Skip to main content

Articles

Page 4 of 7

  1. 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

    Content type: Research

    Published on:

  2. 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

    Content type: Research

    Published on:

  3. 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

    Content type: Research

    Published on:

  4. 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

    Content type: Research

    Published on:

  5. 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

    Content type: SOFTWARE ARTICLE

    Published on:

  6. 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

    Content type: Research

    Published on:

  7. 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

    Content type: Research

    Published on:

  8. 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

    Content type: Research

    Published on:

  9. 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

    Content type: Research

    Published on:

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

  10. 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

    Content type: Software article

    Published on:

  11. 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

    Content type: Research

    Published on:

  12. Molecular networks act as the backbone of molecular activities within cells, offering a unique opportunity to better understand the mechanism of diseases. While network data usually constitute only static netw...

    Authors: Yuji Zhang

    Citation: BioData Mining 2015 8:26

    Content type: Research

    Published on:

  13. Although principal component analysis (PCA) is widely used for the dimensional reduction of biomedical data, interpretation of PCA results remains daunting. Most existing interpretation methods attempt to expl...

    Authors: H. Robert Frost, Zhigang Li and Jason H. Moore

    Citation: BioData Mining 2015 8:25

    Content type: Methodology

    Published on:

  14. Biological data mining is a powerful tool that can provide a wealth of information about patterns of genetic and genomic biomarkers of health and disease. A potential disadvantage of data mining is volume and ...

    Authors: Talia L. Weiss, Amanda Zieselman, Douglas P. Hill, Solomon G. Diamond, Li Shen, Andrew J. Saykin and Jason H. Moore

    Citation: BioData Mining 2015 8:22

    Content type: Review

    Published on:

  15. Microbial communities adapt to environmental conditions for optimizing metabolic flux. Such adaption may include cooperative mechanisms eventually resulting in phenotypic observables as emergent properties tha...

    Authors: Magnus Bosse, Alexander Heuwieser, Andreas Heinzel, Ivan Nancucheo, Hivana Melo Barbosa Dall’Agnol, Arno Lukas, George Tzotzos and Bernd Mayer

    Citation: BioData Mining 2015 8:21

    Content type: Research

    Published on:

  16. Taxanes are naturally occurring compounds which belong to a powerful group of chemotherapeutic drugs with anticancer properties. Their current use, clinical efficacy, and unique mechanism of action indicate th...

    Authors: Kasi Murugan, Sangeetha Shanmugasamy, Saleh Al-Sohaibani, Naga Vignesh, Kandavel Palanikannan, Antonydhason Vimala and Gopal Ramesh Kumar

    Citation: BioData Mining 2015 8:19

    Content type: Methodology

    Published on:

  17. The study of interactions between molecules belonging to different biochemical families (such as lipids and nucleic acids) requires specialized data analysis methods. This article describes the DNA Microarray ...

    Authors: Tomasz Waller, Tomasz Gubała, Krzysztof Sarapata, Monika Piwowar and Wiktor Jurkowski

    Citation: BioData Mining 2015 8:18

    Content type: Software article

    Published on:

  18. In genome-wide studies, hundreds of thousands of hypothesis tests are performed simultaneously. Bonferroni correction and False Discovery Rate (FDR) can effectively control type I error but often yield a high ...

    Authors: Jiang Gui, Casey S. Greene, Con Sullivan, Walter Taylor, Jason H. Moore and Carol Kim

    Citation: BioData Mining 2015 8:17

    Content type: Methodology

    Published on:

  19. Biorepositories linked to de-identified electronic medical records (EMRs) have the potential to complement traditional epidemiologic studies in genotype-phenotype studies of complex human diseases and traits. ...

    Authors: Logan Dumitrescu, Robert Goodloe, Yukiko Bradford, Eric Farber-Eger, Jonathan Boston and Dana C Crawford

    Citation: BioData Mining 2015 8:15

    Content type: Research

    Published on:

  20. Accurate identification of linear B-cell epitopes plays an important role in peptide vaccine designs, immunodiagnosis, and antibody productions. Although several prediction methods have been reported, unsatisf...

    Authors: Weike Shen, Yuan Cao, Lei Cha, Xufei Zhang, Xiaomin Ying, Wei Zhang, Kun Ge, Wuju Li and Li Zhong

    Citation: BioData Mining 2015 8:14

    Content type: Research

    Published on:

  21. To facilitate the implementation of the Family Smoking Prevention and Tobacco Control Act of 2009, the Federal Drug Agency (FDA) Center for Tobacco Products (CTP) has identified research priorities under the u...

