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    ICANN
    2009
    Springer
    141views Neural Networks» more  ICANN 2009»
    Adaptive Ensemble Models of Extreme Learning Machines for Time Series Prediction
    14 years 2 months ago
    Adaptive Ensemble Models of Extreme Learning Machines for Time Series Prediction
    Download  www.icsi.berkeley.edu
    Abstract. In this paper, we investigate the application of adaptive ensemble models of Extreme Learning Machines (ELMs) to the problem of one-step ahead prediction in (non)stationa...
    Mark van Heeswijk, Yoan Miche, Tiina Lindh-Knuutil...
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    BMCBI
    2008
    173views more  BMCBI 2008»
    Improved machine learning method for analysis of gas phase chemistry of peptides
    13 years 8 months ago
    Improved machine learning method for analysis of gas phase chemistry of peptides
    Download  www.biomedcentral.com
    Background: Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS) o...
    Allison Gehrke, Shaojun Sun, Lukasz A. Kurgan, Nat...
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    BMCBI
    2010
    109views more  BMCBI 2010»
    Application of machine learning methods to histone methylation ChIP-Seq data reveals H4R3me2 globally represses gene expression
    13 years 8 months ago
    Application of machine learning methods to histone methylation ChIP-Seq data reveals H4R3me2 globally represses gene expression
    Download  www.biomedcentral.com
    Background: In the last decade, biochemical studies have revealed that epigenetic modifications including histone modifications, histone variants and DNA methylation form a comple...
    Xiaojiang Xu, Stephen Hoang, Marty W. Mayo, Stefan...
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    BMCBI
    2008
    123views more  BMCBI 2008»
    Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach
    13 years 8 months ago
    Pol II promoter prediction using characteristic 4-mer motifs: a machine learning approach
    Download  www.biomedcentral.com
    Background: Eukaryotic promoter prediction using computational analysis techniques is one of the most difficult jobs in computational genomics that is essential for constructing a...
    Firoz Anwar, Syed Murtuza Baker, Taskeed Jabid, Md...
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    IJON
    2010
    148views more  IJON 2010»
    Integration of heterogeneous data sources for gene function prediction using decision templates and ensembles of learning machin
    13 years 5 months ago
    Integration of heterogeneous data sources for gene function prediction using decision templates and ensembles of learning machin
    Download  homes.dsi.unimi.it
    Several solutions have been proposed to exploit the availability of heterogeneous sources of biomolecular data for gene function prediction, but few attention has been dedicated t...
    Matteo Re, Giorgio Valentini
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