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  1. In the nervous system, the neurons communicate through synapses. The size, morphology, and connectivity of these synapses are significant in determining the functional properties of the neural network. Therefo...

    Authors: Qiwei Xie, Xi Chen, Hao Deng, Danqian Liu, Yingyu Sun, Xiaojuan Zhou, Yang Yang and Hua Han

    Citation: BioData Mining 2017 10:40

    Content type: Research

    Published on:

  2. Recent advances in nucleic acid sequencing technologies have led to a dramatic increase in the number of markers available to generate genetic linkage maps. This increased marker density can be used to improve...

    Authors: J. Grey Monroe, Zachariah A. Allen, Paul Tanger, Jack L. Mullen, John T. Lovell, Brook T. Moyers, Darrell Whitley and John K. McKay

    Citation: BioData Mining 2017 10:38

    Content type: Software article

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  3. Clustering plays a crucial role in several application domains, such as bioinformatics. In bioinformatics, clustering has been extensively used as an approach for detecting interesting patterns in genetic data...

    Authors: Luluah Alhusain and Alaaeldin M. Hafez

    Citation: BioData Mining 2017 10:37

    Content type: Methodology

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  4. The selection, development, or comparison of machine learning methods in data mining can be a difficult task based on the target problem and goals of a particular study. Numerous publicly available real-world ...

    Authors: Randal S. Olson, William La Cava, Patryk Orzechowski, Ryan J. Urbanowicz and Jason H. Moore

    Citation: BioData Mining 2017 10:36

    Content type: Research

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  5. Obesity is a medical condition that is known for increased body mass index (BMI). It is also associated with chronic low level inflammation. Obesity disrupts the immune-metabolic homeostasis by changing the se...

    Authors: Indrani Ray, Anindya Bhattacharya and Rajat K. De

    Citation: BioData Mining 2017 10:33

    Content type: Research

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  6. Detecting the differences in gene expression data is important for understanding the underlying molecular mechanisms. Although the differentially expressed genes are a large component, differences in correlati...

    Authors: Elpidio-Emmanuel Gonzalez-Valbuena and Víctor Treviño

    Citation: BioData Mining 2017 10:32

    Content type: Methodology

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  7. The ability of external investigators to reproduce published scientific findings is critical for the evaluation and validation of biomedical research by the wider community. However, a substantial proportion o...

    Authors: Spiros Denaxas, Kenan Direk, Arturo Gonzalez-Izquierdo, Maria Pikoula, Aylin Cakiroglu, Jason Moore, Harry Hemingway and Liam Smeeth

    Citation: BioData Mining 2017 10:31

    Content type: Review

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  8. Measuring how gene expression changes in the course of an experiment assesses how an organism responds on a molecular level. Sequencing of RNA molecules, and their subsequent quantification, aims to assess glo...

    Authors: Bork A. Berghoff, Torgny Karlsson, Thomas Källman, E. Gerhart H. Wagner and Manfred G. Grabherr

    Citation: BioData Mining 2017 10:30

    Content type: Research

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  9. The modeling of genetic interactions within a cell is crucial for a basic understanding of physiology and for applied areas such as drug design. Interactions in gene regulatory networks (GRNs) include effects ...

    Authors: Mina Moradi Kordmahalleh, Mohammad Gorji Sefidmazgi, Scott H. Harrison and Abdollah Homaifar

    Citation: BioData Mining 2017 10:29

    Content type: Methodology

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  10. BarraCUDA is an open source C program which uses the BWA algorithm in parallel with nVidia CUDA to align short next generation DNA sequences against a reference genome. Recently its source code was optimised u...

    Authors: W. B. Langdon and Brian Yee Hong Lam

    Citation: BioData Mining 2017 10:28

    Content type: Short Report

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  11. Non-coding RNA (ncRNA) are small non-coding sequences involved in gene expression regulation of many biological processes and diseases. The recent discovery of a large set of different ncRNAs with biologically...

    Authors: Antonino Fiannaca, Massimo La Rosa, Laura La Paglia, Riccardo Rizzo and Alfonso Urso

    Citation: BioData Mining 2017 10:27

    Content type: Research

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  12. The genetic etiology of human lipid quantitative traits is not fully elucidated, and interactions between variants may play a role. We performed a gene-centric interaction study for four different lipid traits...

    Authors: Emily R. Holzinger, Shefali S. Verma, Carrie B. Moore, Molly Hall, Rishika De, Diane Gilbert-Diamond, Matthew B. Lanktree, Nathan Pankratz, Antoinette Amuzu, Amber Burt, Caroline Dale, Scott Dudek, Clement E. Furlong, Tom R. Gaunt, Daniel Seung Kim, Helene Riess…

    Citation: BioData Mining 2017 10:25

    Content type: Research

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  13. Recently we surveyed the dark-proteome, i.e., regions of proteins never observed by experimental structure determination and inaccessible to homology modelling. Surprisingly, we found that most of the dark pro...

