An edge-coloring of a graph G is an coloring of a graph G is an edge-coloring of G such assignment of colors to all the edges of G. A go- that each color appears at each vertex at least g（v） times. The maximum integ...An edge-coloring of a graph G is an coloring of a graph G is an edge-coloring of G such assignment of colors to all the edges of G. A go- that each color appears at each vertex at least g（v） times. The maximum integer k such that G has a go-coloring with k colors is called the gc-chromatic index of G and denoted by X＇gc （G）. In this paper, we extend a result on edge-covering coloring of Zhang X＇gc（ ） = δg（G）, and Liu in 2011, and give a new sufficient condition for a simple graph G to satisfy ＇ x＇gc（G）=δg（G）,where δg（G）=minv∈V（G）{[d（v）/g（v）]}.展开更多
As one of the essential topics in proteomics and molecular biology, protein subcellular localization has been extensively studied in previous decades. However, most of the methods are limited to the prediction of sing...As one of the essential topics in proteomics and molecular biology, protein subcellular localization has been extensively studied in previous decades. However, most of the methods are limited to the prediction of single-location proteins. In many studies, multi-location proteins are either not considered or assumed not existing. This paper proposes a novel multi-label subcellular-localization predictor based on the semantic similarity between Gene Ontology (GO) terms. Given a protein, the accession numbers of its homologs are obtained via BLAST search. Then, the homologous accession numbers of the protein are used as keys to search against the gene ontology annotation database to obtain a set of GO terms. The semantic similarity between GO terms is used to formulate semantic similarity vectors for classification. A support vector machine (SVM) classifier with a new decision scheme is proposed to classify the multi-label GO semantic similarity vectors. Experimental results show that the proposed multi-label predictor significantly outperforms the state-of-the-art predictors such as iLoc-Plant and Plant-mPLoc.展开更多
基金Supported by Shandong Provincial Natural Science Foundation,China(Grant No.ZR2014JL001)the Shandong Province Higher Educational Science and Technology Program(Grant No.J13LI04)the Excellent Young Scholars Research Fund of Shandong Normal University of China
文摘An edge-coloring of a graph G is an coloring of a graph G is an edge-coloring of G such assignment of colors to all the edges of G. A go- that each color appears at each vertex at least g（v） times. The maximum integer k such that G has a go-coloring with k colors is called the gc-chromatic index of G and denoted by X＇gc （G）. In this paper, we extend a result on edge-covering coloring of Zhang X＇gc（ ） = δg（G）, and Liu in 2011, and give a new sufficient condition for a simple graph G to satisfy ＇ x＇gc（G）=δg（G）,where δg（G）=minv∈V（G）{[d（v）/g（v）]}.
文摘As one of the essential topics in proteomics and molecular biology, protein subcellular localization has been extensively studied in previous decades. However, most of the methods are limited to the prediction of single-location proteins. In many studies, multi-location proteins are either not considered or assumed not existing. This paper proposes a novel multi-label subcellular-localization predictor based on the semantic similarity between Gene Ontology (GO) terms. Given a protein, the accession numbers of its homologs are obtained via BLAST search. Then, the homologous accession numbers of the protein are used as keys to search against the gene ontology annotation database to obtain a set of GO terms. The semantic similarity between GO terms is used to formulate semantic similarity vectors for classification. A support vector machine (SVM) classifier with a new decision scheme is proposed to classify the multi-label GO semantic similarity vectors. Experimental results show that the proposed multi-label predictor significantly outperforms the state-of-the-art predictors such as iLoc-Plant and Plant-mPLoc.
