s disease associated pathways and regulatory patterns using microarray gene expression and network data: revealed association with aging and other diseases (2013)
  5. Cesa-Bianchi, Nicolò; Re, Matteo; Valentini, Giorgio: Synergy of multi-label hierarchical ensembles, data fusion, and cost-sensitive methods for gene functional inference (2012)
  6. Livingstone, Kevin; Olofsson, Peter; Cochran, Garner; Dagilis, Andrius; MacPherson, Karen; Seitz, Kerry A. jun.: A stochastic model for the development of Bateson-Dobzhansky-Muller incompatibilities that incorporates protein interaction networks (2012)
  7. Doderer, Mark; Yoon, Kihoon; Robbins, Kay A.: SIDEKICK: genomic data driven analysis and decision-making framework (2010) ioport
  8. Lachmann, Alexander; Ma’ayan, Avi: Lists2networks: integrated analysis of gene/protein lists (2010) ioport
  9. Li, Yongjin; Patra, Jagdish Chandra: Integration of multiple data sources to prioritize candidate genes using discounted rating system (2010) ioport
  10. Roslan, Rosfuzah; Othman, Razib M.; Shah, Zuraini A.; Kasim, Shahreen; Asmuni, Hishammuddin; Taliba, Jumail; Hassan, Rohayanti; Zakaria, Zalmiyah: Incorporating multiple genomic features with the utilization of interacting domain patterns to improve the prediction of protein-protein interactions (2010) ioport
  11. Bayir, Murat Ali; Guney, Tacettin Dogacan; Can, Tolga: Integration of topological measures for eliminating non-specific interactions in protein interaction networks (2009)
  12. Brandão, Marcelo M.; Dantas, Luiza L.; Silva-Filho, Marcio C.: Atpin: \textitarabidopsisthalianaprotein interaction network (2009) ioport
  13. Chipman, Kyle C.; Singh, Ambuj K.: Predicting genetic interactions with random walks on biological networks (2009) ioport
  14. Heath, Allison P.; Kavraki, Lydia E.: Computational challenges in systems biology (2009)
  15. Marín, Ignacio; Hoyas, Sergio: Basic networks: definition and applications (2009)
  16. Mesiti, Marco; Jiménez-Ruiz, Ernesto; Sanz, Ismael; Llavori, Rafael Berlanga; Perlasca, Paolo; Valentini, Giorgio; Manset, David: XML-based approaches for the integration of heterogeneous bio-molecular data (2009) ioport
  17. Pandey, Gaurav; Myers, Chad L.; Kumar, Vipin: Incorporating functional inter-relationships into protein function prediction algorithms (2009) ioport
  18. Qu, Xiaoyan A.; Gudivada, Ranga Chandra; Jegga, Anil G.; Neumann, Eric K.; Aronow, Bruce J.: Inferring novel disease indications for known drugs by semantically linking drug action and disease mechanism relationships (2009) ioport
  19. Vlasblom, James; Wodak, Shoshana J.: Markov clustering versus affinity propagation for the partitioning of protein interaction graphs (2009) ioport
  20. Wong, Limsoon; Liu, Guimei: Protein interactome analysis for countering pathogen drug resistance (2009) ioport