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Volume 14 Supplement 3

Selected proceedings from the Automated Function Prediction Meeting 2011

Proceedings

Edited by Iddo Friedberg and Predrag Radivojac

The Automated Function Prediction meeting at ISMB 2011 was supported by a US National Institutes of Health grant R13 HG006079-01A1 awarded to PR and a US Department of Energy, Office of Science grant DE-SC0006807TDD awarded to IF. The meeting organizers gratefully acknowledge the ongoing support of the International Society for Computational Biology to the Automated Function Prediction Special Interest Group.

Automated Function Prediction SIG 2011 featuring the CAFA Challenge: Critical Assessment of Function Annotations. Go to conference site.

Vienna, Austria15-16 July 2011

  1. Accurate protein function annotation is a severe bottleneck when utilizing the deluge of high-throughput, next generation sequencing data. Keeping database annotations up-to-date has become a major scientific ...

    Authors: Domenico Cozzetto, Daniel WA Buchan, Kevin Bryson and David T Jones
    Citation: BMC Bioinformatics 2013 14(Suppl 3):S1
  2. Many Automatic Function Prediction (AFP) methods were developed to cope with an increasing growth of the number of gene sequences that are available from high throughput sequencing experiments. To support the ...

    Authors: Meghana Chitale, Ishita K Khan and Daisuke Kihara
    Citation: BMC Bioinformatics 2013 14(Suppl 3):S2
  3. Predicting protein function from sequence is useful for biochemical experiment design, mutagenesis analysis, protein engineering, protein design, biological pathway analysis, drug design, disease diagnosis, an...

    Authors: Zheng Wang, Renzhi Cao and Jianlin Cheng
    Citation: BMC Bioinformatics 2013 14(Suppl 3):S3
  4. In the genomic era a key issue is protein annotation, namely how to endow protein sequences, upon translation from the corresponding genes, with structural and functional features. Routinely this operation is ...

    Authors: Damiano Piovesan, Pier Luigi Martelli, Piero Fariselli, Giuseppe Profiti, Andrea Zauli, Ivan Rossi and Rita Casadio
    Citation: BMC Bioinformatics 2013 14(Suppl 3):S4
  5. Here we assessed the use of domain families for predicting the functions of whole proteins. These 'functional families' (FunFams) were derived using a protocol that combines sequence clustering with supervised...

    Authors: Robert Rentzsch and Christine A Orengo
    Citation: BMC Bioinformatics 2013 14(Suppl 3):S5
  6. Annotating protein function with both high accuracy and sensitivity remains a major challenge in structural genomics. One proven computational strategy has been to group a few key functional amino acids into t...

    Authors: Serkan Erdin, Eric Venner, Andreas Martin Lisewski and Olivier Lichtarge
    Citation: BMC Bioinformatics 2013 14(Suppl 3):S6
  7. Any method that de novo predicts protein function should do better than random. More challenging, it also ought to outperform simple homology-based inference.

    Authors: Tobias Hamp, Rebecca Kassner, Stefan Seemayer, Esmeralda Vicedo, Christian Schaefer, Dominik Achten, Florian Auer, Ariane Boehm, Tatjana Braun, Maximilian Hecht, Mark Heron, Peter Hönigschmid, Thomas A Hopf, Stefanie Kaufmann, Michael Kiening, Denis Krompass…
    Citation: BMC Bioinformatics 2013 14(Suppl 3):S7
  8. Combining heterogeneous sources of data is essential for accurate prediction of protein function. The task is complicated by the fact that while sequence-based features can be readily compared across species, ...

    Authors: Artem Sokolov, Christopher Funk, Kiley Graim, Karin Verspoor and Asa Ben-Hur
    Citation: BMC Bioinformatics 2013 14(Suppl 3):S10
  9. The prediction of biochemical function from the 3D structure of a protein has proved to be much more difficult than was originally foreseen. A reliable method to test the likelihood of putative annotations and...

    Authors: Zhouxi Wang, Pengcheng Yin, Joslynn S Lee, Ramya Parasuram, Srinivas Somarowthu and Mary Jo Ondrechen
    Citation: BMC Bioinformatics 2013 14(Suppl 3):S13
  10. The assignment of gene function remains a difficult but important task in computational biology. The establishment of the first Critical Assessment of Functional Annotation (CAFA) was aimed at increasing progr...

    Authors: Jesse Gillis and Paul Pavlidis
    Citation: BMC Bioinformatics 2013 14(Suppl 3):S15

Annual Journal Metrics

  • Speed
    15 days to first decision for all manuscripts
    70 days to first decision for reviewed manuscripts only
    163 days from submission to acceptance
    36 days from acceptance to publication

    Citation Impact
    3.169 - 2-year Impact Factor
    3.629 - 5-year Impact Factor
    1.276 - Source Normalized Impact per Paper (SNIP)
    1.567 - SCImago Journal Rank (SJR)

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