PDQ Wizard: automated prioritization and characterization of gene and protein lists using biomedical literature

SUMMARY: PDQ Wizard automates the process of interrogating biomedical references using large lists of genes, proteins or free text. Using the principle of linkage through co-citation biologists can mine PubMed with these proteins or genes to identify relationships within a biological field of interest. In addition, PDQ Wizard provides novel features to define more specific relationships, highlight key publications describing those activities and relationships, and enhance protein queries. PDQ Wizard also outputs a metric that can be used for prioritization of genes and proteins for further research. AVAILABILITY: PDQ Wizard is freely available from http://www.gti.ed.ac.uk/pdqwizard/.     

Get ready to GO! A biologist's guide to the Gene Ontology

The Gene Ontology (GO) project provides a controlled vocabulary to facilitate high-quality functional gene annotation for all species. Genes in biological databases are linked to GO terms, allowing biologists to ask questions about gene function in a manner independent of species. This tutorial provides an introduction for biologists to the GO resources and covers three of the most common methods of querying GO: by individual gene, by gene function and by using a list of genes. [For the sake of brevity, the term 'gene' is used throughout this paper to refer to genes and their products (proteins and RNAs). GO annotations are always based on the characteristics of gene products, even though it may be the gene that is cited in the annotation.].     

Text-mining and information-retrieval services for molecular biology

Text-mining in molecular biology - defined as the automatic extraction of information about genes, proteins and their functional relationships from text documents - has emerged as a hybrid discipline on the edges of the fields of information science, bioinformatics and computational linguistics. A range of text-mining applications have been developed recently that will improve access to knowledge for biologists and database annotators.     

产电微生物基因调控网络的构建和特异性通路分析

研究产电微生物胞外电子传递过程和机制,发现与产电效率相关的关键基因、通路和代谢物,是微生物燃料电池研究中的关键技术。为了发现在胞外电子传递过程中起到关键作用的基因以及通路,首先利用比较基因组学的方法,以模式微生物大肠杆菌和同属希瓦氏菌的其他菌株为参考,构建了Shewanella.onedensis MR-1的全基因组基因转录调控网络,大大扩展了目前已知的基因调控关系。然后以此网络为基础,结合基于蛋白质相互作用分析得到的胞外电子传递通路,构建了与胞外电子传递直接传递密切相关的细胞色素C编码基因及其相关调控基因构成的子网络,结合全基因组基因表达数据,研究了特异性条件下胞外电子传递的可能通路和基因调控过程。     

GeneNetwork: an interactive tool for reconstruction of genetic networks using microarray data

SUMMARY: Inferring genetic network architecture from time series data generated from high-throughput experimental technologies, such as cDNA microarray, can help us to understand the system behavior of living organisms. We have developed an interactive tool, GeneNetwork, which provides four reverse engineering models and three data interpolation approaches to infer relationships between genes. GeneNetwork enables a user to readily reconstruct genetic networks based on microarray data without having intimate knowledge of the mathematical models. A simple graphical user interface enables rapid, intuitive mapping and analysis of the reconstructed network allowing biologists to explore gene relationships at the system level. AVAILABILITY: Download from http://genenetwork.sbl.bc.sinica.edu.tw/. SUPPLEMENTARY INFORMATION: Supplement documentation of algorithms for the four approaches is downloadable at the above location.     

Comparing functional genomic datasets: lessons from DNA microarray analyses of host-pathogen interactions

Functional genomic technologies such as high density DNA microarrays allow biologists to study the structure and behavior of thousands of genes in a single experiment. One of the fields in which microarrays have had an increasingly important impact is host-pathogen interactions. Early investigations in this area over the past two years not only emphasize the utility of this approach, but also highlight the stereotyped gene expression responses of different host cells to diverse infectious stimuli, and the potential value of broad dataset comparisons in revealing fundamental features of innate immunity. The comparative analysis of recently published datasets involving human gene expression responses to two bacterial respiratory pathogens illustrates many of these points. Comparisons between these large, highly parallel sets of experimental observations also emphasize important technical and experimental design issues as future challenges.     

