Skip to content

Advertisement

BioData Mining

Articles

Sort by
Previous Page Page 4 of 11 Next Page
  1. Content type: Methodology

    Machine learning methods and in particular random forests (RFs) are a promising alternative to standard single SNP analyses in genome-wide association studies (GWAS). RFs provide variable importance measures (...

    Authors: Silke Szymczak, Emily Holzinger, Abhijit Dasgupta, James D. Malley, Anne M. Molloy, James L. Mills, Lawrence C. Brody, Dwight Stambolian and Joan E. Bailey-Wilson

    Citation: BioData Mining 2016 9:7

    Published on:

  2. Content type: SOFTWARE ARTICLE

    To understand the molecular function of biopolymers, studying their structural characteristics is of central importance. Graphics programs are often utilized to conceive these properties, but with the increasi...

    Authors: Florian Heinke, Sebastian Bittrich, Florian Kaiser and Dirk Labudde

    Citation: BioData Mining 2016 9:6

    Published on:

  3. Content type: Short report

    Alzheimer’s disease (AD) is a neurodegenerative disease that causes dementia. While molecular basis of AD is not fully understood, genetic factors are expected to participate in the development and progression...

    Authors: Ailin Song, Jingwen Yan, Sungeun Kim, Shannon Leigh Risacher, Aaron K. Wong, Andrew J. Saykin, Li Shen and Casey S. Greene

    Citation: BioData Mining 2016 9:3

    Published on:

  4. Content type: SHORT REPORT

    Multi-gene lists and single sample predictor models have been currently used to reduce the multidimensional complexity of breast cancers, and to identify intrinsic subtypes. The perceived inability of some mod...

    Authors: Heloisa H. Milioli, Renato Vimieiro, Inna Tishchenko, Carlos Riveros, Regina Berretta and Pablo Moscato

    Citation: BioData Mining 2016 9:2

    Published on:

  5. Content type: Research

    Recent findings have reemphasized the importance of epistasis, or gene-gene interactions, as a contributing factor to the unexplained heritability of obesity. Network-based methods such as statistical epistasis n...

    Authors: Rishika De, Ting Hu, Jason H. Moore and Diane Gilbert-Diamond

    Citation: BioData Mining 2015 8:45

    Published on:

  6. Content type: Research

    The interaction effect among multiple genetic factors, i.e. epistasis, plays an important role in explaining susceptibility on common human diseases and phenotypic traits. The uncertainty over the number of ge...

    Authors: Ting Hu, Angeline S. Andrew, Margaret R. Karagas and Jason H. Moore

    Citation: BioData Mining 2015 8:43

    Published on:

  7. Content type: Research

    The genetic background to bipolar disorder (BPD) has been attributed to different genetic and genomic risk factors. In the present study we hypothesized that inherited copy number variations (CNVs) contribute ...

    Authors: Magnus Lekman, Robert Karlsson, Lisette Graae, Ola Hössjer and Ingrid Kockum

    Citation: BioData Mining 2015 8:42

    Published on:

  8. Content type: Research

    Despite heritability estimates of 40–70 % for obesity, less than 2 % of its variation is explained by Body Mass Index (BMI) associated loci that have been identified so far. Epistasis, or gene-gene interactions a...

    Authors: Rishika De, Shefali S. Verma, Fotios Drenos, Emily R. Holzinger, Michael V. Holmes, Molly A. Hall, David R. Crosslin, David S. Carrell, Hakon Hakonarson, Gail Jarvik, Eric Larson, Jennifer A. Pacheco, Laura J. Rasmussen-Torvik, Carrie B. Moore, Folkert W. Asselbergs, Jason H. Moore…

    Citation: BioData Mining 2015 8:41

    Published on:

  9. Content type: SOFTWARE ARTICLE

    The purpose of the MaxT algorithm is to provide a significance test algorithm that controls the family-wise error rate (FWER) during simultaneous hypothesis testing. However, the requirements in terms of compu...

    Authors: François Van Lishout, Francesco Gadaleta, Jason H. Moore, Louis Wehenkel and Kristel Van Steen

    Citation: BioData Mining 2015 8:36

    Published on:

  10. Content type: Research

    Racial/ethnic differences for commonly measured clinical variables are well documented, and it has been postulated that population-specific genetic factors may play a role. The genetic heterogeneity of admixed...

    Authors: Logan Dumitrescu, Nicole A. Restrepo, Robert Goodloe, Jonathan Boston, Eric Farber-Eger, Sarah A. Pendergrass, William S. Bush and Dana C. Crawford

    Citation: BioData Mining 2015 8:35

    Published on:

  11. Content type: Research

    Connectivity networks, which reflect multiple interactions between genes and proteins, possess not only a descriptive but also a predictive value, as new connections can be extrapolated and tested by means of ...

    Authors: Olga V. Valba, Sergei K. Nechaev, Mark G. Sterken, L. Basten Snoek, Jan E. Kammenga and Olga O. Vasieva

    Citation: BioData Mining 2015 8:33

    Published on:

  12. Content type: Research

    In cancer, large-scale technologies such as next-generation sequencing and microarrays have produced a wide number of genomic features such as DNA copy number alterations (CNA), mRNA expression (EXPR), microRN...

    Authors: Hugo Gómez-Rueda, Emmanuel Martínez-Ledesma, Antonio Martínez-Torteya, Rebeca Palacios-Corona and Victor Trevino

    Citation: BioData Mining 2015 8:32

    Published on:

  13. Content type: Research

    Diverse types of biological data, primary as well as derived, are available in various formats and are stored in heterogeneous resources. Database-specific as well as integrated search engines are available fo...

    Authors: Rajiv Karbhal, Sangeeta Sawant and Urmila Kulkarni-Kale

    Citation: BioData Mining 2015 8:31

    Published on:

    The Erratum to this article has been published in BioData Mining 2016 9:8

  14. Content type: Software article

    The identification of interaction networks between proteins and complexes holds the promise of offering novel insights into the molecular mechanisms that regulate many biological processes. With increasing vol...

    Authors: Syed Haider, Zoltan Lipinszki, Marcin R. Przewloka, Yaseen Ladak, Pier Paolo D’Avino, Yuu Kimata, Pietro Lio’ and David M. Glover

    Citation: BioData Mining 2015 8:30

    Published on:

  15. Content type: Research

    Modeling of the immune system – a highly non-linear and complex system – requires practical and efficient data analytic approaches. The immune system is composed of heterogeneous cell populations and hundreds ...

    Authors: Pinyi Lu, Vida Abedi, Yongguo Mei, Raquel Hontecillas, Stefan Hoops, Adria Carbo and Josep Bassaganya-Riera

    Citation: BioData Mining 2015 8:27

    Published on:

Previous Page Page 4 of 11 Next Page

2016 Journal Metrics

Advertisement