Abstract: SUMMARY: The Network Ontology Analysis (NOA) plugin for Cytoscape implements the NOA algorithm for network-based enrichment analysis, which extends Gene Ontology annotations to network links, or edges. The plugin facilitates the annotation and analysis of one or more networks in Cytoscape according to user-defined parameters. In addition to tables, the NOA plugin also presents results in the form of heatmaps and overview networks in Cytoscape, which can be exported for publication figures. AVAILABILITY: The NOA plugin is an open source, Java program for Cytoscape version 2.8 available via the Cytoscape App Store (http://apps.cytoscape.org/apps/noa) and plugin manager. A detailed user manual is available at http://nrnb.org/tools/noa. CONTACT: apico@gladstone.ucsf.edu.
Abstract: As a marker of Helicobacter pylori, Cytotoxin-associated gene A (cagA) has been revealed to be the major virulence factor causing gastroduodenal diseases. However, the molecular mechanisms that underlie the development of different gastroduodenal diseases caused by cagA-positive H. pylori infection remain unknown. Current studies are limited to the evaluation of the correlation between diseases and the number of Glu-Pro-Ile-Tyr-Ala (EPIYA) motifs in the CagA strain. To further understand the relationship between CagA sequence and its virulence to gastric cancer, we proposed a systematic entropy-based approach to identify the cancer-related residues in the intervening regions of CagA and employed a supervised machine learning method for cancer and non-cancer cases classification.
Abstract: Adiponectin is secreted from adipose tissue and functions as a protein hormone in regulating glucose metabolism and fatty acid catabolism. Adiponectin plays an important role as a novel risk factor and potential diagnostic and prognostic biomarker in cancer. Crystal structures of globular adiponectin have been resolved with three calcium-binding sites on the top of its central tunnel. However, the calcium-binding property of adiponectin remains elusive. Mouse globular adiponectin was cloned into pET11a and expressed in Escherichia coli. The folding of adiponectin was indicated by the spread of resonances in HSQC spectrum. Luminescence resonance energy transfer was used to obtain the binding constant (K(d) ) of Tb(3+) and the inhibitor constant (K(i) ) of Ca(2+) for globular adiponectin. The obtained calcium-binding affinity to adiponectin is relatively low (~2 mM), which indicates that the high concentration of adiponectin in circulating system may function as calcium storage bank and buffer the free calcium concentration. Copyright (c) 2012 John Wiley & Sons, Ltd.
Notes: Yu, Dongmei xD;Zhang, Chao xD;Wang, Han xD;Qin, Peiwu xD;ENG xD;2012/10/02 06:00 xD;Cell Biochem Funct. 2012 Oct 1. doi: 10.1002/cbf.2906.
Abstract: We present a Cytoscape plugin called Mosaic to support interactive network annotation, partitioning, layout and coloring based on gene ontology or other relevant annotations.
Abstract: Alpha helix transmembrane proteins (αTMPs) represent roughly 30% of all open reading frames (ORFs) in a typical genome and are involved in many critical biological processes. Due to the special physicochemical properties, it is hard to crystallize and obtain high resolution structures experimentally, thus, sequence-based topology prediction is highly desirable for the study of transmembrane proteins (TMPs), both in structure prediction and function prediction. Various model-based topology prediction methods have been developed, but the accuracy of those individual predictors remain poor due to the limitation of the methods or the features they used. Thus, the consensus topology prediction method becomes practical for high accuracy applications by combining the advances of the individual predictors. Here, based on the observation that inter-helical interactions are commonly found within the transmembrane helixes (TMHs) and strongly indicate the existence of them, we present a novel consensus topology prediction method for αTMPs, CNTOP, which incorporates four top leading individual topology predictors, and further improves the prediction accuracy by using the predicted inter-helical interactions. The method achieved 87% prediction accuracy based on a benchmark dataset and 78% accuracy based on a non-redundant dataset which is composed of polytopic αTMPs. Our method derives the highest topology accuracy than any other individual predictors and consensus predictors, at the same time, the TMHs are more accurately predicted in their length and locations, where both the false positives (FPs) and the false negatives (FNs) decreased dramatically. The CNTOP is available at: http://ccst.jlu.edu.cn/JCSB/cntop/CNTOP.html.
