GONUTS: the Gene Ontology Normal Usage Tracking System

The Gene Ontology Normal Usage Tracking System (GONUTS) is a community-based browser and usage guide for Gene Ontology (GO) terms and a community system for general GO annotation of proteins. GONUTS uses wiki technology to allow registered users to share and edit notes on the use of each term in GO, and to contribute annotations for specific genes of interest. By providing a site for generation of third-party documentation at the granularity of individual terms, GONUTS complements the official documentation of the Gene Ontology Consortium. To provide examples for community users, GONUTS displays the complete GO annotations from seven model organisms: Saccharomyces cerevisiae, Dictyostelium discoideum, Caenorhabditis elegans, Drosophila melanogaster, Danio rerio, Mus musculus and Arabidopsis thaliana. To support community annotation, GONUTS allows automated creation of gene pages for gene products in UniProt. GONUTS will improve the consistency of annotation efforts across genome projects, and should be useful in training new annotators and consumers in the production of GO annotations and the use of GO terms. GONUTS can be accessed at http://gowiki.tamu.edu. The source code for generating the content of GONUTS is available upon request

DAS Writeback: A Collaborative Annotation System

<p>Abstract</p> <p>Background</p> <p>Centralised resources such as GenBank and UniProt are perfect examples of the major international efforts that have been made to integrate and share biological information. However, additional data that adds value to these resources needs a simple and rapid route to public access. The Distributed Annotation System (DAS) provides an adequate environment to integrate genomic and proteomic information from multiple sources, making this information accessible to the community. DAS offers a way to distribute and access information but it does not provide domain experts with the mechanisms to participate in the curation process of the available biological entities and their annotations.</p> <p>Results</p> <p>We designed and developed a Collaborative Annotation System for proteins called DAS Writeback. DAS writeback is a protocol extension of DAS to provide the functionalities of adding, editing and deleting annotations. We implemented this new specification as extensions of both a DAS server and a DAS client. The architecture was designed with the involvement of the DAS community and it was improved after performing usability experiments emulating a real annotation task.</p> <p>Conclusions</p> <p>We demonstrate that DAS Writeback is effective, usable and will provide the appropriate environment for the creation and evolution of community protein annotation.</p

Selection-based design of in silico dengue epitope ensemble vaccines

Dengue virus affects approximately 130 countries. 25% of infections result in febrile, self‐limiting illness; heterotypic infection results in potentially fatal Dengue Haemorrhagic Fever or Dengue Shock Syndrome. Only one vaccine is currently available. Its efficacy is very variable. Thus, to target Dengue, we used an innovative immunoinformatic protocol to design a putative epitope ensemble vaccine by selecting an optimal set of highly‐conserved epitopes with experimentally‐verified immunogenicity. From 1597 CD4+ and MHC II epitopes, 6 MHC Class I epitopes (RAVHADMGYW, GPWHLGKLEM, GLYGNGVVTK, NMIIMDEAHF, KTWAYHGSY, WAYHGSYEV) and 9 MHC Class II epitopes (LAKAIFKLTYQNKVV, GKIVGLYGNGVVTTS, AAIFMTATPPGSVEA, AAIFMTATPPGTADA, GKTVWFVPSIKAGND, KFWNTTIAVSMANIF, RAIWYMWLGARYLEF, VGTYGLNTFTNMEVQ, WTLMYFHRRDLRLAA) were selected; this candidate vaccine achieved a world population coverage of 92.49%

DAS Writeback: A Collaborative Annotation System

<p>Abstract</p> <p>Background</p> <p>Centralised resources such as GenBank and UniProt are perfect examples of the major international efforts that have been made to integrate and share biological information. However, additional data that adds value to these resources needs a simple and rapid route to public access. The Distributed Annotation System (DAS) provides an adequate environment to integrate genomic and proteomic information from multiple sources, making this information accessible to the community. DAS offers a way to distribute and access information but it does not provide domain experts with the mechanisms to participate in the curation process of the available biological entities and their annotations.</p> <p>Results</p> <p>We designed and developed a Collaborative Annotation System for proteins called DAS Writeback. DAS writeback is a protocol extension of DAS to provide the functionalities of adding, editing and deleting annotations. We implemented this new specification as extensions of both a DAS server and a DAS client. The architecture was designed with the involvement of the DAS community and it was improved after performing usability experiments emulating a real annotation task.</p> <p>Conclusions</p> <p>We demonstrate that DAS Writeback is effective, usable and will provide the appropriate environment for the creation and evolution of community protein annotation.</p

Species-level functional profiling of metagenomes and metatranscriptomes.

