Titlebook: Data Mining for Systems Biology; Methods and Protocol Hiroshi Mamitsuka Book 2018Latest edition Springer Science+Business Media, LLC, part

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DrugE-Rank: Predicting Drug-Target Interactions by Learning to Rank,d into two types: feature-based and similarity-based methods. By utilizing the “Learning to rank” framework, we propose a new method, DrugE-Rank, to combine these two different types of methods for improving the prediction performance of new candidate drugs and targets. DrugE-Rank is available at ..

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Data Mining for Systems Biology978-1-4939-8561-6Series ISSN 1064-3745 Series E-ISSN 1940-6029

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https://doi.org/10.1007/978-1-4939-8561-6Metagenomics; Epigenomics; Metabolomics; Data sciences; Machine learning; Pharmaceutical science; Artifici

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Commercial Applications of Ionic LiquidsDatabase Project, and IMG, handling massive amounts of raw data and meta information. 16s rRNA gene contains hypervariable regions with great classification power. As a result, numerous classification tools have emerged including state-of-the-art tools such as Mothur, Qiime, and the 16s classifier.

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Commercial Applications of Ionic Liquidsdate no single experiment can capture these separate modifications, and integrative experimental designs are needed to fully characterize cytosine methylation and chemical modification. This chapter describes a generative probabilistic model, ., for integrative analysis of cytosine methylation and i

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Julia L. Shamshina,Robin D. Rogersed approaches like the Illumina 450 K or 850 K EPIC chips have been used in a wide range of studies mostly comparing a disease group with healthy control, but also to correlate with survival times, for instance. Processing, normalization, and analysis of raw data require extensive knowledge in stati