Knowledge discovery in bioinformatics
Xiaohua Tony Hu,Yi Pan +1 more
- 25 May 2007
18
TL;DR: In this article, the authors compared seven methods for mining hidden links for protein secondary-structure prediction based on support vector machines (SVM) and compared the results of different methods for detecting hidden links.
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Abstract: 1- Current methods for protein secondary-structure prediction based on support vector machines - 2 - Comparison of seven methods for mining hidden links - 3 - Voting scheme-based evolutionary kernel machines for drug activity comparisons - 4 - Bioinformatics analyses of arabidopsis thaliana tiling array expression data - 5 - Identification marker genes from high-dimensional microarray data for cancer classification - 6 - Patient survival prediction from gene expression data - 7 - RNA interference and microRNA - 8 - Protein structure prediction using string kernels - 9 - Public genomic databases : data representation, storage, and access - 10 - Automatic query expansion with keyphrases and POS phrase categorization for effective biomedical text mining - 11 - Evolutionary dynamics of protein-Protein interactions - 12 - On comparing and visualizing RNA secondary structures - 13 - Integrative analysis of yeast protein translation networks - 14 - Identification of transmembrane proteins using variants of the self-organizing feature map algorithm - 15 - Tricluster : mining coherent clusters in three-dimensional microarray data - 16 - Clustering methods in a protein-protein interaction network
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Profiles and majority voting-based ensemble method for protein secondary structure prediction.
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26
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Katerina C. Nastou,Georgios N. Tsaousis,Kimon E. Kremizas,Zoi I. Litou,Stavros J. Hamodrakas +4 more
TL;DR: In this article, the authors constructed and analyzed the interactions of the human plasma membrane peripheral proteins (peripherome hereinafter) and collected a dataset of peripheral proteins of the Human Plasma membrane.
Solar Wind Reconnection Exhausts in the Inner Heliosphere Observed by Helios and Detected via Machine Learning
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