Titlebook: Computational Intelligence Methods for Bioinformatics and Biostatistics; 11th International M Clelia DI Serio,Pietro Liò,Roberto Tagliaferr

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/c/image/232384.jpg

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出來

Conference proceedings 2015 Bioinformatics and Biostatistics, CIBB 2014, held in Cambridge, UK, in June 2014..The 25 revised full papers presented were carefully reviewed and selected from 44 submissions. The papers focus problems concerning computational techniques in bioinformatics, systems biology, medical informatics and biostatistics..

Endoscope

GO-WAR: A Tool for Mining Weighted Association Rules from Gene Ontology Annotationson of a biological concept that is associated to one or more gene products through a process also known as annotation. Each annotation may be derived using different methods and an Evidence Code (EC) takes into account of this process. The importance and the specificity of both GO terms and annotati

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Extended Spearman and Kendall Coefficients for Gene Annotation List Correlational machine learning algorithms are available in this domain; they include relevant parameters that might influence the output list of predicted gene annotations. The amount that the variation of these key parameters affect the output gene annotation lists remains an open aspect to be evaluated. Here

Outshine

Statistical Analysis of Protein Structural Features: Relationships and PCA Groupingng novel and strengthened methods to investigate in deep protein structure, and to analyze conformational features, in order to highlight relationships to functional properties. We selected some protein families based on their different structural class from CATH database, and studied in detail many

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FECK

Consensus Clustering in Gene Expressionlonging to the same group are more similar between each other than items in different groups. Consensus clustering is a methodology for combining different clustering solutions from the same data set in a new clustering, in order to obtain a more accurate and stable solution. In this work we compare

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Automated Detection of Fluorescent Probes in Molecular Imagingxpert, are now subjected to computational analytics. The use of machine learning techniques allows one to extend the computational imaging approach by considering various markers based on DNA, mRNA, microRNA (miRNA) and proteins that could be used for classification of disease taxonomy, response to

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