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
  • Mihai Pop, University of Maryland

Executive Editor

  • Irene Pala, BioMed Central


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  • Image attributed to: Taken from Sohn et al. BMC Bioinformatics 2014, 15:242, Figure 7

    TAEC – accurate quantification of genomes

    Taxonomic Analysis by Elimination and Correction outperforms other tools in estimating taxonomic composition at a very low rank, especially when closely related species/strains exist in a metagenomic sample.

    BMC Bioinformatics 2014, 15:242
  • Image attributed to: By Gnomehacker via Wikipedia

    MoTex-II for motifs

    MoTeX-II is  a word-based high-performance computing tool for single and  structured MoTif eXtraction from large-scale datasets where runtime does not depend on the length of motifs, the size of the alphabet, or the error thresholds

    BMC Bioinformatics 2014, 15:235
  • Image attributed to: Taken from Kalari et al. BMC Bioinformatics 2014, 15:224, Fig. 6

    MAP-RSeq from Mayo clinic

    A comprehensive analysis pipeline and workflow provides detailed research data reports for RNA-Seq; the software is available as a multi-threaded version for cluster use or single thread for a virtual machine

    BMC Bioinformatics 2014, 15:224
  • Image attributed to: Taken from Ferreira et al. BMC Bioinformatics 2014, 15:  fig 1

    Cache-Oblivious Parallel SIMD Viterbi (COPS)

    COPS introduces an optimized vectorization of the Viterbi decoding algorithm built to work with the HMMER tool suite to improve speed of biological sequence analysis, with long and short models being processed up to two times faster.

    BMC Bioinformatics 2014, 15:165



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