Newly identified families of human endogenous retroviruses.
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Biomedical subjects
Nalini Polavarapu
Publications and source records attributed to Nalini Polavarapu.
Identification, characterization and comparative genomics of chimpanzee endogenous retroviruses.
BACKGROUND: Retrotransposons, the most abundant and widespread class of eukaryotic transposable elements, are believed to play a significant role in mutation and disease and to have contributed significantly to the evolution of genome structure and function. The recent sequencing of the chimpanzee genome is providing an unprecedented opportunity to study the functional significance of these elements in two closely related primate species and to better evaluate their role in primate evolution. RESULTS: We report here that the chimpanzee genome contains at least 42 separate families of endogenous retroviruses, nine of which were not previously identified. All but two (CERV 1/PTERV1 and CERV 2) of the 42 families of chimpanzee endogenous retroviruses were found to have orthologs in humans. Molecular analysis (PCR and Southern hybridization) of CERV 2 elements demonstrates that this family is present in chimpanzee, bonobo, gorilla and old-world monkeys but absent in human, orangutan and new-world monkeys. A survey of endogenous retroviral positional variation between chimpanzees and humans determined that approximately 7% of all chimpanzee-human INDEL variation is associated with endogenous retroviral sequences. CONCLUSION: Nine families of chimpanzee endogenous retroviruses have been transpositionally active since chimpanzees and humans diverged from a common ancestor. Seven of these transpositionally active families have orthologs in humans, one of which has also been transpositionally active in humans since the human-chimpanzee divergence about six million years ago. Comparative analyses of orthologous regions of the human and chimpanzee genomes have revealed that a significant portion of INDEL variation between chimpanzees and humans is attributable to endogenous retroviruses and may be of evolutionary significance.
Animals↗
Investigation into biomedical literature classification using support vector machines.
Specific topic search in the PubMed Database, one of the most important information resources for scientific community, presents a big challenge to the users. The researcher typically formulates boolean queries followed by scanning the retrieved records for relevance, which is very time consuming and error prone. We applied Support Vector Machines (SVM) for automatic retrieval of PubMed articles related to Human genome epidemiological research at CDC (Center for disease Control and Prevention). In this paper, we discuss various investigations into biomedical literature classification and analyze the effect of various issues related to the choice of keywords, training sets, kernel functions and parameters for the SVM technique. We report on the various factors above to show that SVM is a viable technique for automatic classification of biomedical literature into topics of interest such as epidemiology, cancer, birth defects etc. In all our experiments, we achieved high values of PPV, sensitivity and specificity.
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