Evaluation of similarity measures for gene expression data and their correspondent combined measures.

It is commonly considered that genes with similar expression profiles are functional related. And there are many ways to measure the similarity of gene expression data. Especially with the advent of lots of biological information, new combined measures have been constructed by combining the biological information with different similarity measures.

Effect of the quality of the interaction data on predicting protein function from protein-protein interactions.

Protein function prediction is an important issue in the post-genomic era. When protein function is deduced from protein interaction data, the traditional methods treat each interaction sample equally, where the qualities of the interaction samples are seldom taken into account. In this paper, we investigate the effect of the quality of protein-protein interaction data on predicting protein function.

Classification of G-protein coupled receptors at four levels.

G-protein coupled receptors (GPCRs) are transmembrane proteins which via G-proteins initiate some of the important signaling pathways in a cell and are involved in various physiological processes. Thus, computational prediction and classification of GPCRs can supply significant information for the development of novel drugs in pharmaceutical industry. In this paper, a nearest neighbor method has been introduced to discriminate GPCRs from non-GPCRs and subsequently classify GPCRs at four levels on the basis of amino acid composition and dipeptide composition of proteins.

[Construction of standard human transcript dataset based on RefSeq and human genome sequence database].

The NCBI Reference Sequence (RefSeq) database aimed to provide a biologically non-redundant collection of DNA, RNA, and protein sequences and to promote the research on genes and proteins of human beings and other species. However, because of widely distributed polymorphisms and different quality control of experiments in individual laboratories, there are potential problems need to be identified in the RefSeq database. Regarding which, we herein define the concept, standard transcript, based on the Central Dogmas of Biology that each standard transcript should be perfectly mapped to the standard genomic DNA sequence at the exon level.

Using Nearest Feature Line and Tunable Nearest Neighbor methods for prediction of protein subcellular locations.

The subcellular location of a protein is closely correlated with it biological function. In this paper, two new pattern classification methods termed as Nearest Feature Line (NFL) and Tunable Nearest Neighbor (TNN) have been introduced to predict the subcellular location of proteins based on their amino acid composition alone. The simulation experiments were performed with the jackknife test on a previously constructed data set, which consists of 2,427 eukaryotic and 997 prokaryotic proteins.

Prediction of protein subcellular location using a combined feature of sequence.

To understand the structure and function of a protein, an important task is to know where it occurs in the cell. Thus, a computational method for properly predicting the subcellular location of proteins would be significant in interpreting the original data produced by the large-scale genome sequencing projects. The present work tries to explore an effective method for extracting features from protein primary sequence and find a novel measurement of similarity among proteins for classifying a protein to its proper subcellular location.