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  1. Research

    Learning directed acyclic graphs from large-scale genomics data

    In this paper, we consider the problem of learning the genetic interaction map, i.e., the topology of a directed acyclic graph (DAG) of genetic interactions from noisy double-knockout (DK) data. Based on a set...

    Fabio Nikolay, Marius Pesavento, George Kritikos and Nassos Typas

    EURASIP Journal on Bioinformatics and Systems Biology 2017 2017:10

    Published on: 20 September 2017

  2. Research

    Bayesian inference for biomarker discovery in proteomics: an analytic solution

    This paper addresses the question of biomarker discovery in proteomics. Given clinical data regarding a list of proteins for a set of individuals, the tackled problem is to extract a short subset of proteins t...

    Noura Dridi, Audrey Giremus, Jean-Francois Giovannelli, Caroline Truntzer, Melita Hadzagic, Jean-Philippe Charrier, Laurent Gerfault, Patrick Ducoroy, Bruno Lacroix, Pierre Grangeat and Pascal Roy

    EURASIP Journal on Bioinformatics and Systems Biology 2017 2017:9

    Published on: 14 July 2017

  3. Research

    BCC-NER: bidirectional, contextual clues named entity tagger for gene/protein mention recognition

    Tagging biomedical entities such as gene, protein, cell, and cell-line is the first step and an important pre-requisite in biomedical literature mining. In this paper, we describe our hybrid named entity taggi...

    Gurusamy Murugesan, Sabenabanu Abdulkadhar, Balu Bhasuran and Jeyakumar Natarajan

    EURASIP Journal on Bioinformatics and Systems Biology 2017 2017:7

    Published on: 5 May 2017

  4. Review

    From protein-protein interactions to protein co-expression networks: a new perspective to evaluate large-scale proteomic data

    The reductionist approach of dissecting biological systems into their constituents has been successful in the first stage of the molecular biology to elucidate the chemical basis of several biological processe...

    Danila Vella, Italo Zoppis, Giancarlo Mauri, Pierluigi Mauri and Dario Di Silvestre

    EURASIP Journal on Bioinformatics and Systems Biology 2017 2017:6

    Published on: 20 March 2017

  5. Research

    On biometric systems: electrocardiogram Gaussianity and data synthesis

    Electrocardiogram is a slow signal to acquire, and it is prone to noise. It can be inconvenient to collect large number of ECG heartbeats in order to train a reliable biometric system; hence, this issue might ...

    Wael Louis, Shahad Abdulnour, Sahar Javaher Haghighi and Dimitrios Hatzinakos

    EURASIP Journal on Bioinformatics and Systems Biology 2017 2017:5

    Published on: 21 February 2017

  6. Research

    Reverse engineering gene regulatory networks from measurement with missing values

    Gene expression time series data are usually in the form of high-dimensional arrays. Unfortunately, the data may sometimes contain missing values: for either the expression values of some genes at some time po...

    Oyetunji E. Ogundijo, Abdulkadir Elmas and Xiaodong Wang

    EURASIP Journal on Bioinformatics and Systems Biology 2017 2017:2

    Published on: 10 January 2017

  7. Research

    Graph reconstruction using covariance-based methods

    Methods based on correlation and partial correlation are today employed in the reconstruction of a statistical interaction graph from high-throughput omics data. These dedicated methods work well even for the ...

    Nurgazy Sulaimanov and Heinz Koeppl

    EURASIP Journal on Bioinformatics and Systems Biology 2016 2016:19

    Published on: 23 November 2016

  8. Research

    Towards organizing health knowledge on community-based health services

    Online community-based health services accumulate a huge amount of unstructured health question answering (QA) records at a continuously increasing pace. The ability to organize these health QA records has bee...

