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  1. 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
  2. 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
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  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
  9. 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
  10. 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
  11. 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
  12. 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
  13. 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
  14. 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
  15. 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
  16. 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
  17. 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

Annual Journal Metrics

  • Citation Impact 2023
    Journal Impact Factor: 4.0
    5-year Journal Impact Factor: 3.7
    Source Normalized Impact per Paper (SNIP): 1.413
    SCImago Journal Rank (SJR): 0.958

    Speed 2023
    Submission to first editorial decision (median days): 15
    Submission to acceptance (median days): 171

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