Controlled vocabularies in bioinformatics: A case study in the Gene Ontology

The automatic integration of information resources in the life sciences is one of the most challenging goals facing biomedical informatics today. Controlled vocabularies have played an important role in realizing this goal, by making it possible to draw together information from heterogeneous sources secure in the knowledge that the same terms will also represent the same entities on all occasions of use. One of the most impressive achievements in this regard is the Gene Ontology (GO), which is rapidly acquiring the status of a de facto standard in the field of gene and gene product annotations, and whose methodology has been much intimated in attempts to develop controlled vocabularies for shared use in different domains of biology. The GO Consortium has recognized, however, that its controlled vocabulary as currently constituted is marked by several problematic features - features which are characteristic of much recent work in bioinformatics and which are destined to raise increasingly serious obstacles to the automatic integration of biomedical information in the future. Here, we survey some of these problematic features, focusing especially on issues of compositionality and syntactic regimentation

Biomedical Informatics and Granularity

An explicit formal-ontological representation of entities existing at multiple levels of granularity is an urgent requirement for biomedical information processing. We discuss some fundamental principles which can form a basis for such a representation. We also comment on some of the implicit treatments of granularity in currently available ontologies and terminologies (GO, FMA, SNOMED CT)

AgBase: supporting functional modeling in agricultural organisms

AgBase (http://www.agbase.msstate.edu/) provides resources to facilitate modeling of functional genomics data and structural and functional annotation of agriculturally important animal, plant, microbe and parasite genomes. The website is redesigned to improve accessibility and ease of use, including improved search capabilities. Expanded capabilities include new dedicated pages for horse, cat, dog, cotton, rice and soybean. We currently provide 590 240 Gene Ontology (GO) annotations to 105 454 gene products in 64 different species, including GO annotations linked to transcripts represented on agricultural microarrays. For many of these arrays, this provides the only functional annotation available. GO annotations are available for download and we provide comprehensive, species-specific GO annotation files for 18 different organisms. The tools available at AgBase have been expanded and several existing tools improved based upon user feedback. One of seven new tools available at AgBase, GOModeler, supports hypothesis testing from functional genomics data. We host several associated databases and provide genome browsers for three agricultural pathogens. Moreover, we provide comprehensive training resources (including worked examples and tutorials) via links to Educational Resources at the AgBase website

Assembly, assessment and availability of de novo generated transcriptomes

De novo assembly of a complete transcriptome without the need for a guiding reference genome is attractive, particularly where the cost and complexity of generating a eukaryote genome is prohibitive. The transcriptome should not however be seen as just a quick and cheap alternative to building a complete genome. Transcriptomics allows the understanding and comparison of spatial and temporal samples within an organism and allows surveying of multiple individuals or closely related species. De novo assembly in theory allows the building of a complete transcriptome without any prior knowledge of the genome it also allows the discovery of alternate splice forms of coding RNAs and also non-coding RNAs, which are often missed by proteomic approaches or are incompletely annotated in genome studies. The limitations of the method are that generation of a truly complete assembly is unlikely and so we require some method for assessment of the quality and appropriateness of a generated transcriptome. Whilst no single consensus pipeline or tools is agreed as optimal, various algorithms and easy to use software do exist making transcriptome generation a more common approach. With this expansion of data, questions still exist relating to how do we make these datasets fully discoverable, comparable and most useful to understand complex biological systems

ProFITS of maize: a database of protein families involved in the transduction of signalling in the maize genome

<p>Abstract</p> <p>Background</p> <p>Maize (<it>Zea mays </it>ssp. <it>mays </it>L.) is an important model for plant basic and applied research. In 2009, the B73 maize genome sequencing made a great step forward, using clone by clone strategy; however, functional annotation and gene classification of the maize genome are still limited. Thus, a well-annotated datasets and informative database will be important for further research discoveries. Signal transduction is a fundamental biological process in living cells, and many protein families participate in this process in sensing, amplifying and responding to various extracellular or internal stimuli. Therefore, it is a good starting point to integrate information on the maize functional genes involved in signal transduction.</p> <p>Results</p> <p>Here we introduce a comprehensive database 'ProFITS' (Protein Families Involved in the Transduction of Signalling), which endeavours to identify and classify protein kinases/phosphatases, transcription factors and ubiquitin-proteasome-system related genes in the B73 maize genome. Users can explore gene models, corresponding transcripts and FLcDNAs using the three abovementioned protein hierarchical categories, and visualize them using an AJAX-based genome browser (JBrowse) or Generic Genome Browser (GBrowse). Functional annotations such as GO annotation, protein signatures, protein best-hits in the <it>Arabidopsis </it>and rice genome are provided. In addition, pre-calculated transcription factor binding sites of each gene are generated and mutant information is incorporated into ProFITS. In short, ProFITS provides a user-friendly web interface for studies in signal transduction process in maize.</p> <p>Conclusion</p> <p>ProFITS, which utilizes both the B73 maize genome and full length cDNA (FLcDNA) datasets, provides users a comprehensive platform of maize annotation with specific focus on the categorization of families involved in the signal transduction process. ProFITS is designed as a user-friendly web interface and it is valuable for experimental researchers. It is freely available now to all users at <url>http://bioinfo.cau.edu.cn/ProFITS</url>.</p

Phenotypic screen for oxygen consumption rate identifies an anti-cancer naphthoquinone that induces mitochondrial oxidative stress.

A hallmark of cancer cells is their ability to reprogram nutrient metabolism. Thus, disruption to this phenotype is a potential avenue for anti-cancer therapy. Herein we used a phenotypic chemical library screening approach to identify molecules that disrupted nutrient metabolism (by increasing cellular oxygen consumption rate) and were toxic to cancer cells. From this screen we discovered a 1,4-Naphthoquinone (referred to as BH10) that is toxic to a broad range of cancer cell types. BH10 has improved cancer-selective toxicity compared to doxorubicin, 17-AAG, vitamin K3, and other known anti-cancer quinones. BH10 increases glucose oxidation via both mitochondrial and pentose phosphate pathways, decreases glycolysis, lowers GSH:GSSG and NAPDH/NAPD+ ratios exclusively in cancer cells, and induces necrosis. BH10 targets mitochondrial redox defence as evidenced by increased mitochondrial peroxiredoxin 3 oxidation and decreased mitochondrial aconitase activity, without changes in markers of cytosolic or nuclear damage. Over-expression of mitochondria-targeted catalase protects cells from BH10-mediated toxicity, while the thioredoxin reductase inhibitor auranofin synergistically enhances BH10-induced peroxiredoxin 3 oxidation and cytotoxicity. Overall, BH10 represents a 1,4-Naphthoquinone with an improved cancer-selective cytotoxicity profile via its mitochondrial specificity

Polyphasic taxonomy of Aspergillus section Usti

Aspergillus ustus is a very common species in foods, soil and indoor environments. Based on chemical, molecular and morphological data, A. insuetus is separated from A. ustus and revived. A. insuetus differs from A. ustus in producing drimans and ophiobolin G and H and not producing ustic acid and austocystins. The molecular, physiological and morphological data also indicated that another species, A. keveii sp. nov. is closely related but distinct from A. insuetus. Aspergillus section Usti sensu stricto includes 8 species: A. ustus, A. puniceus, A. granulosus, A. pseudodeflectus, A. calidoustus, A. insuetus and A. keveii together with Emericella heterothallica