MOTIVATION The large, complex networks of interactions between proteins provide a lens through which one can examine the structure and function of biological systems. Previous analyses of these continually growing networks have primarily followed either of two approaches: large-scale statistical analysis of holistic network properties, or small-scale analysis of local topological features. Mean...

OBJECTIVE To uncover the potential regulatory mechanisms of the relevant genes that contribute to the prognosis and prevention of multiple myeloma (MM). METHODS Microarray data (GSE13591) were downloaded, including five plasma cell samples from normal donors and 133 plasma cell samples from MM patients. Differentially expressed genes (DEGs) were identified by Student's t-test. Functional enri...

Successive whole genome duplications have recently been firmly established in all major eukaryote kingdoms. It is not clear, however, how such dramatic evolutionary process has contributed to shape the large scale topology of protein-protein interaction (PPI) networks. We propose and analytically solve a generic model of PPI network evolution under successive whole genome duplications. This dem...

MOTIVATION Proteins are essential macromolecules of life and thus understanding their function is of great importance. The number of functionally unclassified proteins is large even for simple and well studied organisms such as baker's yeast. Methods for determining protein function have shifted their focus from targeting specific proteins based solely on sequence homology to analyses of the en...

It has been shown that protein-protein interactions analysis may be useful to infer information about biological variations caused by evolution. All the known protein-protein interactions of a given organism may be modelled by a network, namely, the protein-protein interaction (PPI) network of that organism, stored in a graph database. The analysis and comparison of protein-protein interaction ...

In this study, we constructed a protein-protein interaction (PPI) network of B. licheniformis strain WX-02 with interolog method and domain-based method, which contained 15,864 edges and 2,448 nodes. Although computationally predicted networks have relatively low coverage and high false-positive rate, our prediction was confirmed from three perspectives: local structural features, functional si...

The aim of the present study was to identify key genes and pathways in glioblastoma-associated stromal cells (GASCs) using bioinformatics. The expression profile of microarray GSE24100 was obtained from the Gene Expression Omnibus database, which included the expression profile of 4 GASC samples and 3 control stromal cell samples. Differentially expressed genes (DEGs) were identified using limm...

Interactions between proteins occur in many, if not most, biological processes. This fact has motivated the development of a variety of experimental methods for the identification of protein-protein interaction (PPI) networks. Leveraging PPI data available STRING database, we use network-based statistical learning methods to infer the putative functions of proteins from the known functions of n...