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  1. Methodology

    Label-free data standardization for clinical metabolomics

    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 ...

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

    BioData Mining 2017 10:10

    Published on: 28 February 2017

  2. Methodology

    Semantics-based plausible reasoning to extend the knowledge coverage of medical knowledge bases for improved clinical decision support

    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...

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

    BioData Mining 2017 10:7

    Published on: 10 February 2017

  3. Research

    Elevated transcriptional levels of aldolase A (ALDOA) associates with cell cycle-related genes in patients with NSCLC and several solid tumors

    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...

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

    BioData Mining 2017 10:6

    Published on: 7 February 2017

  4. Methodology

    Gene set analysis controlling for length bias in RNA-seq experiments

    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...

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

    BioData Mining 2017 10:5

    Published on: 6 February 2017

  5. Methodology

    Meta-analytic support vector machine for integrating multiple omics data

    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 (...

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

    BioData Mining 2017 10:2

    Published on: 26 January 2017

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

  6. Short report

    Complex systems analysis of bladder cancer susceptibility reveals a role for decarboxylase activity in two genome-wide association studies

    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...

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

    BioData Mining 2016 9:40

    Published on: 12 December 2016

  7. Research

    MISSEL: a method to identify a large number of small species-specific genomic subsequences and its application to viruses classification

    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...

    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

    BioData Mining 2016 9:38

    Published on: 6 December 2016

  8. Research

    Adaptive swarm cluster-based dynamic multi-objective synthetic minority oversampling technique algorithm for tackling binary imbalanced datasets in biomedical data classification

    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...

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

    BioData Mining 2016 9:37

    Published on: 1 December 2016

  9. Research

    Compensation of feature selection biases accompanied with improved predictive performance for binary classification by using a novel ensemble feature selection approach

    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 ...

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

    BioData Mining 2016 9:36

    Published on: 18 November 2016

  10. Research

    On the evaluation of the fidelity of supervised classifiers in the prediction of chimeric RNAs

    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...

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

    BioData Mining 2016 9:34

    Published on: 2 November 2016

  11. Research

    Low-mass-ion discriminant equation (LOME) for ovarian cancer screening

    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.

    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

    BioData Mining 2016 9:32

    Published on: 12 October 2016

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