Minería de textos y medicina: utilidad en las enfermedades respiratorias / Text Mining and Medicine: Usefulness in Respiratory Diseases

Cada vez es más habitual disponer de información médica en formato electrónico. Esto incluye tanto artículos científicos como revisiones sobre el manejo clínico e incluso registros de instituciones sanitarias con datos de pacientes. Sin embargo, los instrumentos tradicionales, tanto individuales como institucionales, son poco útiles para seleccionar la información más apropiada en cada caso, sea en el ámbito clínico o en el de la investigación. La llamada «minería» de textos o de datos permite gestionar esa gran cantidad de información, extrayéndola de fuentes diversas mediante sistemas de procesamiento (filtrado y curado), integrándola y permitiendo la generación de nuevo conocimiento. La presente revisión pretende proporcionar una idea general sobre la minería de textos y datos, así como sobre la ayuda que esta técnica bioinformática puede suponer para el ejercicio asistencial de la medicina respiratoria y para la investigación en ese mismo campo

It is increasingly common to have medical information in electronic format. This includes scientific articles as well as clinical management reviews, and even records from health institutions with patient data. However, traditional instruments, both individual and institutional, are of little use for selecting the most appropriate information in each case, either in the clinical or research field. So-called text or data «mining» enables this huge amount of information to be managed, extracting it from various sources using processing systems (filtration and curation), integrating it and permitting the generation of new knowledge. This review aims to provide an overview of text and data mining, and of the potential usefulness of this bioinformatic technique in the exercise of care in respiratory medicine and in research in the same field

Text mining and medicine: usefulness in respiratory diseases.

It is increasingly common to have medical information in electronic format. This includes scientific articles as well as clinical management reviews, and even records from health institutions with patient data. However, traditional instruments, both individual and institutional, are of little use for selecting the most appropriate information in each case, either in the clinical or research field. So-called text or data «mining¼ enables this huge amount of information to be managed, extracting it from various sources using processing systems (filtration and curation), integrating it and permitting the generation of new knowledge. This review aims to provide an overview of text and data mining, and of the potential usefulness of this bioinformatic technique in the exercise of care in respiratory medicine and in research in the same field.

Preservation of protein clefts in comparative models.

BACKGROUND: Comparative, or homology, modelling of protein structures is the most widely used prediction method when the target protein has homologues of known structure. Given that the quality of a model may vary greatly, several studies have been devoted to identifying the factors that influence modelling results. These studies usually consider the protein as a whole, and only a few provide a separate discussion of the behaviour of biologically relevant features of the protein. Given the value of the latter for many applications, here we extended previous work by analysing the preservation of native protein clefts in homology models. We chose to examine clefts because of their role in protein function/structure, as they are usually the locus of protein-protein interactions, host the enzymes' active site, or, in the case of protein domains, can also be the locus of domain-domain interactions that lead to the structure of the whole protein. RESULTS: We studied how the largest cleft of a protein varies in comparative models. To this end, we analysed a set of 53507 homology models that cover the whole sequence identity range, with a special emphasis on medium and low similarities. More precisely we examined how cleft quality - measured using six complementary parameters related to both global shape and local atomic environment, depends on the sequence identity between target and template proteins. In addition to this general analysis, we also explored the impact of a number of factors on cleft quality, and found that the relationship between quality and sequence identity varies depending on cleft rank amongst the set of protein clefts (when ordered according to size), and number of aligned residues. CONCLUSION: We have examined cleft quality in homology models at a range of seq.id. levels. Our results provide a detailed view of how quality is affected by distinct parameters and thus may help the user of comparative modelling to determine the final quality and applicability of his/her cleft models. In addition, the large variability in model quality that we observed within each sequence bin, with good models present even at low sequence identities (between 20% and 30%), indicates that properly developed identification methods could be used to recover good cleft models in this sequence range.

Involvement of chromatin and histone deacetylation in SV40 T antigen transcription regulation.

Simian Virus 40 (SV40) large T antigen (T Ag) is a multifunctional viral oncoprotein that regulates viral and cellular transcriptional activity. However, the mechanisms by which such regulation occurs remain unclear. Here we show that T antigen represses CBP-mediated transcriptional activity. This repression is concomitant with histone H3 deacetylation and is TSA sensitive. Moreover, our results demonstrate that T antigen interacts with HDAC1 in vitro in an Rb-independent manner. In addition, the overexpression of HDAC1 cooperates with T antigen to antagonize CBP transactivation function and correlates with chromatin deacetylation of the TK promoter. Finally, decreasing HDAC1 levels with small interfering RNA (siRNA) partially abolishes T antigen-induced repression. These findings highlight the importance of the histone acetylation/deacetylation balance in the cellular transformation mediated by oncoviral proteins.