Current Issue : October - December Volume : 2012 Issue Number : 4 Articles : 6 Articles
Chemical entities are ubiquitous through the biomedical literature and the development of text-mining systems that can efficiently\r\nidentify those entities are required. Due to the lack of available corpora and data resources, the community has focused its efforts\r\nin the development of gene and protein named entity recognition systems, but with the release of ChEBI and the availability of an\r\nannotated corpus, this task can be addressed.We developed a machine-learning-based method for chemical entity recognition and\r\na lexical-similarity-based method for chemical entity resolution and compared them with Whatizit, a popular-dictionary-based\r\nmethod. Our methods outperformed the dictionary-based method in all tasks, yielding an improvement in F-measure of 20% for\r\nthe entity recognition task, 2ââ?¬â??5% for the entity-resolution task, and 15% for combined entity recognition and resolution tasks....
To capitalize on the vast potential of patient genetic information to aid in assuring drug safety, a substantial effort is needed in\r\nboth the training of healthcare professionals and the operational enablement of clinical environments. Our research aims to satisfy\r\nthese needs through the development of a drug safety assurance information system (GeneScription) based on clinical genotyping\r\nthat utilizes patient-specific genetic information to predict and prevent adverse drug responses. In this paper, we present the\r\nmotivations for this work, the algorithms at the heart of GeneScription, and a discussion of our system and its uses. We also\r\ndescribe our efforts to validate GeneScription through its evaluation by practicing pharmacists and pharmacy professors and its\r\nrepeated use in training pharmacists. The positive assessment of the GeneScription software tool by these domain experts provides\r\nstrong validation of the importance, accuracy, and effectiveness of GeneScription....
The GenSensor Suite consists of four web tools for elucidating relationships among genes and proteins. GenPath results show which\r\nbiochemical, regulatory, or other gene set categories are over- or under-represented in an input list compared to a background list.\r\nAll common gene sets are available for searching in GenPath, plus some specialized sets. Users can add custom background lists.\r\nGenInteract builds an interaction gene list from a single gene input and then analyzes this in GenPath. GenPubMed uses a PubMed\r\nquery to identify a list of PubMed IDs, from which a gene list is extracted and queried in GenPath. GenViewer allows the user to\r\nquery one gene set against another in GenPath. GenPath results are presented with relevant P- and q-values in an uncluttered, fully\r\nlinked, and integrated table. Users can easily copy this table and paste it directly into a spreadsheet or document....
Background.Delivery of full doses of adjuvant chemotherapy on schedule is key to optimal breast cancer outcomes.Neutropenia is a\r\nserious complication of chemotherapy and a common barrier to this goal, leading to dose reductions or delays in treatment.While\r\npast research has observed correlations between complete blood count data and neutropenic events, a reliable method of classifying\r\nbreast cancer patients into low- and high-risk groups remains elusive. Patients andMethods. Thirty-five patients receiving adjuvant\r\nchemotherapy for early-stage breast cancer under the care of a single oncologist are examined in this study. FOS-3NN stratifies\r\npatient risk based on complete blood count data after the first cycle of treatment. All classifications are independent of breast\r\ncancer subtype and clinical markers, with risk level determined by the kinetics of patient blood count response to the first cycle\r\nof treatment. Results. In an independent test set of patients unseen by FOS-3NN, 19 out of 21 patients were correctly classified\r\n(Fisher�s exact test probability P < 0.00023 [2 tailed], Matthews� correlation coefficient +0.83). Conclusions. We have developed a\r\nmodel that accurately predicts neutropenic events in a population treated with adjuvant chemotherapy in the first cycle of a 6-cycle\r\ntreatment....
Supertree methods allow to reconstruct large phylogenetic trees by combining smaller trees with overlapping leaf sets into one,\r\nmore comprehensive supertree. The most commonly used supertree method, matrix representation with parsimony (MRP),\r\nproduces accurate supertrees but is rather slow due to the underlying hard optimization problem. In this paper, we present an\r\nextensive simulation study comparing the performance of MRP and the polynomial supertree methodsMinCut Supertree,Modified\r\nMinCut Supertree, Build-with-distances, PhySIC, PhySIC IST, and super distance matrix.We consider both quality and resolution of\r\nthe reconstructed supertrees. Our findings illustrate the tradeoff between accuracy and running time in supertree construction, as\r\nwell as the pros and cons of voting- and veto-based supertree approaches. Based on our results, we make some general suggestions\r\nfor supertree methods yet to come....
Lung cancer is a common cancer, and expression profiling can provide an accurate indication to advance the medical intervention.\r\nHowever, this requires the availability of stably expressed genes as reference. Recent studies had shown that genes that are stably\r\nexpressed in a tissue may not be stably expressed in other tissues suggesting the need to identify stably expressed genes in each\r\ntissue for use as reference genes. DNA microarray analysis has been used to identify those reference genes with low fluctuation.\r\nFourteen datasets with different lung conditions were employed in our study. Coefficient of variance, followed by NormFinder,\r\nwas used to identify stably expressed genes. Our results showed that classical reference genes such as GAPDH and HPRT1 were\r\nhighly variable; thus, they are unsuitable as reference genes. Signal peptidase complex subunit 1 (SPCS1) and hydroxyacyl-CoA\r\ndehydrogenase beta subunit (HADHB), which are involved in fundamental biochemical processes, demonstrated high expression\r\nstability suggesting their suitability in human lung cell profiling....
Loading....