Sort by
Previous Page Page 2 of 11 Next Page
  1. 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

  2. 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

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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

  8. Methodology

    Functional networks inference from rule-based machine learning models

    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...

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

    BioData Mining 2016 9:28

    Published on: 5 September 2016

  9. Software article

    A biologically informed method for detecting rare variant associations

    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...

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

    BioData Mining 2016 9:27

    Published on: 30 August 2016


    msBiodat analysis tool, big data analysis for high-throughput experiments

    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...

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

    BioData Mining 2016 9:26

    Published on: 19 August 2016


    Mango: combining and analyzing heterogeneous biological networks

    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...

    Jennifer Chang, Hyejin Cho and Hui-Hsien Chou

    BioData Mining 2016 9:25

    Published on: 2 August 2016

  12. Methodology

    Joint analysis of multiple high-dimensional data types using sparse matrix approximations of rank-1 with applications to ovarian and liver cancer

    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...

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

    BioData Mining 2016 9:24

    Published on: 29 July 2016

  13. Review

    Representing and querying disease networks using graph databases

    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...

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

    BioData Mining 2016 9:23

    Published on: 25 July 2016

  14. Research

    Data integration to prioritize drugs using genomics and curated data

    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 ...

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

    BioData Mining 2016 9:21

    Published on: 26 May 2016

Previous Page Page 2 of 11 Next Page