High throughput chemical methods were to be used to make large numbers of predicted proteins and protein domains, based on microbial genome sequences. excellence, Structure To browse Academia.edu and the wider internet faster and more securely, please take a few seconds toupgrade your browser. 3, Issue 1, Proceedings of the National Academy of Sciences, Vol. for Research on Aging, Novato, CA (United States), Univ. Bioinformatics Group, Purdue Univ., West Lafayette, IN (United States). Dept. P. Radivojac, W.T. DomainSVM method utilizes evidence of multiple interacting domains to predict a protein interaction. of California, San Francisco, CA (United States). Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. Inst. Here we present DomainSVM, a predictive method for PPI that uses computationally inferred domain-domain interaction values in a Support Vector Machine framework to predict protein interactions. 28, Issue 12, PLoS Computational Biology, Vol. facilities. of Bioengineering and Therapeutic Sciences, Colorado State Univ., Fort Collins, CO (United States). Fifty-four methods representing the state of the art for protein function prediction were evaluated on a target set of 866 proteins from 11 organisms. Gene Ontology: tool for the unification of biology. Intrinsically disordered proteins and intrinsically disordered protein regions. Dept. Oron, A.M. Schnoes, T. Wittkop, Y.A.I. Division of Molecular Biosciences; Spanish National Research Council (CSIC), Madrid (Spain). of California, Berkeley, CA (United States). 295, Issue 2, Journal of Aquatic Food Product Technology, Vol. Univ.
44, Issue 14, Royal Society Open Science, Vol. Fenner, Kathrin; Canonica, Silvio; Wackett, Lawrence P. Hornung, Bastian; Martins dos Santos, Vitor A. P.; Smidt, Hauke, Yu, Guoxian; Zhu, Hailong; Domeniconi, Carlotta, Callahan, Alison; Cifuentes, Juan Jos; Dumontier, Michel, Lena, Pietro Di; Domeniconi, Giacomo; Margara, Luciano, vek, Clemens; Friedrichs, Gerald; Heizinger, Leonhard, Alborzi, Seyed Ziaeddin; Ritchie, David W.; Devignes, Marie-Dominique, Teso, Stefano; Masera, Luca; Diligenti, Michelangelo, Perlasca, Paolo; Frasca, Marco; Ba, Cheick Tidiane. 9, Issue 5, PLOS Computational Biology, Vol. Hoehndorf, R.; Schofield, P. N.; Gkoutos, G. V. Koskinen, Patrik; Trnen, Petri; Nokso-Koivisto, Jussi, Alshahrani, Mona; Khan, Mohammad Asif; Maddouri, Omar, Mahlich, Yannick; Steinegger, Martin; Rost, Burkhard, Khan, Ishita K.; Jain, Aashish; Rawi, Reda, Morandin, Claire; Havukainen, Heli; Kulmuni, Jonna, Motion, Graham B.; Howden, AndrewJ.M.; Huitema, Edgar, Tatusova, Tatiana; DiCuccio, Michael; Badretdin, Azat, Zhu, Chengsheng; Miller, Maximilian; Marpaka, Srinayani. of Missouri, Columbia, MO (United States). Computational Bioscience Program. 284, Issue 31, Molecular Systems Biology, Vol. of Padova (Italy). Here we report the results from the first large-scale community-based critical assessment of protein function annotation (CAFA) experiment. 08, Issue 02, PLoS Computational Biology, Vol. campus tour, Connect with A large-scale evaluation of computational protein function prediction, Mathematical and Statistical Methods - Biometris, Nature Methods : techniques for life scientists and chemists. of Electrical Engineering and Computer Science. and governance, Alumni & sections dedicated to protein function research, with an emphasis on the theory and practice of computational methods utilized in functional annotation. Dive into the research topics of 'A large-scale evaluation of computational protein function prediction'. Wimalanathan, Kokulapalan; Lawrence-Dill, Carolyn J. Vidulin, Vedrana; muc, Tomislav; Deroski, Sao. Ashburner, Michael; Ball, Catherine A.; Blake, Judith A. Kourmpetis, Yiannis A. I.; van Dijk, Aalt D. J.; Bink, Marco C. A. M. Wang, Dennis Ding-Hwa; Shu, Zhanyong; Lieser, Scot A. Vazquez, Alexei; Flammini, Alessandro; Maritan, Amos, Sharan, Roded; Ulitsky, Igor; Shamir, Ron.
journal = "Nature Methods : techniques for life scientists and chemists", Radivojac, P, Clark, WT, Oron, TR, Schnoes, AM, Wittkop, T, Kourmpetis, YAI. The meeting was exciting and, based on feedback, quite successful. 38, Issue 1, Journal of Evolutionary Biology, Vol. College of Medicine. 31, Issue 8, Nucleic Acids Research, Vol. Such patterns suggest relationships in the data that only a biology domain expert might be able to explain. School of Medicine. of Plant and Microbial Biology; Wellcome Trust Genome Campus, Hinxton (United Kingdom). Centre for Systems and Synthetic Biology. There were 73 registered delegates at the meeting. Have you forgotten your guest credentials? Two findings stand out: (i) today's best protein function prediction algorithms substantially outperform widely used first-generation methods, with large gains on all types of targets; and (ii) although the top methods perform well enough to guide experiments, there is considerable need for improvement of currently available tools.". of Plant and Microbial Biology, Miami Univ., Oxford, OH (United States). 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