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Volume 11 Supplement 9

Selected Proceedings of the 2010 AMIA Summit on Translational Bioinformatics


Edited by Eneida A Mendoça

2010 AMIA Summit on Translational Bioinformatics.

San Francisco, CA, USA10-12 March 2010

  1. Identification of expression quantitative trait loci (eQTLs) is an emerging area in genomic study. The task requires an integrated analysis of genome-wide single nucleotide polymorphism (SNP) data and gene exp...

    Authors: Hsun-Hsien Chang, Michael McGeachie, Gil Alterovitz and Marco F Ramoni
    Citation: BMC Bioinformatics 2010 11(Suppl 9):S2
  2. Given the rapid growth of translational research and personalized healthcare paradigms, the ability to relate and reason upon networks of bio-molecular and phenotypic variables at various levels of granularity...

    Authors: Philip RO Payne, Kun Huang, Kristin Keen-Circle, Abhisek Kundu, Jie Zhang and Tara B Borlawsky
    Citation: BMC Bioinformatics 2010 11(Suppl 9):S3
  3. Diagnosis and treatment of patients in the clinical setting is often driven by known symptomatic factors that distinguish one particular condition from another. Treatment based on noticeable symptoms, however,...

    Authors: David P Chen, Joel T Dudley and Atul J Butte
    Citation: BMC Bioinformatics 2010 11(Suppl 9):S4
  4. Chronic lymphocytic leukemia (CLL) is the most common adult leukemia. It is a highly heterogeneous disease, and can be divided roughly into indolent and progressive stages based on classic clinical markers. Im...

    Authors: Jie Zhang, Yang Xiang, Liya Ding, Kristin Keen-Circle, Tara B Borlawsky, Hatice Gulcin Ozer, Ruoming Jin, Philip Payne and Kun Huang
    Citation: BMC Bioinformatics 2010 11(Suppl 9):S5
  5. Combining the results of studies using highly parallelized measurements of gene expression such as microarrays and RNAseq offer unique challenges in meta analysis. Motivated by a need for a deeper understandin...

    Authors: Alexander A Morgan, Purvesh Khatri, Richard Hayden Jones, Minnie M Sarwal and Atul J Butte
    Citation: BMC Bioinformatics 2010 11(Suppl 9):S6
  6. A key challenge in pharmacogenomics is the identification of genes whose variants contribute to drug response phenotypes, which can include severe adverse effects. Pharmacogenomics GWAS attempt to elucidate ge...

    Authors: Nicholas P Tatonetti, Joel T Dudley, Hersh Sagreiya, Atul J Butte and Russ B Altman
    Citation: BMC Bioinformatics 2010 11(Suppl 9):S9
  7. In pursuing personalized medicine, pharmacogenomic (PGx) knowledge may help guide prescribing drugs based on a person’s genotype. Here we evaluate the feasibility of incorporating PGx knowledge, combined with ...

    Authors: Casey Lynnette Overby, Peter Tarczy-Hornoch, James I Hoath, Ira J Kalet and David L Veenstra
    Citation: BMC Bioinformatics 2010 11(Suppl 9):S10
  8. Mouse xenograft models, in which human cancer cells are implanted in immune-suppressed mice, have been popular for studying the mechanisms of novel therapeutic targets, tumor progression and metastasis. We hyp...

    Authors: Xinan Yang, Younghee Lee, Yong Huang, James L Chen, Rosie H Xing and Yves A Lussier
    Citation: BMC Bioinformatics 2010 11(Suppl 9):S11
  9. In humans, copies of the Long Interspersed Nuclear Element 1 (LINE-1) retrotransposon comprise 21% of the reference genome, and have been shown to modulate expression and produce novel splice isoforms of trans...

    Authors: Eric Rouchka, Diego E Montoya-Durango, Vilius Stribinskis, Kenneth Ramos and Ted Kalbfleisch
    Citation: BMC Bioinformatics 2010 11(Suppl 9):S12

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