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BioData Mining [electronic resource] / edited by Marylyn Ritchie, Jason Moore.

Contributor(s): Material type: Continuing resourceContinuing resourcePublisher: London : BioMed Central : Imprint: BioMed Central. Description: online resourceISSN:
  • 1756-0381
Subject(s): Online resources: Summary: BioData Mining is an open access, open peer-reviewed journal encompassing research on all aspects of data mining applied to high-dimensional biological and biomedical data, focusing on computational aspects of knowledge discovery from large-scale genetic, transcriptomic, genomic, proteomic, and metabolomic data. Topical areas include, but are not limited to: Development, evaluation, and application of novel data mining and machine learning algorithms. Adaptation, evaluation, and application of traditional data mining and machine learning algorithms. Open-source software for the application of data mining and machine learning algorithms. Design, development and integration of databases, software and web services for the storage, management, retrieval, and analysis of data from large scale studies. Pre-processing, post-processing, modeling, and interpretation of data mining and machine learning results for biological interpretation and knowledge discovery.
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BioData Mining is an open access, open peer-reviewed journal encompassing research on all aspects of data mining applied to high-dimensional biological and biomedical data, focusing on computational aspects of knowledge discovery from large-scale genetic, transcriptomic, genomic, proteomic, and metabolomic data. Topical areas include, but are not limited to: Development, evaluation, and application of novel data mining and machine learning algorithms. Adaptation, evaluation, and application of traditional data mining and machine learning algorithms. Open-source software for the application of data mining and machine learning algorithms. Design, development and integration of databases, software and web services for the storage, management, retrieval, and analysis of data from large scale studies. Pre-processing, post-processing, modeling, and interpretation of data mining and machine learning results for biological interpretation and knowledge discovery.

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