    Authors: Dingcheng Li, Janet Okamoto, Hongfang Liu and Scott Leischow

    Citation: BioData Mining 2015 8:11

    Content type: Research

    Published on:

  22. One of the most challenging tasks in genomic analysis nowadays is metagenomics. Biomedical applications of metagenomics give rise to datasets containing hundreds and thousands of samples from various body site...

    Authors: Dmitry Alexeev, Tanya Bibikova, Boris Kovarsky, Damir Melnikov, Alexander Tyakht and Vadim Govorun

    Citation: BioData Mining 2015 8:10

    Content type: Methodology

    Published on:

  23. Pharmacogenomics (PGx) as an emerging field, is poised to change the way we practice medicine and deliver health care by customizing drug therapies on the basis of each patient’s genetic makeup. A large volume...

    Authors: Liwei Wang, Hongfang Liu, Christopher G Chute and Qian Zhu

    Citation: BioData Mining 2015 8:9

    Content type: Research

    Published on:

  24. Whether your interests lie in scientific arenas, the corporate world, or in government, you have certainly heard the praises of big data: Big data will give you new insights, allow you to become more efficient...

    Authors: Xiuzhen Huang, Steven F Jennings, Barry Bruce, Alison Buchan, Liming Cai, Pengyin Chen, Carole L Cramer, Weihua Guan, Uwe KK Hilgert, Hongmei Jiang, Zenglu Li, Gail McClure, Donald F McMullen, Bindu Nanduri, Andy Perkins, Bhanu Rekepalli…

    Citation: BioData Mining 2015 8:7

    Content type: Editorial

    Published on:

  25. Biological insights into group differences, such as disease status, have been achieved through differential co-expression analysis of microarray data. Additional understanding of group differences may be achie...

    Authors: Caleb A Lareau, Bill C White, Ann L Oberg and Brett A McKinney

    Citation: BioData Mining 2015 8:5

    Content type: Research

    Published on:

  26. The prediction of solvent accessibility could provide valuable clues for analyzing protein structure and functions, such as protein 3-Dimensional structure and B-cell epitope prediction. To fully decipher the ...

    Authors: Jian Zhang, Wenhan Chen, Pingping Sun, Xiaowei Zhao and Zhiqiang Ma

    Citation: BioData Mining 2015 8:3

    Content type: Research

    Published on:

  27. We develop a new concept that reflects how genes are connected based on microarray data using the coefficient of determination (the squared Pearson correlation coefficient). Our gene rank combines a priori kno...

    Authors: Eugene Demidenko

    Citation: BioData Mining 2015 8:2

    Content type: Research

    Published on:

  28. The discovery of breast cancer subtypes and subsequent development of treatments aimed at them has allowed for a great reduction in the mortality of breast cancer. But despite this progress, tumors with simila...

    Authors: Nima Pouladi, Richard Cowper-Sallari and Jason H Moore

    Citation: BioData Mining 2014 7:27

    Content type: Research

    Published on:

  29. Identifying genetic interactions in data obtained from genome-wide association studies (GWASs) can help in understanding the genetic basis of complex diseases. The large number of single nucleotide polymorphis...

    Authors: Charalampos S Floudas, Nara Um, M Ilyas Kamboh, Michael M Barmada and Shyam Visweswaran

    Citation: BioData Mining 2014 7:35

    Content type: Methodology

    Published on:

  30. Using a collection of different terminal nodesize constructed random forests, each generating a synthetic feature, a synthetic random forest is defined as a kind of hyperforest, calculated using the new input ...

    Authors: Hemant Ishwaran and James D Malley

    Citation: BioData Mining 2014 7:28

    Content type: Methodology

    Published on:

  31. Human genomic variations, including single nucleotide polymorphisms (SNPs) and copy number variations (CNVs), are associated with several phenotypic traits varying from mild features to hereditary diseases. Se...

    Authors: Kirsti Laurila, Reija Autio, Lingjia Kong, Elisa Närvä, Samer Hussein, Timo Otonkoski, Riitta Lahesmaa and Harri Lähdesmäki

    Citation: BioData Mining 2014 7:32

    Content type: Research

    Published on:

Annual Journal Metrics