Clustering evolving proteins into homologous families
نویسندگان
چکیده
منابع مشابه
On the power and limits of sequence similarity based clustering of proteins into families
Over the last decades, we have observed an ongoing tremendous growth of available sequencing data fueled by the advancements in wet-lab technology. The sequencing information is only the beginning of the actual understanding of how organisms survive and prosper. It is, for instance, equally important to also unravel the proteomic repertoire of an organism. A classical computational approach for...
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Roughly speaking, clustering evolving networks aims at detecting structurally dense subgroups in networks that evolve over time. This implies that the subgroups we seek for also evolve, which results in many additional tasks compared to clustering static networks. We discuss these additional tasks and difficulties resulting thereof and present an overview on current approaches to solve these pr...
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The ProDom database is a comprehensive set of protein domain families automatically generated from the SWISS-PROT and TrEMBL sequence databases. An associated database, ProDom-CG, has been derived as a restriction of ProDom to completely sequenced genomes. The ProDom construction method is based on iterative PSI-BLAST searches and multiple alignments are generated for each domain family. The Pr...
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An artificial neural network was used to cluster proteins into families. The network, composed of 7 x 7 neurons, was trained with the Kohonen unsupervised learning algorithm using, as inputs, matrix patterns derived from the bipeptide composition of 447 proteins, belonging to 13 different families. As a result of the training, and without any a priori indication of the number or composition of ...
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ژورنال
عنوان ژورنال: BMC Bioinformatics
سال: 2013
ISSN: 1471-2105
DOI: 10.1186/1471-2105-14-120