    Mohammad Akbari, Xia Hu, Liqiang Nie and Tat-Seng Chua

    EURASIP Journal on Bioinformatics and Systems Biology 2016 2016:18

    Published on: 17 November 2016

  9. Research

    Stochastic convex sparse principal component analysis

    Principal component analysis (PCA) is a dimensionality reduction and data analysis tool commonly used in many areas. The main idea of PCA is to represent high-dimensional data with a few representative compone...

    Inci M. Baytas, Kaixiang Lin, Fei Wang, Anil K. Jain and Jiayu Zhou

    EURASIP Journal on Bioinformatics and Systems Biology 2016 2016:15

    Published on: 9 September 2016

  10. Research

    Machine learning to predict rapid progression of carotid atherosclerosis in patients with impaired glucose tolerance

    Prediabetes is a major epidemic and is associated with adverse cardio-cerebrovascular outcomes. Early identification of patients who will develop rapid progression of atherosclerosis could be beneficial for im...

    Xia Hu, Peter D. Reaven, Aramesh Saremi, Ninghao Liu, Mohammad Ali Abbasi, Huan Liu and Raymond Q. Migrino

    EURASIP Journal on Bioinformatics and Systems Biology 2016 2016:14

    Published on: 5 September 2016

  11. Research

    Detecting Visually Observable Disease Symptoms from Faces

    Recent years have witnessed an increasing interest in the application of machine learning to clinical informatics and healthcare systems. A significant amount of research has been done on healthcare systems ba...

    Kuan Wang and Jiebo Luo

    EURASIP Journal on Bioinformatics and Systems Biology 2016 2016:13

    Published on: 31 August 2016

  12. Research

    A new method to detect event-related potentials based on Pearson’s correlation

    Event-related potentials (ERPs) are widely used in brain-computer interface applications and in neuroscience.  Normal EEG activity is rich in background noise, and therefore, in order to detect ERPs, it is usu...

    William Giroldini, Luciano Pederzoli, Marco Bilucaglia, Simone Melloni and Patrizio Tressoldi

    EURASIP Journal on Bioinformatics and Systems Biology 2016 2016:11

    Published on: 7 June 2016

  13. Research

    The prediction of virus mutation using neural networks and rough set techniques

    Viral evolution remains to be a main obstacle in the effectiveness of antiviral treatments. The ability to predict this evolution will help in the early detection of drug-resistant strains and will potentially...

    Mostafa A. Salama, Aboul Ella Hassanien and Ahmad Mostafa

    EURASIP Journal on Bioinformatics and Systems Biology 2016 2016:10

    Published on: 13 May 2016

  14. Research

    shRNA target prediction informed by comprehensive enquiry (SPICE): a supporting system for high-throughput screening of shRNA library

    RNA interference (RNAi) screening is extensively used in the field of reverse genetics. RNAi libraries constructed using random oligonucleotides have made this technology affordable. However, the new methodolo...

    Kenta Kamatuka, Masahiro Hattori and Tomoyasu Sugiyama

    EURASIP Journal on Bioinformatics and Systems Biology 2016 2016:7

    Published on: 19 February 2016

  15. Research

    Gene expression analysis supports tumor threshold over 2.0 cm for T-category breast cancer

    Tumor size, as indicated by the T-category, is known as a strong prognostic indicator for breast cancer. It is common practice to distinguish the T1 and T2 groups at a tumor size of 2.0 cm. We investigated the...

    Hiroko K. Solvang, Arnoldo Frigessi, Fateme Kaveh, Margit L. H. Riis, Torben Lüders, Ida R. K. Bukholm, Vessela N. Kristensen and Bettina K. Andreassen

    EURASIP Journal on Bioinformatics and Systems Biology 2016 2016:6

    Published on: 8 February 2016

  16. Research

    Bayesian module identification from multiple noisy networks

    Module identification has been studied extensively in order to gain deeper understanding of complex systems, such as social networks as well as biological networks. Modules are often defined as groups of verti...

    Siamak Zamani Dadaneh and Xiaoning Qian

    EURASIP Journal on Bioinformatics and Systems Biology 2016 2016:5

    Published on: 5 February 2016

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