Functional profiles of microbial communities are typically generated using comprehensive metagenomic or metatranscriptomic sequence read searches, which are time-consuming, prone to spurious mapping, and often limited to community-level quantification. We developed HUMAnN2, a tiered search strategy that enables fast, accurate, and species-resolved functional profiling of host-associated and environmental communities. HUMAnN2 identifies a community's known species, aligns reads to their pangenomes, performs translated search on unclassified reads, and finally quantifies gene families and pathways. Relative to pure translated search, HUMAnN2 is faster and produces more accurate gene family profiles. We applied HUMAnN2 to study clinal variation in marine metabolism, ecological contribution patterns among human microbiome pathways, variation in species' genomic versus transcriptional contributions, and strain profiling. Further, we introduce 'contributional diversity' to explain patterns of ecological assembly across different microbial community types

InterMitoBase: An annotated database and analysis platform of protein-protein interactions for human mitochondria

<p>Abstract</p> <p>Background</p> <p>The mitochondrion is an essential organelle which plays important roles in diverse biological processes, such as metabolism, apoptosis, signal transduction and cell cycle. Characterizing protein-protein interactions (PPIs) that execute mitochondrial functions is fundamental in understanding the mechanisms underlying biological functions and diseases associated with mitochondria. Investigations examining mitochondria are expanding to the system level because of the accumulation of mitochondrial proteomes and human interactome. Consequently, the development of a database that provides the entire protein interaction map of the human mitochondrion is urgently required.</p> <p>Results</p> <p>InterMitoBase provides a comprehensive interactome of human mitochondria. It contains the PPIs in biological pathways mediated by mitochondrial proteins, the PPIs between mitochondrial proteins and non-mitochondrial proteins as well as the PPIs between mitochondrial proteins. The current version of InterMitoBase covers 5,883 non-redundant PPIs of 2,813 proteins integrated from a wide range of resources including PubMed, KEGG, BioGRID, HPRD, DIP and IntAct. Comprehensive curations have been made on the interactions derived from PubMed. All the interactions in InterMitoBase are annotated according to the information collected from their original sources, GenBank and GO. Additionally, InterMitoBase features a user-friendly graphic visualization platform to present functional and topological analysis of PPI networks identified. This should aid researchers in the study of underlying biological properties.</p> <p>Conclusions</p> <p>InterMitoBase is designed as an integrated PPI database which provides the most up-to-date PPI information for human mitochondria. It also works as a platform by integrating several on-line tools for the PPI analysis. As an analysis platform and as a PPI database, InterMitoBase will be an important database for the study of mitochondria biochemistry, and should be particularly helpful in comprehensive analyses of complex biological mechanisms underlying mitochondrial functions.</p

The Generation Challenge Programme comparative plant stress-responsive gene catalogue

The Generation Challenge Programme (GCP; www.generationcp.org) has developed an online resource documenting stress-responsive genes comparatively across plant species. This public resource is a compendium of protein families, phylogenetic trees, multiple sequence alignments (MSA) and associated experimental evidence. The central objective of this resource is to elucidate orthologous and paralogous relationships between plant genes that may be involved in response to environmental stress, mainly abiotic stresses such as water deficit (‘drought’). The web-based graphical user interface (GUI) of the resource includes query and visualization tools that allow diverse searches and browsing of the underlying project database. The web interface can be accessed at http://dayhoff.generationcp.org

IUPHAR-DB: An Open-Access, Expert-Curated Resource for Receptor and Ion Channel Research

[Image: see text] This contribution highlights efforts by the International Union of Basic and Clinical Pharmacology (IUPHAR) Nomenclature Committee (NC-IUPHAR) to classify human receptors and ion channels, to document their properties, and to recommend ligands that are useful for characterization. This effort has inspired the creation of an online database (IUPHAR-DB), which is intended to provide free information to all scientists, summarized from primary literature by experts

Formalization of taxon-based constraints to detect inconsistencies in annotation and ontology development

<p>Abstract</p> <p>Background</p> <p>The Gene Ontology project supports categorization of gene products according to their location of action, the molecular functions that they carry out, and the processes that they are involved in. Although the ontologies are intentionally developed to be taxon neutral, and to cover all species, there are inherent taxon specificities in some branches. For example, the process 'lactation' is specific to mammals and the location 'mitochondrion' is specific to eukaryotes. The lack of an explicit formalization of these constraints can lead to errors and inconsistencies in automated and manual annotation.</p> <p>Results</p> <p>We have formalized the taxonomic constraints implicit in some GO classes, and specified these at various levels in the ontology. We have also developed an inference system that can be used to check for violations of these constraints in annotations. Using the constraints in conjunction with the inference system, we have detected and removed errors in annotations and improved the structure of the ontology.</p> <p>Conclusions</p> <p>Detection of inconsistencies in taxon-specificity enables gradual improvement of the ontologies, the annotations, and the formalized constraints. This is progressively improving the quality of our data. The full system is available for download, and new constraints or proposed changes to constraints can be submitted online at <url>https://sourceforge.net/tracker/?atid=605890&group_id=36855</url>.</p