    Authors: Nelson Perdigão, Agostinho C. Rosa and Seán I. O’Donoghue

    Citation: BioData Mining 2017 10:24

    Content type: Software article

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  14. Refinement of candidate gene lists to select the most promising candidates for further experimental verification remains an essential step between high-throughput exploratory analysis and the discovery of spec...

    Authors: Artem Lysenko, Keith Anthony Boroevich and Tatsuhiko Tsunoda

    Citation: BioData Mining 2017 10:22

    Content type: Software article

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  15. Large-scale genetic studies of common human diseases have focused almost exclusively on the independent main effects of single-nucleotide polymorphisms (SNPs) on disease susceptibility. These studies have had ...

    Authors: Jason H. Moore, Peter C. Andrews, Randal S. Olson, Sarah E. Carlson, Curt R. Larock, Mario J. Bulhoes, James P. O’Connor, Ellen M. Greytak and Steven L. Armentrout

    Citation: BioData Mining 2017 10:19

    Content type: Methodology

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  16. Genetic studies for complex diseases have predominantly discovered main effects at individual loci, but have not focused on genomic and environmental contexts important for a phenotype. Gene Set Enrichment Ana...

    Authors: Vinicius Tragante, Johannes M. I. H. Gho, Janine F. Felix, Ramachandran S. Vasan, Nicholas L. Smith, Benjamin F. Voight, Colin Palmer, Pim van der Harst, Jason H. Moore and Folkert W. Asselbergs

    Citation: BioData Mining 2017 10:18

    Content type: Methodology

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  17. Every year around 300 Gl of vinasse, a by-product of ethanol distillation in sugarcane mills, are flushed into more than 9 Mha of sugarcane cropland in Brazil. This practice links fermentation waste management...

    Authors: Lucas P. P. Braga, Rafael F. Alves, Marina T. F. Dellias, Acacio A. Navarrete, Thiago O. Basso and Siu M. Tsai

    Citation: BioData Mining 2017 10:17

    Content type: Short report

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  18. Any family of learning machines can be combined into a single learning machine using various methods with myriad degrees of usefulness.

    Authors: Bilguunzaya Battogtokh, Majid Mojirsheibani and James Malley

    Citation: BioData Mining 2017 10:16

    Content type: Research

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  19. Reverse engineering of gene regulatory networks (GRNs) from gene expression data is a classical challenge in systems biology. Thanks to high-throughput technologies, a massive amount of gene-expression data ha...

    Authors: Ngoc C. Pham, Benjamin Haibe-Kains, Pau Bellot, Gianluca Bontempi and Patrick E. Meyer

    Citation: BioData Mining 2017 10:15

    Content type: Methodology

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  20. Large number of features are extracted from protein crystallization trial images to improve the accuracy of classifiers for predicting the presence of crystals or phases of the crystallization process. The exc...

    Authors: Madhav Sigdel, Imren Dinc, Madhu S. Sigdel, Semih Dinc, Marc L. Pusey and Ramazan S. Aygun

    Citation: BioData Mining 2017 10:14

    Content type: Research

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  21. A computational evolution system (CES) is a knowledge discovery engine that can identify subtle, synergistic relationships in large datasets. Pareto optimization allows CESs to balance accuracy with model comp...

    Authors: Nathaniel M. Crabtree, Jason H. Moore, John F. Bowyer and Nysia I. George

    Citation: BioData Mining 2017 10:13

    Content type: Methodology

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  22. In metabolomics, thousands of substances can be detected in a single assay. This capacity motivates the development of metabolomics testing, which is currently a very promising option for improving laboratory ...

    Authors: Petr G. Lokhov, Dmitri L. Maslov, Oleg N. Kharibin, Elena E. Balashova and Alexander I. Archakov

    Citation: BioData Mining 2017 10:10

    Content type: Methodology

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  23. Genetic predispositions to diseases populate the noncoding regions of the human genome. Delineating their functional basis can inform on the mechanisms contributing to disease development. However, this remain...

    Authors: Musaddeque Ahmed, Richard C. Sallari, Haiyang Guo, Jason H. Moore, Housheng Hansen He and Mathieu Lupien

    Citation: BioData Mining 2017 10:9

    Content type: Methodology

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  24. Capturing complete medical knowledge is challenging-often due to incomplete patient Electronic Health Records (EHR), but also because of valuable, tacit medical knowledge hidden away in physicians’ experiences...

