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BioData Mining

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  1. Content type: Research

    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

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  2. Content type: Methodology

    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

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  3. Content type: Research

    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

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  4. Content type: Methodology

    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

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  5. Content type: Methodology

    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

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  6. Content type: Methodology

    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

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  7. Content type: Methodology

    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

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  8. Content type: Research

    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

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  9. Content type: Methodology

    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

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  10. Content type: Methodology

    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

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  11. Content type: Methodology

    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

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

  12. Content type: Research

    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

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  13. Content type: Short report

    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

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  14. Content type: Research

    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

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  15. Content type: Research

    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

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  16. Content type: Research

    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

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  17. Content type: Research

    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

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