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Automated Function Prediction: sifting through the biological data labelled as unknown function

Tying in with the Automated Function Prediction-Special Interest Group (AFP-SIG) at the Intelligent Systems for Molecular Biology (ISMB) meetings, this thematic series highlights function prediction using sequence-based methods, function from genomic information, molecular interactions, structure, use of combined methods, and phylogeny-based methods. Articles can also take advantage of GigaDB to host data and tools to promote reproducible research and further collaboration amongst computational biologists crossing many different data domains.

Dr. Iddo Friedberg, Prof Predrag Radivojac, Dr Mark Wass

  1. Content type: Research

    The recently held Critical Assessment of Function Annotation challenge (CAFA2) required its participants to submit predictions for a large number of target proteins regardless of whether they have previous ann...

    Authors: Indika Kahanda, Christopher S Funk, Fahad Ullah, Karin M Verspoor and Asa Ben-Hur

    Citation: GigaScience 2015 4:41

    Published on:

  2. Content type: Research

    Functional annotation of novel proteins is one of the central problems in bioinformatics. With the ever-increasing development of genome sequencing technologies, more and more sequence information is becoming ...

    Authors: Ishita K. Khan, Qing Wei, Samuel Chapman, Dukka B. KC and Daisuke Kihara

    Citation: GigaScience 2015 4:43

    Published on:

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