    Authors: Hossein Mohammadhassanzadeh, William Van Woensel, Samina Raza Abidi and Syed Sibte Raza Abidi

    Citation: BioData Mining 2017 10:7

    Content type: Methodology

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  25. Aldolase A (ALDOA) is one of the glycolytic enzymes primarily found in the developing embryo and adult muscle. Recently, a new role of ALDOA in several cancers has been proposed. However, the underlying mechan...

    Authors: Fan Zhang, Jie-Diao Lin, Xiao-Yu Zuo, Yi-Xuan Zhuang, Chao-Qun Hong, Guo-Jun Zhang, Xiao-Jiang Cui and Yu-Kun Cui

    Citation: BioData Mining 2017 10:6

    Content type: Research

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  26. In gene set analysis, the researchers are interested in determining the gene sets that are significantly correlated with an outcome, e.g. disease status or treatment. With the rapid development of high through...

    Authors: Xing Ren, Qiang Hu, Song Liu, Jianmin Wang and Jeffrey C. Miecznikowski

    Citation: BioData Mining 2017 10:5

    Content type: Methodology

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  27. With the development of high-throughput technology, the researchers can acquire large number of expression data with different types from several public databases. Because most of these data have small number ...

    Authors: Wei Du, Zhongbo Cao, Tianci Song, Ying Li and Yanchun Liang

    Citation: BioData Mining 2017 10:4

    Content type: Methodology

    Published on:

  28. Of late, high-throughput microarray and sequencing data have been extensively used to monitor biomarkers and biological processes related to many diseases. Under this circumstance, the support vector machine (...

    Authors: SungHwan Kim, Jae-Hwan Jhong, JungJun Lee and Ja-Yong Koo

    Citation: BioData Mining 2017 10:2

    Content type: Methodology

    Published on:

    The Erratum to this article has been published in BioData Mining 2017 10:8

  29. The Interaction Network Ontology (INO) logically represents biological interactions, pathways, and networks. INO has been demonstrated to be valuable in providing a set of structured ontological terms and asso...

    Authors: Arzucan Özgür, Junguk Hur and Yongqun He

    Citation: BioData Mining 2016 9:41

    Content type: Research

    Published on:

  30. Bladder cancer is common disease with a complex etiology that is likely due to many different genetic and environmental factors. The goal of this study was to embrace this complexity using a bioinformatics ana...

    Authors: Samantha Cheng, Angeline S. Andrew, Peter C. Andrews and Jason H. Moore

    Citation: BioData Mining 2016 9:40

    Content type: Short report

    Published on:

  31. Continuous improvements in next generation sequencing technologies led to ever-increasing collections of genomic sequences, which have not been easily characterized by biologists, and whose analysis requires h...

    Authors: Giulia Fiscon, Emanuel Weitschek, Eleonora Cella, Alessandra Lo Presti, Marta Giovanetti, Muhammed Babakir-Mina, Marco Ciotti, Massimo Ciccozzi, Alessandra Pierangeli, Paola Bertolazzi and Giovanni Felici

    Citation: BioData Mining 2016 9:38

    Content type: Research

    Published on:

  32. An imbalanced dataset is defined as a training dataset that has imbalanced proportions of data in both interesting and uninteresting classes. Often in biomedical applications, samples from the stimulating clas...

    Authors: Jinyan Li, Simon Fong, Yunsick Sung, Kyungeun Cho, Raymond Wong and Kelvin K. L. Wong

    Citation: BioData Mining 2016 9:37

    Content type: Research

    Published on:

  33. Biomarker discovery methods are essential to identify a minimal subset of features (e.g., serum markers in predictive medicine) that are relevant to develop prediction models with high accuracy. By now, there ...

    Authors: Ursula Neumann, Mona Riemenschneider, Jan-Peter Sowa, Theodor Baars, Julia Kälsch, Ali Canbay and Dominik Heider

    Citation: BioData Mining 2016 9:36

    Content type: Research

    Published on:

  34. High-throughput sequencing technology and bioinformatics have identified chimeric RNAs (chRNAs), raising the possibility of chRNAs expressing particularly in diseases can be used as potential biomarkers in bot...

    Authors: Sacha Beaumeunier, Jérôme Audoux, Anthony Boureux, Florence Ruffle, Thérèse Commes, Nicolas Philippe and Ronnie Alves

    Citation: BioData Mining 2016 9:34

    Content type: Research

    Published on:

  35. A low-mass-ion discriminant equation (LOME) was constructed to investigate whether systematic low-mass-ion (LMI) profiling could be applied to ovarian cancer (OVC) screening.

    Authors: Jun Hwa Lee, Byong Chul Yoo, Yun Hwan Kim, Sun-A Ahn, Seung-Gu Yeo, Jae Youl Cho, Kyung-Hee Kim and Seung Cheol Kim

    Citation: BioData Mining 2016 9:32

    Content type: Research

    Published on:

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