Semantic Predications for Complex Information Needs in Biomedical Literature.

Many complex information needs that arise in biomedical disciplines require exploring multiple documents in order to obtain information. While traditional information retrieval techniques that return a single ranked list of documents are quite common for such tasks, they may not always be adequate. The main issue is that ranked lists typically impose a significant burden on users to filter out irrelevant documents. Additionally, users must intuitively reformulate their search query when relevant documents have not been not highly ranked. Furthermore, even after interesting documents have been selected, very few mechanisms exist that enable document-to-document transitions. In this paper, we demonstrate the utility of assertions extracted from biomedical text (called semantic predications) to facilitate retrieving relevant documents for complex information needs. Our approach offers an alternative to query reformulation by establishing a framework for transitioning from one document to another. We evaluate this novel knowledge-driven approach using precision and recall metrics on the 2006 TREC Genomics Track.

ProtozoaDB: dynamic visualization and exploration of protozoan genomes.

ProtozoaDB (http://www.biowebdb.org/protozoadb) is being developed to initially host both genomics and post-genomics data from Plasmodium falciparum, Entamoeba histolytica, Trypanosoma brucei, T. cruzi and Leishmania major, but will hopefully host other protozoan species as more genomes are sequenced. It is based on the Genomics Unified Schema and offers a modern Web-based interface for user-friendly data visualization and exploration. This database is not intended to duplicate other similar efforts such as GeneDB, PlasmoDB, TcruziDB or even TDRtargets, but to be complementary by providing further analyses with emphasis on distant similarities (HMM-based) and phylogeny-based annotations including orthology analysis. ProtozoaDB will be progressively linked to the above-mentioned databases, focusing in performing a multi-source dynamic combination of information through advanced interoperable Web tools such as Web services. Also, to provide Web services will allow third-party software to retrieve and use data from ProtozoaDB in automated pipelines (workflows) or other interoperable Web technologies, promoting better information reuse and integration. We also expect ProtozoaDB to catalyze the development of local and regional bioinformatics capabilities (research and training), and therefore promote/enhance scientific advancement in developing countries.

GARSA: genomic analysis resources for sequence annotation.

SUMMARY: Growth of genome data and analysis possibilities have brought new levels of difficulty for scientists to understand, integrate and deal with all this ever-increasing information. In this scenario, GARSA has been conceived aiming to facilitate the tasks of integrating, analyzing and presenting genomic information from several bioinformatics tools and genomic databases, in a flexible way. GARSA is a user-friendly web-based system designed to analyze genomic data in the context of a pipeline. EST and GGS data can be analyzed using the system since it accepts (1) chromatograms, (2) download of sequences from GenBank, (3) Fasta files stored locally or (4) a combination of all three. Quality evaluation of chromatograms, vector removing and clusterization are easily performed as part of the pipeline. A number of local and customizable Blast and CDD analyses can be performed as well as Interpro, complemented with phylogeny analyses. GARSA is being used for the analyses of Trypanosoma vivax (GSS and EST), Trypanosoma rangeli (GSS, EST and ORESTES), Bothrops jararaca (EST), Piaractus mesopotamicus (EST) and Lutzomyia longipalpis (EST). AVAILABILITY: The GARSA system is freely available under GPL license (http://www.biowebdb.org/garsa/). For download requests visit http://www.biowebdb.org/garsa/ or contact Dr Alberto Dávila.

Exploring the genome of Trypanosoma vivax through GSS and in silico comparative analysis.

A survey of the Trypanosoma vivax genome was carried out by the genome sequence survey (GSS) approach resulting in 1,086 genomic sequences. A total of 455 high-quality GSS sequences were generated, consisting of 331 non-redundant sequences distributed in 264 singlets and 67 clusters in a total of 135.5 Kb of the T. vivax genome. The estimation of the overall G+C content, and the prediction of the presence of ORFs and putative genes were carried out using the Glimmer and Jemboss packages. Analysis of the obtained sequences was carried out by BLAST programs against 12 different databases and also using the Conserved Domain Database, InterProScan, and tRNAscan-SE. Along with the existing 23 T. vivax entries in the GenBank, the 32 putative genes predicted and the 331 non-redundant GSS sequences reported herein represent new potential markers for the development of PCRbased assays for specific diagnosis and typing of Trypanosoma vivax.