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  1. Redundant hierarchical relations refer to such patterns as two paths from one concept to another, one with length one (direct) and the other with length greater than one (indirect). Each redundant relation rep...

    Authors: Guangming Xing, Guo-Qiang Zhang and Licong Cui

    Citation: BioData Mining 2016 9:31

    Content type: Research

    Published on:

  2. Modern cohort studies include self-reported measures on disease, behavior and lifestyle, sensor-based observations from mobile phones and wearables, and rich -omics data. Follow-up is often achieved through el...

    Authors: Spiros C. Denaxas, Folkert W. Asselbergs and Jason H. Moore

    Citation: BioData Mining 2016 9:29

    Content type: Editorial

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  3. Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the si...

    Authors: Nicola Lazzarini, Paweł Widera, Stuart Williamson, Rakesh Heer, Natalio Krasnogor and Jaume Bacardit

    Citation: BioData Mining 2016 9:28

    Content type: Methodology

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  4. BioBin is a bioinformatics software package developed to automate the process of binning rare variants into groups for statistical association analysis using a biological knowledge-driven framework. BioBin col...

    Authors: Carrie Colleen Buchanan Moore, Anna Okula Basile, John Robert Wallace, Alex Thomas Frase and Marylyn DeRiggi Ritchie

    Citation: BioData Mining 2016 9:27

    Content type: Software article

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  5. Mass spectrometry (MS) are a group of a high-throughput techniques used to increase knowledge about biomolecules. They produce a large amount of data which is presented as a list of hundreds or thousands of pr...

    Authors: Pau M. Muñoz-Torres, Filip Rokć, Robert Belužic, Ivana Grbeša and Oliver Vugrek

    Citation: BioData Mining 2016 9:26

    Content type: SOFTWARE ARTICLE

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  6. Heterogeneous biological data such as sequence matches, gene expression correlations, protein-protein interactions, and biochemical pathways can be merged and analyzed via graphs, or networks. Existing softwar...

    Authors: Jennifer Chang, Hyejin Cho and Hui-Hsien Chou

    Citation: BioData Mining 2016 9:25

    Content type: SOFTWARE ARTICLE

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  7. Technological advances enable the cost-effective acquisition of Multi-Modal Data Sets (MMDS) composed of measurements for multiple, high-dimensional data types obtained from a common set of bio-samples. The joint...

    Authors: Gordon Okimoto, Ashkan Zeinalzadeh, Tom Wenska, Michael Loomis, James B. Nation, Tiphaine Fabre, Maarit Tiirikainen, Brenda Hernandez, Owen Chan, Linda Wong and Sandi Kwee

    Citation: BioData Mining 2016 9:24

    Content type: Methodology

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  8. Systems biology experiments generate large volumes of data of multiple modalities and this information presents a challenge for integration due to a mix of complexity together with rich semantics. Here, we des...

    Authors: Artem Lysenko, Irina A. Roznovăţ, Mansoor Saqi, Alexander Mazein, Christopher J Rawlings and Charles Auffray

    Citation: BioData Mining 2016 9:23

    Content type: Review

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  9. Genomic alterations affecting drug target proteins occur in several tumor types and are prime candidates for patient-specific tailored treatments. Increasingly, patients likely to benefit from targeted cancer ...

    Authors: Riku Louhimo, Marko Laakso, Denis Belitskin, Juha Klefström, Rainer Lehtonen and Sampsa Hautaniemi

    Citation: BioData Mining 2016 9:21

    Content type: Research

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  10. Large-scale sequencing experiments are complex and require a wide spectrum of computational tools to extract and interpret relevant biological information. This is especially true in projects where individual ...

    Authors: Katherine Icay, Ping Chen, Alejandra Cervera, Ville Rantanen, Rainer Lehtonen and Sampsa Hautaniemi

    Citation: BioData Mining 2016 9:20

    Content type: SOFTWARE ARTICLE

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  11. Real Time Cell Analysis (RTCA) technology is used to monitor cellular changes continuously over the entire exposure period. Combining with different testing concentrations, the profiles have potential in probi...

    Authors: Yile Zhang, Yau Shu Wong, Jian Deng, Cristina Anton, Stephan Gabos, Weiping Zhang, Dorothy Yu Huang and Can Jin

    Citation: BioData Mining 2016 9:19

    Content type: Research

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  12. The future of medicine is moving towards the phase of precision medicine, with the goal to prevent and treat diseases by taking inter-individual variability into account. A large part of the variability lies i...

    Authors: Ruowang Li, Scott M. Dudek, Dokyoon Kim, Molly A. Hall, Yuki Bradford, Peggy L. Peissig, Murray H. Brilliant, James G. Linneman, Catherine A. McCarty, Le Bao and Marylyn D. Ritchie

    Citation: BioData Mining 2016 9:18

    Content type: Methodology

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  13. High-throughput or next-generation sequencing (NGS) technologies have become an established and affordable experimental framework in biological and medical sciences for all basic and translational research. Pr...

    Authors: Franco Milicchio, Rebecca Rose, Jiang Bian, Jae Min and Mattia Prosperi

    Citation: BioData Mining 2016 9:16

    Content type: Review

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  14. Biomedical informatics has become a central focus for many academic medical centers and universities as biomedical research because increasingly reliant on the processing, analysis, and interpretation of large...

    Authors: Jason H. Moore and John H. Holmes

    Citation: BioData Mining 2016 9:15

    Content type: Editorial

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  15. Gene isoforms are commonly found in both prokaryotes and eukaryotes. Since each isoform may perform a specific function in response to changing environmental conditions, studying the dynamics of gene isoforms ...

    Authors: Ma Liang, Castle Raley, Xin Zheng, Geetha Kutty, Emile Gogineni, Brad T. Sherman, Qiang Sun, Xiongfong Chen, Thomas Skelly, Kristine Jones, Robert Stephens, Bin Zhou, William Lau, Calvin Johnson, Tomozumi Imamichi, Minkang Jiang…

    Citation: BioData Mining 2016 9:13

    Content type: Methodology

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  16. Genetic studies of human diseases have identified many variants associated with pathogenesis and severity. However, most studies have used only statistical association to assess putative relationships to disea...

    Authors: Minjun Huang, Britney E. Graham, Ge Zhang, Reed Harder, Nuri Kodaman, Jason H. Moore, Louis Muglia and Scott M. Williams

    Citation: BioData Mining 2016 9:12

    Content type: Methodology

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  17. study of mapping and interaction of co-localized proteins at a sub-cellular level is important for understanding complex biological phenomena. One of the recent techniques to map co-localized proteins is to us...

    Authors: Shan E Ahmed Raza, Daniel Langenkämper, Korsuk Sirinukunwattana, David Epstein, Tim W. Nattkemper and Nasir M. Rajpoot

    Citation: BioData Mining 2016 9:11

    Content type: Research

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  18. Antiretroviral therapy is essential for human immunodeficiency virus (HIV) infected patients to inhibit viral replication and therewith to slow progression of disease and prolong a patient’s life. However, the...

    Authors: Mona Riemenschneider, Robin Senge, Ursula Neumann, Eyke Hüllermeier and Dominik Heider

    Citation: BioData Mining 2016 9:10

    Content type: SHORT REPORT

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  19. 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

    Content type: Methodology

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  20. 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

    Content type: SOFTWARE ARTICLE

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  21. 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

    Content type: Short report

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  22. 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

    Content type: SHORT REPORT

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  23. 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

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  24. 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

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  25. 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

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  26. 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:

  27. 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:

  28. 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:

  29. 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:

  30. 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

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  31. 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

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

  32. 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:

  33. 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:

  34. 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:

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