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  1. Indexing is a crucial step in any information retrieval system. In MEDLINE, a widely used database of the biomedical literature, the indexing process involves the selection of Medical Subject Headings in order to...

    Authors: Aurélie Névéol, Sonya E Shooshan and Vincent Claveau
    Citation: BMC Bioinformatics 2008 9(Suppl 11):S11

    This article is part of a Supplement: Volume 9 Supplement 11

  2. Due to the nature of scientific methodology, research articles are rich in speculative and tentative statements, also known as hedges. We explore a linguistically motivated approach to the problem of recognizi...

    Authors: Halil Kilicoglu and Sabine Bergler
    Citation: BMC Bioinformatics 2008 9(Suppl 11):S10

    This article is part of a Supplement: Volume 9 Supplement 11

  3. Detecting uncertain and negative assertions is essential in most BioMedical Text Mining tasks where, in general, the aim is to derive factual knowledge from textual data. This article reports on a corpus annot...

    Authors: Veronika Vincze, György Szarvas, Richárd Farkas, György Móra and János Csirik
    Citation: BMC Bioinformatics 2008 9(Suppl 11):S9

    This article is part of a Supplement: Volume 9 Supplement 11

  4. Previous studies of named entity recognition have shown that a reasonable level of recognition accuracy can be achieved by using machine learning models such as conditional random fields or support vector mach...

    Authors: Yoshimasa Tsuruoka, Jun'ichi Tsujii and Sophia Ananiadou
    Citation: BMC Bioinformatics 2008 9(Suppl 11):S8

    This article is part of a Supplement: Volume 9 Supplement 11

  5. Like text in other domains, biomedical documents contain a range of terms with more than one possible meaning. These ambiguities form a significant obstacle to the automatic processing of biomedical texts. Pre...

    Authors: Mark Stevenson, Yikun Guo, Robert Gaizauskas and David Martinez
    Citation: BMC Bioinformatics 2008 9(Suppl 11):S7

    This article is part of a Supplement: Volume 9 Supplement 11

  6. Term identification is the task of grounding ambiguous mentions of biomedical named entities in text to unique database identifiers. Previous work on term identification has focused on studying species-specifi...

    Authors: Xinglong Wang and Michael Matthews
    Citation: BMC Bioinformatics 2008 9(Suppl 11):S6

    This article is part of a Supplement: Volume 9 Supplement 11

  7. The Clinical E-Science Framework (CLEF) project has built a system to extract clinically significant information from the textual component of medical records in order to support clinical research, evidence-ba...

    Authors: Angus Roberts, Robert Gaizauskas, Mark Hepple and Yikun Guo
    Citation: BMC Bioinformatics 2008 9(Suppl 11):S3

    This article is part of a Supplement: Volume 9 Supplement 11

  8. An important emerging trend in the analysis of microarray data is to incorporate known pathway information a priori. Expression level "summaries" for pathways, obtained from the expression data for the genes c...

    Authors: Rosemary Braun, Leslie Cope and Giovanni Parmigiani
    Citation: BMC Bioinformatics 2008 9:488
  9. By using a standard Support Vector Machine (SVM) with a Sequential Minimal Optimization (SMO) method of training, Naïve Bayes and other machine learning algorithms we are able to distinguish between two classe...

    Authors: Myron Peto, Andrzej Kloczkowski, Vasant Honavar and Robert L Jernigan
    Citation: BMC Bioinformatics 2008 9:487
  10. Large-scale compilation of gene expression microarray datasets across diverse biological phenotypes provided a means of gathering a priori knowledge in the form of identification and annotation of bimodal gene...

    Authors: Michael Gormley and Aydin Tozeren
    Citation: BMC Bioinformatics 2008 9:486
  11. The rate of mRNA transcription is controlled by transcription factors that bind to specific DNA motifs in promoter regions upstream of protein coding genes. Recent results indicate that not only the presence o...

    Authors: Jakub Orzechowski Westholm, Feifei Xu, Hans Ronne and Jan Komorowski
    Citation: BMC Bioinformatics 2008 9:484
  12. For the past few years, scientific controversy has surrounded the large number of errors in forensic and literature mitochondrial DNA (mtDNA) data. However, recent research has shown that using mtDNA phylogeny...

    Authors: Hwan Young Lee, Injee Song, Eunho Ha, Sung-Bae Cho, Woo Ick Yang and Kyoung-Jin Shin
    Citation: BMC Bioinformatics 2008 9:483
  13. Recently, microarray data analyses using functional pathway information, e.g., gene set enrichment analysis (GSEA) and significance analysis of function and expression (SAFE), have gained recognition as a way ...

    Authors: Rongheng Lin, Shuangshuang Dai, Richard D Irwin, Alexandra N Heinloth, Gary A Boorman and Leping Li
    Citation: BMC Bioinformatics 2008 9:481
  14. Microarray techniques are one of the main methods used to investigate thousands of gene expression profiles for enlightening complex biological processes responsible for serious diseases, with a great scientif...

