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Titlebook: Computational Intelligence Methods for Bioinformatics and Biostatistics; 6th International Me Francesco Masulli,Leif E. Peterson,Roberto Ta

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發(fā)表于 2025-3-21 18:18:17 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Computational Intelligence Methods for Bioinformatics and Biostatistics
副標(biāo)題6th International Me
編輯Francesco Masulli,Leif E. Peterson,Roberto Tagliaf
視頻videohttp://file.papertrans.cn/233/232391/232391.mp4
概述Unique visibility, state-of-the-art survey,.fast-track conference proceedings
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Computational Intelligence Methods for Bioinformatics and Biostatistics; 6th International Me Francesco Masulli,Leif E. Peterson,Roberto Ta
出版日期Conference proceedings 2010
關(guān)鍵詞LA; Simulation; algorithms; bioinformatics; classification; ecolutionary information; game theory; gene cha
版次1
doihttps://doi.org/10.1007/978-3-642-14571-1
isbn_softcover978-3-642-14570-4
isbn_ebook978-3-642-14571-1Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer-Verlag Berlin Heidelberg 2010
The information of publication is updating

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發(fā)表于 2025-3-21 20:34:31 | 只看該作者
https://doi.org/10.1007/978-3-476-99314-4genetic algorithms is not new, the presented approach differs in the representation of the multiple alignment and in the simplicity of the genetic operators. The results so far obtained are reported and discussed in this paper.
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發(fā)表于 2025-3-22 09:27:45 | 只看該作者
,Kurzl?sungen zu den übungsaufgaben,nsional matrix, SVD may be very expensive in terms of computational time. We propose to reduce the SVD task to the ordinary maximisation problem with an Euclidean norm which may be solved easily using gradient-based optimisation. We demonstrate the effectiveness of this approach to the supervised classification of gene expression data.
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發(fā)表于 2025-3-22 17:18:52 | 只看該作者
Penalized Principal Component Analysis of Microarray Datansional matrix, SVD may be very expensive in terms of computational time. We propose to reduce the SVD task to the ordinary maximisation problem with an Euclidean norm which may be solved easily using gradient-based optimisation. We demonstrate the effectiveness of this approach to the supervised classification of gene expression data.
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發(fā)表于 2025-3-22 23:37:44 | 只看該作者
Searching a Multivariate Partition Space Using MAX-SATthis method can be used to fully search the space of partitions in smaller problems and how it can be used to enhance the performance of more familiar algorithms in large problems. We illustrate our method on clustering of time-course microarray experiments.
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發(fā)表于 2025-3-23 02:54:28 | 只看該作者
Andreas Kurtenbach,Andreas Kreino simulate a model of the studied biological system but also to deduce the sets of parameter values that lead to a behaviour compatible with the biological knowledge (or hypotheses) about dynamics. This approach is based on formal logic. It is illustrated in the discrete modelling framework of genetic regulatory networks due to René Thomas.
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發(fā)表于 2025-3-23 08:07:39 | 只看該作者
Kleineinzugsgebiete im Mittelgebirgeclassification algorithm to the classes of interacting and noninteracting proteins. Results show that it is possible to achieve high prediction accuracy in cross validation. A case study is analyzed to show it is possible to reconstruct a real network of thousands interacting proteins with high accuracy on standard hardware.
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