Section Editors

  • John S Garavelli, University of Delaware
  • Adam Godzik, Sanford-Burnham Medical Research Institute and UCSD
  • Igor Jurisica, Ontario Cancer Institute
  • Adam Olshen, University of California, San Francisco
  • Hanchuan Peng, Allen Institute for Brain Science
  • Graziano Pesole, University of Bari
  • Olivier Poch, ICube Laboratory, Strasbourg
  • Mihai Pop, University of Maryland
  • Hagit Shatkay, University of Delaware

Executive Editor

  • Irene Pala, BioMed Central


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  • Image attributed to: BMC Bioinformatics 2014, 15:388, from Fig 3

    MAW - Linear-time computation of minimal absent words

    The implementation of the first O(n)-time and O(n)-space algorithm using  suffix arrays outperforms existing tools for computing the minimal absent words of a given sequence, without the use of data structures and with increased efficiency in terms of speed and memory.

    BMC Bioinformatics 2014, 15:388
  • Image attributed to: BMC Bioinformatics 2014, 15:384, from Fig 6

    Taxonomic classification of metagenomes

    The taxonomic classifier AKE (Accelerated k-mer Exploration web-tool), based on a data-driven hierarchical model and parallel computing,  allows faster classification and visual inspection of whole metagenome data sets.

    BMC Bioinformatics 2014, 15:384
  • Image attributed to: BMC Bioinformatics 2014, 15:405, from Fig 3

    Gene Ontology prediction from phenotype data

    A new set of algorithms that inspect the structure and relationship between gene functions and phenotypes through correlation modeling  independently of semantic analysis, can be used to infer functional biological knowledge potentially overlooked through lexical or semantic similarity measures.

    BMC Bioinformatics 2014, 15:405
  • Image attributed to: BMC Bioinformatics 2014, 15:399, from Fig 2

    Bio3D - Integrated analysis of protein structure and evolution

    The Bio3D package includes new methods for the analysis and visualization of protein dynamics both from experimental and simulated data, integrated with tools for comparative analysis of evolutionary related protein structures and systematic retrieval of publicly available sequence and structural data.

    BMC Bioinformatics 2014, 15:399


BMC Bioinformatics is an open access, peer-reviewed journal that considers articles on all aspects of the development, testing and novel application of computational and statistical methods for the modeling and analysis of all kinds of biological data, as well as other areas of computational biology.

BMC Bioinformatics is part of the BMC series which publishes subject-specific journals focused on the needs of individual research communities across all areas of biology and medicine. We offer an efficient, fair and friendly peer review service, and are committed to publishing all sound science, provided that there is some advance in knowledge presented by the work.

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Call for papers - 3D Cell Segmentation and Quantitative Profiling: Methods and Applications

3D Cell Segmentation and Quantitative Profiling

BMC Bioinformatics is currently accepting submissions to a thematic issue entitled ‘3D Cell Segmentation and Quantitative Profiling: Methods and Applications’. We welcome manuscripts that emphasize large-scale image segmentation methods and the biological and biomedical applications thus enabled, including but not limited to multidimensional cellular image segmentation, cell tracking, neuron tracing, modeling of cellular processes and cell populations. Please see the call for papers information page for more details and how to submit.

Image from Wait et al. BMC Bioinformatics 2014 15:328 doi:10.1186/1471-2105-15-328 – figure 3

Volume 16 Suppl 4 (23 February 2015)

Selected articles from the 9th IAPR conference on Pattern Recognition in Bioinformatics

Stockholm, Sweden. 21-23 August 2014

Volume 16 Suppl 3 (13 February 2015)

Highlights from the Third International Society for Computational Biology (ISCB) European Student Council Symposium 2014

Meeting abstracts
Strasbourg, France. 6 September 2014

View all supplements

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ISSN: 1471-2105