    Authors: Luca Corradi, Marco Fato, Ivan Porro, Silvia Scaglione and Livia Torterolo
    Citation: BMC Bioinformatics 2008 9:480
  15. Alternative splicing is a major contributor to the diversity of eukaryotic transcriptomes and proteomes. Currently, large scale detection of alternative splicing using expressed sequence tags (ESTs) or microar...

    Authors: Rileen Sinha, Michael Hiller, Rainer Pudimat, Ulrike Gausmann, Matthias Platzer and Rolf Backofen
    Citation: BMC Bioinformatics 2008 9:477
  16. The prediction of a consensus structure for a set of related RNAs is an important first step for subsequent analyses. RNAalifold, which computes the minimum energy structure that is simultaneously formed by a ...

    Authors: Stephan H Bernhart, Ivo L Hofacker, Sebastian Will, Andreas R Gruber and Peter F Stadler
    Citation: BMC Bioinformatics 2008 9:474
  17. The epidermal physiology results from a complex regulated homeostasis of keratinocyte proliferation, differentiation and death and is tightly regulated by a specific protein expression during cellular maturati...

    Authors: Thora Pommerencke, Thorsten Steinberg, Hartmut Dickhaus, Pascal Tomakidi and Niels Grabe
    Citation: BMC Bioinformatics 2008 9:473
  18. Researchers interested in analysing the expression patterns of functionally related genes usually hope to improve the accuracy of their results beyond the boundaries of currently available experimental data. G...

    Authors: Tao Xu, LinFang Du and Yan Zhou
    Citation: BMC Bioinformatics 2008 9:472
  19. Detection of non coding RNA (ncRNA) molecules is a major bioinformatics challenge. This challenge is particularly difficult when attempting to detect H/ACA molecules which are involved in converting uridine to...

    Authors: Inna Myslyuk, Tirza Doniger, Yair Horesh, Avraham Hury, Ran Hoffer, Yaara Ziporen, Shulamit Michaeli and Ron Unger
    Citation: BMC Bioinformatics 2008 9:471
  20. Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectroscopy or Mass Spectrometry. Such analysis ...

    Authors: Kenneth Bryan, Lorraine Brennan and Pádraig Cunningham
    Citation: BMC Bioinformatics 2008 9:470
  21. Despite the widespread usage of DNA microarrays, questions remain about how best to interpret the wealth of gene-by-gene transcriptional levels that they measure. Recently, methods have been proposed which use...

    Authors: Nathan L Tintle, Aaron A Best, Matthew DeJongh, Dirk Van Bruggen, Fred Heffron, Steffen Porwollik and Ronald C Taylor
    Citation: BMC Bioinformatics 2008 9:469
  22. Probability based statistical learning methods such as mutual information and Bayesian networks have emerged as a major category of tools for reverse engineering mechanistic relationships from quantitative bio...

    Authors: Weijun Luo, Kurt D Hankenson and Peter J Woolf
    Citation: BMC Bioinformatics 2008 9:467
  23. Identification of approximate tandem repeats is an important task of broad significance and still remains a challenging problem of computational genomics. Often there is no single best approach to periodicity ...

    Authors: Vladimir Paar, Nenad Pavin, Ivan Basar, Marija Rosandić, Matko Glunčić and Nils Paar
    Citation: BMC Bioinformatics 2008 9:466
  24. Medium- to large-scale expression profiling using quantitative polymerase chain reaction (qPCR) assays are becoming increasingly important in genomics research. A major bottleneck in experiment preparation is ...

    Authors: Samuel Arvidsson, Miroslaw Kwasniewski, Diego Mauricio Riaño-Pachón and Bernd Mueller-Roeber
    Citation: BMC Bioinformatics 2008 9:465
  25. Authors: Regina Bohnert, Georg Zeller, Richard M Clark, Kevin L Childs, Victor Ulat, Renee Stokowski, Dennis Ballinger, Kelly Frazer, David Cox, Richard Bruskiewich, C Robin Buell, Jan Leach, Hei Leung, Kenneth L McNally, Detlef Weigel and Gunnar Rätsch
    Citation: BMC Bioinformatics 2008 9(Suppl 10):O8

    This article is part of a Supplement: Volume 9 Supplement 10

  26. In this meeting report we give an overview of the talks and presentations from the Fourth International Society for Computational Biology (ISCB) Student Council Symposium held as part of the annual Intelligent...

    Authors: Lucia Peixoto, Nils Gehlenborg and Sarath Chandra Janga
    Citation: BMC Bioinformatics 2008 9(Suppl 10):I1

    This article is part of a Supplement: Volume 9 Supplement 10

  27. Inferring cluster structure in microarray datasets is a fundamental task for the so-called -omic sciences. It is also a fundamental question in Statistics, Data Analysis and Classification, in particular with ...

    Authors: Raffaele Giancarlo, Davide Scaturro and Filippo Utro
    Citation: BMC Bioinformatics 2008 9:462
  28. This paper presents the R/Bioconductor package minet (version 1.1.6) which provides a set of functions to infer mutual information networks from a dataset. Once fed with a microarray dataset, the package returns ...

    Authors: Patrick E Meyer, Frédéric Lafitte and Gianluca Bontempi
    Citation: BMC Bioinformatics 2008 9:461

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