Comparative bacterial proteomics: analysis of the core genome concept

While comparative bacterial genomic studies commonly predict a set of genes indicative of common ancestry, experimental validation of the existence of this core genome requires extensive measurement and is typically not undertaken. Enabled by an extensive proteome database developed over six years, we have experimentally verified the expression of proteins predicted from genomic ortholog comparisons among 17 environmental and pathogenic bacteria. More exclusive relationships were observed among the expressed protein content of phenotypically related bacteria, which is indicative of the specific lifestyles associated with these organisms. Although genomic studies can establish relative orthologous relationships among a set of bacteria and propose a set of ancestral genes, our proteomics study establishes expressed lifestyle differences among conserved genes and proposes a set of expressed ancestral traits.     

The Arabidopsis co-expression tool (ACT): a WWW-based tool and database for microarray-based gene expression analysis

We present a new WWW-based tool for plant gene analysis, the Arabidopsis Co-Expression Tool (ACT), based on a large Arabidopsis thaliana microarray data set obtained from the Nottingham Arabidopsis Stock Centre. The co-expression analysis tool allows users to identify genes whose expression patterns are correlated across selected experiments or the complete data set. Results are accompanied by estimates of the statistical significance of the correlation relationships, expressed as probability (P) and expectation (E) values. Additionally, highly ranked genes on a correlation list can be examined using the novel clique finder tool to determine the sets of genes most likely to be regulated in a similar manner. In combination, these tools offer three levels of analysis: creation of correlation lists of co-expressed genes, refinement of these lists using two-dimensional scatter plots, and dissection into cliques of co-regulated genes. We illustrate the applications of the software by analysing genes encoding functionally related proteins, as well as pathways involved in plant responses to environmental stimuli. These analyses demonstrate novel biological relationships underlying the observed gene co-expression patterns. To demonstrate the ability of the software to develop testable hypotheses on gene function within a defined biological process we have used the example of cell wall biosynthesis genes. The resource is freely available at http://www.arabidopsis.leeds.ac.uk/ACT/     

A genetic uncertainty problem

The existence of genes that, when knocked out, result in no obvious phenotype has puzzled biologists for many years. The phenomenon is often ascribed to redundancy in regulatory networks, caused by duplicated genes. However, a recent systematic analysis of data from the yeast genome projects does not support a link between gene duplications and redundancies. An alternative explanation suggests that genes might also evolve by very weak selection, which would mean that their true function cannot be studied in normal laboratory experiments. This problem is comparable to Heisenberg's uncertainty relationship in physics. It is possible to formulate an analogous relationship for biology, which, at its extreme, predicts that the understanding of the full function of a gene might require experiments on an evolutionary scale, involving the entire effective population size of a given species.     

Pleiotropic effects on cardiovascular risk factors within and between the fourth and sixth decades of life: implications for genotype x age interactions

We used an approach for detecting genotype x environment interactions to detect and characterize genotype x age interaction in longitudinal measures of three well known cardiovascular risk factors: total plasma cholesterol (TC), systolic blood pressure (SBP), and body weight (Wgt). Our objectives were to determine if the same gene or suite of genes influences quantitative variation in each of these phenotypes in the 4th and 6th decades of life, to assess the impact of additive gene effects in these two decades, and to evaluate the stability of pleiotropic relationships among these phenotypes. Using the Framingham Heart Study data, we constructed two cross-sectional samples comprising individuals on whom these phenotypes were measured at ages 30-39 years (Original Cohort: exam 1, Offspring Cohort: exam 2) and at ages 50-59 years (Original Cohort: exam 11, Offspring Cohort: exam 5). We also constructed a longitudinal sample from the cross-sectional sample members for whom measures on these traits were available at both ages (i.e., 4th and 6th decades of life). Patterns of pleiotropy, inferred from genetic correlations between traits, differ between the two age classes. Further, additive genetic variance in SBP during the 4th decade of life is attributable to a different gene or suite of genes than during the 6th. The magnitude of the effect increases for SBP. Variation in TC and Wgt appear to be influenced by the same gene or genes in both decades. The magnitude of the effect is stable for TC, but increases dramatically with age for Wgt.     

