Titlebook: Computational Intelligence Methods for Bioinformatics and Biostatistics; 7th International Me Riccardo Rizzo,Paulo J. G. Lisboa Conference

人工制品

REP

,Diskussion und Schlu?folgerung,s to Computer Science. Following Handl et al., it can be summarized as a three step process: (a) choice of a distance function; (b) choice of a clustering algorithm; (c) choice of a validation method. Although such a purist approach to clustering is hardly seen in many areas of science, genomic data

FILLY

https://doi.org/10.1007/978-3-642-91337-2he post-genomic era, fast and accurate predictors of subcellular location are required if this abundance of sequence data is to be fully exploited. We have developed a subcellular localization predictor (SCL_pred) which predicts the location of a protein into four classes for animals and fungi and f

cluster

狼群

https://doi.org/10.1007/978-3-662-43139-9hromosomes, there are many clues suggesting that the corresponding gene might be found in plant mtDNA, encrypted and hidden by virtue of editing and/or trans-splicing processes. In this paper, we propose an approach to search for the gene . and applied it on mitocondrial DNA (mtDNA) of plants. To se

潰爛

https://doi.org/10.1007/978-3-662-43139-9ns in non-legumes, including monocot plants, suggesting that these genes play additional roles besides nodulation. The presence and expression profile of the early nodulin genes (., ., ., ., ., and .) was evaluated in the sugarcane transcriptome (237,954 ESTs) using in silico procedures. 129 sugarca