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BioData Mining

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  1. Content type: Methodology

    Gene expression microarray data have been organized and made available as public databases, but the utilization of such highly heterogeneous reference datasets in the interpretation of data from individual tes...

    Authors: Sami K Kilpinen, Kalle A Ojala and Olli P Kallioniemi

    Citation: BioData Mining 2011 4:5

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  2. Content type: Research

    Several methods have been presented for the analysis of complex interactions between genetic polymorphisms and/or environmental factors. Despite the available methods, there is still a need for alternative met...

    Authors: Thorsten Lehr, Jing Yuan, Dirk Zeumer, Supriya Jayadev and Marylyn D Ritchie

    Citation: BioData Mining 2011 4:4

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  3. Content type: Research

    Measurements on gene level are widely used to gain new insights in complex diseases e.g. cancer. A promising approach to understand basic biological mechanisms is to combine gene expression profiles and classi...

    Authors: Christian W Martin, Anika Tauchen, Anke Becker and Tim W Nattkemper

    Citation: BioData Mining 2011 4:2

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  4. Content type: Research

    The present knowledge of protein structures at atomic level derives from some 60,000 molecules. Yet the exponential ever growing set of hypothetical protein sequences comprises some 10 million chains and this ...

    Authors: Marco Vassura, Pietro Di Lena, Luciano Margara, Maria Mirto, Giovanni Aloisio, Piero Fariselli and Rita Casadio

    Citation: BioData Mining 2011 4:1

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  5. Content type: Software article

    Initial genome-wide association study (GWAS) discoveries are being further explored through the use of large cohorts across multiple and diverse populations involving meta-analyses within large consortia and n...

    Authors: Sarah A Pendergrass, Scott M Dudek, Dana C Crawford and Marylyn D Ritchie

    Citation: BioData Mining 2010 3:10

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  6. Content type: Methodology

    A fundamental goal of human genetics is the discovery of polymorphisms that predict common, complex diseases. It is hypothesized that complex diseases are due to a myriad of factors including environmental exp...

    Authors: Alison A Motsinger-Reif, Sushamna Deodhar, Stacey J Winham and Nicholas E Hardison

    Citation: BioData Mining 2010 3:8

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  7. Content type: Research

    Growing interest and burgeoning technology for discovering genetic mechanisms that influence disease processes have ushered in a flood of genetic association studies over the last decade, yet little heritabili...

    Authors: Stephen D Turner, Scott M Dudek and Marylyn D Ritchie

    Citation: BioData Mining 2010 3:5

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  8. Content type: Software article

    Massively parallel sequencing allows for genome-wide hypothesis-free investigation of for instance transcription factor binding sites or histone modifications. Although nucleotide resolution detailed informati...

    Authors: Stefan Enroth, Robin Andersson, Claes Wadelius and Jan Komorowski

    Citation: BioData Mining 2010 3:4

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  9. Content type: Research

    Scientific data integration and computational service discovery are challenges for the bioinformatic community. This process is made more difficult by the separate and independent construction of biological da...

    Authors: Rex T Nelson, Shulamit Avraham, Randy C Shoemaker, Gregory D May, Doreen Ware and Damian DG Gessler

    Citation: BioData Mining 2010 3:3

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  10. Content type: Research

    Affymetrix GeneChips utilize 25-mer oligonucleotides probes linked to a silica surface to detect targets in solution. Mismatches due to single nucleotide polymorphisms (SNPs) can affect the hybridization betwe...

    Authors: Fenghai Duan, Mark A Pauley, Eliot R Spindel, Li Zhang and Robert B Norgren Jr

    Citation: BioData Mining 2010 3:2

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  11. Content type: Review

    The quantities of data obtained by the new high-throughput technologies, such as microarrays or ChIP-Chip arrays, and the large-scale OMICS-approaches, such as genomics, proteomics and transcriptomics, are bec...

    Authors: Georgios A Pavlopoulos, Theodoros G Soldatos, Adriano Barbosa-Silva and Reinhard Schneider

    Citation: BioData Mining 2010 3:1

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  12. Content type: Research

    Protein families could be related to each other at broad levels that group them as superfamilies. These relationships are harder to detect at the sequence level due to high evolutionary divergence. Sequence se...

    Authors: Khader Shameer, Paramasivam Nagarajan, Kumar Gaurav and Ramanathan Sowdhamini

    Citation: BioData Mining 2009 2:8

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  13. Content type: Methodology

    Gene-centric analysis tools for genome-wide association study data are being developed both to annotate single locus statistics and to prioritize or group single nucleotide polymorphisms (SNPs) prior to analys...

    Authors: William S Bush, Guanhua Chen, Eric S Torstenson and Marylyn D Ritchie

    Citation: BioData Mining 2009 2:7

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  14. Content type: Methodology

    Genome-wide association studies are becoming the de facto standard in the genetic analysis of common human diseases. Given the complexity and robustness of biological networks such diseases are unlikely to be ...

    Authors: Casey S Greene, Nadia M Penrod, Jeff Kiralis and Jason H Moore

    Citation: BioData Mining 2009 2:5

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  15. Content type: Methodology

    Quality assessment methods, that are common place in engineering and industrial production, are not widely spread in large-scale proteomics experiments. But modern technologies such as Multi-Dimensional Liquid...

    Authors: Ole Schulz-Trieglaff, Egidijus Machtejevas, Knut Reinert, Hartmut Schlüter, Joachim Thiemann and Klaus Unger

    Citation: BioData Mining 2009 2:4

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  16. Content type: Research

    The fidelity of DNA replication serves as the nidus for both genetic evolution and genomic instability fostering disease. Single nucleotide polymorphisms (SNPs) constitute greater than 80% of the genetic varia...

    Authors: Eric Arehart, Scott Gleim, Bill White, John Hwa and Jason H Moore

    Citation: BioData Mining 2009 2:2

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