Abstract: With the rapid development of next-generation sequencing technologies, bacterial identi¯cation becomes a very
important and essential step in processing genomic data, especially for metagenomic data. Many computational methods
have been developed and some of them are widely used to address the problems in bacterial identi¯cation. In this article
we review the algorithms of these methods, discuss their drawbacks, and propose future computational methods that use
genomic data to characterize bacteria. In addition, we tackle two speci¯c computational problems in bacterial identi¯cation,
namely, the detection of host-speci¯c bacteria and the detection of disease-associated bacteria, by o®ering potential solutions
as a starting point for those who are interested in the area.
Abstract: A phylogenetic tree, showing ancestral relations among organisms, is commonly represented as a rooted tree with sets of bifurcating branches (dichotomies) for simplicity, although polytomies (multifurcating branches) may reflect more accurate evolutionary relationships. To represent the true evolutionary relationships, it is important to systematically identify the polytomies from a bifurcating tree and generate a taxonomy-compatible multifurcating tree. For this purpose we propose a novel approach, "PolyPhy", which would classify a set of bifurcating branches of a phylogenetic tree into a set of branches with dichotomies and polytomies by considering genome distances among genomes and tree topological properties.
Abstract: Effector secretion is a common strategy of pathogen in mediating host-pathogen interaction. Eight EPIYA-motif containing effectors have recently been discovered in six pathogens. Once these effectors enter host cells through type III/IV secretion systems (T3SS/T4SS), tyrosine in the EPIYA motif is phosphorylated, which triggers effectors binding other proteins to manipulate host-cell functions. The objectives of this study are to evaluate the distribution pattern of EPIYA motif in broad biological species, to predict potential effectors with EPIYA motif, and to suggest roles and biological functions of potential effectors in host-pathogen interactions.
Abstract: Characterising gene function is one of the major challenging tasks in the post-genomic era. Various approaches have been developed to integrate multiple sources of high-throughput data to predict gene function. Most of those approaches are just used for research purpose and have not been implemented as publicly available tools. Even for those implemented applications, almost all of them are still web-based 'prediction servers' that have to be managed by specialists. This paper introduces a systematic method for integrating various sources of high-throughput data to predict gene function and analyse our prediction results and evaluates its performances based on the competition for mouse gene function prediction (MouseFunc). A stand-alone Java-based software package 'GeneFAS' is freely available at http://digbio. missouri.eduigenefas.
Abstract: Characterizing gene function is one of the major challenging tasks in the postgenomic era. To address this challenge, we developed GeneFAS (gene function annotation system), a computer system with a graphical user interface for cellular function prediction by integrating information from protein-protein interactions, protein complexes, microarray gene expression profiles, and annotations of known proteins. GeneFAS can provide biologists a workspace for their organism of interest, to integrate different types of experimental data and annotation information, and facilitate biological discovery and hypothesis generation using all the information. It also provides testing and training capabilities for users to utilize and integrate their data more efficiently. GeneFAS is freely available for download at http://digbio.missouri.edu/genefas .
Abstract: Several years after sequencing the human genome and the mouse genome, much remains to be discovered about the functions of most human and mouse genes. Computational prediction of gene function promises to help focus limited experimental resources on the most likely hypotheses. Several algorithms using diverse genomic data have been applied to this task in model organisms; however, the performance of such approaches in mammals has not yet been evaluated.
Abstract: Protein identification through high-throughput mass spectrum data is an important domain in proteomics. Peptide mass fingerprinting (PMF) is one of the major methods for protein identification using the mass-spec technology. We developed a software package called "ProteinDecision" for PMF protein identification, together with a user-friendly graphical interface. "ProteinDecision" can handle the issues of selecting peaks from mass spectrum, transforming database format, displaying the top ranks of identification result, and detailed information for each ranking. We used a novel scoring function by considering the distribution of matching a mass-to-charge and peak intensity in a database based on the MOWSE table. Our new scoring function is assessed better than existing ones by comparing the computational results using experimental PMF data. A standalone version of "ProteinDecision" is freely available upon request.
