Prepulse inhibition (PPI) is a neuropsychological process during which a weak sensory stimulus ("prepulse") attenuates the motor response ("startle reaction") to a subsequent strong startling stimulus. It is measured as a surrogate marker of sensorimotor gating in patients suffering from neuropsychological diseases such as schizophrenia, as well as in corresponding animal models. A variety of s...

Invasive ductal carcinoma (IDC) is a common histological type of breast cancer. The aim of this study was to identify the potential crucial genes associated with IDC and to provide valid biological information for further investigations. The gene expression profiles of GSE10780 which contained 42 histologically normal breast tissues and 143 IDC tissues were downloaded from the GEO database. Fun...

Intracranial aneurysm (IA) is a severe clinical condition of primary concern and currently, there is no effective therapeutic reagent. The present study aimed to investigate the molecular mechanism of IA via bioinformatic analysis. Various gene expression profiles (GSE26969) were downloaded from the Gene Expression Omnibus database, including 3 IA and 3 normal superficial temporal artery sample...

Understanding complex networks of protein-protein interactions (PPIs) is one of the foremost challenges of the post-genomic era. Due to the recent advances in experimental bio-technology, including yeast-2-hybrid (Y2H), tandem affinity purification (TAP) and other high-throughput methods for protein-protein interaction (PPI) detection, huge amounts of PPI network data are becoming available. Of...

Analysis of Protein-Protein Interaction (PPI) networks is of great significance in evolutionary biology. Because of high computation cost, recently multi-PPI network alignment becomes hot topic. In this paper, we proposed conserved topological structures mining based multiPPI network alignment technology. The most challenging problems in conserved topological structure mining are the large size...

Protein-Protein Interaction (PPI) networks are commonly represented as undirected graphs with nodes corresponding to proteins and unit-weight edges representing the interactions between two proteins. In an on-going research, we intend to improve the knowledge-base of PPI networks by conducting the following graph theoretic analysis studies: (i) We propose to take an intersection of the PPI netw...

OBJECTIVE To systematically explore the molecular mechanism for hepatocellular carcinoma (HCC) metastasis and identify regulatory genes with text mining methods. RESULTS Genes with highest frequencies and significant pathways related to HCC metastasis were listed. A handful of proteins such as EGFR, MDM2, TP53 and APP, were identified as hub nodes in PPI (protein-protein interaction) network....

BACKGROUND This study was aimed to explore the molecular mechanisms of hypertensive nephropathy (HTN). METHODS Gene expression profile of GSE37460, which based on 27 healthy living donor samples (HTN group) and 15 hypertensive nephropathy samples (control group), were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between two groups were iden...

This paper considers how to computationally predict unknown protein-protein interactions (PPIs) given the experimentally verified PPIs. Matrix completion, a very popular machine learning technique that can be used to to infer the missing part of a matrix, has been introduced to recover the missing interactions of an incomplete PPI network. The benefit of Matrix completion is that it does not re...

With the increase of available protein-protein interaction (PPI) data, more and more efforts have been put to PPI network modeling, and a number of models of PPI networks have been proposed. Roughly speaking, good models of PPI networks should be able to accurately describe PPI mechanisms, and thus reproduce the structures of PPI networks. With such models, theoretical and/or computational biol...