PubMed · 15670535
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Usman Ahmad, Ahmed Ijaz Gillani. 2005. Towards exploring our genes.. https://doi.org/01.2005/jcpsp.6262
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The nuclear factor-kappa B (NF-kappaB) signaling pathway is a multi-component pathway that regulates the expression of hundreds of genes that are involved in diverse and key cellular and organismal processes, including cell proliferation, cell survival, the cellular stress response, innate immunity and inflammation. Not surprisingly, mis-regulation of the NF-kappaB pathway, either by mutation or epigenetic mechanisms, is involved in many human and animal diseases, especially ones associated with chronic inflammation, immunodeficiency or cancer. This review describes human diseases in which mutations in the components of the core NF-kappaB signaling pathway have been implicated and discusses the molecular mechanisms by which these alterations in NF-kappaB signaling are likely to contribute to the disease pathology. These mutations can be germline or somatic and include gene amplification (e.g., REL), point mutations and deletions (REL, NFKB2, IKBA, CYLD, NEMO) and chromosomal translocations (BCL-3). In addition, human genetic diseases are briefly described wherein mutations affect protein modifiers or transducers of NF-kappaB signaling or disrupt NF-kappaB-binding sites in promoters/enhancers.
BACKGROUND: Genomic functional information is valuable for biomedical research. However, such information frequently needs to be extracted from the scientific literature and structured in order to be exploited by automatic systems. Natural language processing is increasingly used for this purpose although it inherently involves errors. A postprocessing strategy that selects relations most likely to be correct is proposed and evaluated on the output of SemGen, a system that extracts semantic predications on the etiology of genetic diseases. Based on the number of intervening phrases between an argument and its predicate, we defined a heuristic strategy to filter the extracted semantic relations according to their likelihood of being correct. We also applied this strategy to relations identified with co-occurrence processing. Finally, we exploited postprocessed SemGen predications to investigate the genetic basis of Parkinson's disease. RESULTS: The filtering procedure for increased precision is based on the intuition that arguments which occur close to their predicate are easier to identify than those at a distance. For example, if gene-gene relations are filtered for arguments at a distance of 1 phrase from the predicate, precision increases from 41.95% (baseline) to 70.75%. Since this proximity filtering is based on syntactic structure, applying it to the results of co-occurrence processing is useful, but not as effective as when applied to the output of natural language processing. In an effort to exploit SemGen predications on the etiology of disease after increasing precision with postprocessing, a gene list was derived from extracted information enhanced with postprocessing filtering and was automatically annotated with GFINDer, a Web application that dynamically retrieves functional and phenotypic information from structured biomolecular resources. Two of the genes in this list are likely relevant to Parkinson's disease but are not associated with this disease in several important databases on genetic disorders. CONCLUSION: Information based on the proximity postprocessing method we suggest is of sufficient quality to be profitably used for subsequent applications aimed at uncovering new biomedical knowledge. Although proximity filtering is only marginally effective for enhancing the precision of relations extracted with co-occurrence processing, it is likely to benefit methods based, even partially, on syntactic structure, regardless of the relation.