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We present CARAS, a web server that allows the automatic annotation of a chloroplast genome sequence, and the visualization and editing of the annotation results interactively and in real-time. CARAS accepts a complete chloroplast genome sequence as input. First, it accurately predicts protein-coding sequences and exon-intron structures by combining the results from two types of annotation approaches:...
Predicting gene function is usually formulated as binary classification problem. However, we only know which gene has some function while we are not sure that it doesn't belong to a function class, which means that only positive examples are given. Therefore, selecting a good training example set becomes a key step. In this paper, we cluster the genes on integrated weighted graph by generalizing the...
Using Multiple Kernels Learning(MKL) to integrate heterogeneous data sources to train Support Vector Machine(SVM) classifier is becoming popular. For the protein function prediction problem, all the function categories form a directed acyclic graph(DAG), that is, Gene Ontology(GO). Given a protein to be predicted, after applying a trained SVM to output probabilistic prediction at each function category...
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