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  2. 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

    Content type: Research

    Published on:

  3. 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

    Content type: Methodology

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  5. 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

    Content type: Methodology

    Published on:

  6. 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

    Content type: Methodology

    Published on:

  8. 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

    Content type: Research

    Published on:

  10. The analysis and interpretation of relationships between biological molecules, networks and concepts is becoming a major bottleneck in systems biology. Very often the pure amount of data and their heterogeneit...

    Authors: Georgios A Pavlopoulos, Anna-Lynn Wegener and Reinhard Schneider

    Citation: BioData Mining 2008 1:12

    Content type: Review

    Published on:

  11. Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations wit...

    Authors: Kristian Ovaska, Marko Laakso and Sampsa Hautaniemi

    Citation: BioData Mining 2008 1:11

    Content type: Software article

    Published on:

  12. Dysfunction in the endolysosome, a late endosomal to lysosomal degradative intracellular compartment, is an early hallmark of some neurodegenerative diseases, in particular Alzheimer's disease. However, the su...

    Authors: Saravana K Kumarasamy, Yunshi Wang, Vignesh Viswanathan and Rachel S Kraut

    Citation: BioData Mining 2008 1:10

    Content type: Methodology

    Published on:

  14. The tissue specificity of gene expression has been linked to a number of significant outcomes including level of expression, and differential rates of polymorphism, evolution and disease association. Recent st...

    Authors: Antonio Reverter, Aaron Ingham and Brian P Dalrymple

    Citation: BioData Mining 2008 1:8

    Content type: Research

    Published on:

  16. Evolutionary search algorithms have become an essential asset in the algorithmic toolbox for solving high-dimensional optimization problems in across a broad range of bioinformatics problems. Genetic algorithm...

    Authors: Rubén Armañanzas, Iñaki Inza, Roberto Santana, Yvan Saeys, Jose Luis Flores, Jose Antonio Lozano, Yves Van de Peer, Rosa Blanco, Víctor Robles, Concha Bielza and Pedro Larrañaga

    Citation: BioData Mining 2008 1:6

    Content type: Review

    Published on:

  17. Serial analysis of gene expression (SAGE) is one of the most powerful tools for global gene expression profiling. It has led to several biological discoveries and biomedical applications, such as the predictio...

    Authors: Haiying Wang, Huiru Zheng and Francisco Azuaje

    Citation: BioData Mining 2008 1:5

    Content type: Review

    Published on:

  18. Contrary to the traditional biology approach, where the expression patterns of a handful of genes are studied at a time, microarray experiments enable biologists to study the expression patterns of many genes ...

    Authors: Qicheng Ma, Gung-Wei Chirn, Joseph D Szustakowski, Adel Bakhtiarova, Penelope A Kosinski, Daniel Kemp and Nanguneri Nirmala

    Citation: BioData Mining 2008 1:4

    Content type: Methodology

    Published on:

  20. Comorbidity of Major Depressive Disorder (depression) and Alcohol Use Disorders (AUD) is well documented. Depression, AUD, and the comorbidity of depression with AUD show evidence of genetic and environmental ...

    Authors: Richard C McEachin, Benjamin J Keller, Erika FH Saunders and Melvin G McInnis

    Citation: BioData Mining 2008 1:2

    Content type: Research

    Published on:

  21. This editorial introduces BioData Mining, a new journal which publishes research articles related to advances in computational methods and techniques for the extraction of useful knowledge from heterogeneous biol...

    Authors: Jesús S Aguilar-Ruiz, Jason H Moore and Marylyn D Ritchie

    Citation: BioData Mining 2008 1:1

    Content type: Editorial

    Published on:

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ISSN: 1756-0381