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  1. Interpretation of simple microarray experiments is usually based on the fold-change of gene expression between a reference and a "treated" sample where the treatment can be of many types from drug exposure to ...

    Authors: Julie L Morrison, Rainer Breitling, Desmond J Higham and David R Gilbert
    Citation: BMC Bioinformatics 2005 6:233
  2. Gene expression microarrays are a prominent experimental tool in functional genomics which has opened the opportunity for gaining global, systems-level understanding of transcriptional networks. Experiments th...

    Authors: Ron Shamir, Adi Maron-Katz, Amos Tanay, Chaim Linhart, Israel Steinfeld, Roded Sharan, Yosef Shiloh and Ran Elkon
    Citation: BMC Bioinformatics 2005 6:232
  3. Baum-Welch training is an expectation-maximisation algorithm for training the emission and transition probabilities of hidden Markov models in a fully automated way. It can be employed as long as a training se...

    Authors: István Miklós and Irmtraud M Meyer
    Citation: BMC Bioinformatics 2005 6:231
  4. There is an increasing need for computer-generated models that can be used for explaining the emergence and predicting the behavior of multi-protein dynamic structures in cells. Multi-agent systems (MAS) have ...

    Authors: Hédi Soula, Céline Robardet, François Perrin, Sébastien Gripon, Guillaume Beslon and Olivier Gandrillon
    Citation: BMC Bioinformatics 2005 6:228
  5. Biological processes are carried out by coordinated modules of interacting molecules. As clustering methods demonstrate that genes with similar expression display increased likelihood of being associated with ...

    Authors: Cecily J Wolfe, Isaac S Kohane and Atul J Butte
    Citation: BMC Bioinformatics 2005 6:227
  6. Protein structure research often deals with the comparison of two or more structures of the same protein, for instance when handling alternative structure models for the same protein, point mutants, molecule m...

    Authors: Martin A Lema and Julian Echave
    Citation: BMC Bioinformatics 2005 6:226
  7. Dynamic programming is a widely used programming technique in bioinformatics. In sharp contrast to the simplicity of textbook examples, implementing a dynamic programming algorithm for a novel and non-trivial ...

    Authors: Peter Steffen and Robert Giegerich
    Citation: BMC Bioinformatics 2005 6:224

    The Erratum to this article has been published in BMC Bioinformatics 2006 7:214

  8. The cataloging of marine prokaryotic DNA sequences is a fundamental aspect for bioprospecting and also for the development of evolutionary and speciation models. However, large amount of DNA sequences used to ...

    Authors: Ravindra Pushker, Giuseppe D'Auria, Jose Carlos Alba-Casado and Francisco Rodríguez-Valera
    Citation: BMC Bioinformatics 2005 6:222
  9. We introduce GASH, a new, publicly accessible program for structural alignment and superposition. Alignments are scored by the Number of Equivalent Residues (NER), a quantitative measure of structural similarity ...

    Authors: Daron M Standley, Hiroyuki Toh and Haruki Nakamura
    Citation: BMC Bioinformatics 2005 6:221
  10. Tissue microarray (TMA) technology has been developed to facilitate large, genome-scale molecular pathology studies. This technique provides a high-throughput method for analyzing a large cohort of clinical sp...

    Authors: Archana Sharma-Oates, Philip Quirke and David R Westhead
    Citation: BMC Bioinformatics 2005 6:218
  11. Cells react to changing intra- and extracellular signals by dynamically modulating complex biochemical networks. Cellular responses to extracellular signals lead to changes in gene and protein expression. Sinc...

    Authors: Mansour Taghavi Azar Sharabiani, Markku Siermala, Tommi O Lehtinen and Mauno Vihinen
    Citation: BMC Bioinformatics 2005 6:215
  12. A typical microarray experiment has many sources of variation which can be attributed to biological and technical causes. Identifying sources of variation and assessing their magnitude, among other factors, ar...

    Authors: Stanislav O Zakharkin, Kyoungmi Kim, Tapan Mehta, Lang Chen, Stephen Barnes, Katherine E Scheirer, Rudolph S Parrish, David B Allison and Grier P Page
    Citation: BMC Bioinformatics 2005 6:214

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