"Plasmo2D": an ancillary proteomic tool to aid identification of proteins from Plasmodium falciparum

Bioinformatics tools to aid gene and protein sequence analysis have become an integral part of biology in the post-genomic era. Release of the Plasmodium falciparum genome sequence has allowed biologists to define the gene and the predicted protein content as well as their sequences in the parasite. Using pI and molecular weight as characteristics unique to each protein, we have developed a bioinformatics tool to aid identification of proteins from Plasmodium falciparum. The tool makes use of a Virtual 2-DE generated by plotting all of the proteins from the Plasmodium database on a pI versus molecular weight scale. Proteins are identified by comparing the position of migration of desired protein spots from an experimental 2-DE and that on a virtual 2-DE. The procedure has been automated in the form of user-friendly software called "Plasmo2D". The tool can be downloaded from http://144.16.89.25/Plasmo2D.zip.     

GAAD: A Gene and Autoimmiune Disease Association Database

Autoimmune diseases (ADs) arise from an abnormal immune response of the body against substances and tissues normally present in the body. More than a hundred of ADs have been described in the literature so far. Although their etiology remains largely unclear, various types of ADs tend to share more associated genes with other types of ADs than with non-AD types. Here we present GAAD, a gene and AD association database. In GAAD, we collected 44,762 associations between 49 ADs and 4249 genes from public databases and MEDLINE documents. We manually verified the associations to ensure the quality and credibility. We reconstructed and recapitulated the relationships among ADs using their shared genes, which further validated the quality of our data. We also provided a list of significantly co-occurring gene pairs among ADs; with embedded tools, users can query gene co-occurrences and construct customized co-occurrence network with genes of interest. To make GAAD more straightforward to experimental biologists and medical scientists, we extracted additional information describing the associations through text mining, including the putative diagnostic value of the associations, type and position of gene polymorphisms, expression changes of implicated genes, as well as the phenotypical consequences, and grouped the associations accordingly. GAAD is freely available at http://gaad.medgenius.info.     

Differential timing of gene expression regulation between leptocephali of the two Anguilla eel species in the Sargasso Sea

The unique life-history characteristics of North Atlantic catadromous eels have long intrigued evolutionary biologists, especially with respect to mechanisms that could explain their persistence as two ecologically very similar but reproductively and geographically distinct species. Differential developmental schedules during young larval stages have commonly been hypothesized to represent such a key mechanism. We performed a comparative analysis of gene expression by means of microarray experiments with American and European eel leptocephali collected in the Sargasso Sea in order to test the alternative hypotheses of (1) differential timing of gene expression regulation during early development versus (2) species-specific differences in expression of particular genes. Our results provide much stronger support for the former hypothesis since no gene showed consistent significant differences in expression levels between the two species. In contrast, 146 genes showed differential timings of expression between species, although the observed expression level differences between the species were generally small. Consequently, species-specific gene expression regulation seems to play a minor role in species differentiation. Overall, these results show that the basis of the early developmental divergence between the American and European eel is probably influenced by differences in the timing of gene expression regulation for genes involved in a large array of biological functions.     

Gene Ontology term overlap as a measure of gene functional similarity

Background  

The availability of various high-throughput experimental and computational methods allows biologists to rapidly infer functional relationships between genes. It is often necessary to evaluate these predictions computationally, a task that requires a reference database for functional relatedness. One such reference is the Gene Ontology (GO). A number of groups have suggested that the semantic similarity of the GO annotations of genes can serve as a proxy for functional relatedness. Here we evaluate a simple measure of semantic similarity, term overlap (TO).     

蛇毒C型凝集素类蛋白cDNA与基因组DNA序列分析显示特别的转录后加工(英文)

为研究蛇毒C型凝集素类蛋白的快速进化机制和结构功能关系 ,使用PCR技术扩增了若干编码C型凝集素类蛋白 β链的cDNA分子以及agkisasinβ的基因组DNA ,并将这些扩增产物进行克隆和测序 .对测序结果与试验过程中的具体条件进行了因果关系分析 ,并且进行点阵图比较和多序列比对 .结果表明 ,可能存在“转录后同源重组”等转录后的事件 ,在蛇毒C型凝集素类蛋白的多样性上起着重要的作用 .对于解释基因数目与蛋白质数目的差异这一后基因组时代的重要问题 ,具有一定的参考价值 .首次报告蛇毒C型凝集素类蛋白的基因组DNA序列 ,其中未发现有内含子