By a News Reporter-Staff News Editor at Information Technology Newsweekly -- Fresh data on Bioinformatics are presented in a new report. According to news reporting originating from Buffalo, New York, by VerticalNews correspondents, research stated, "New technologies are focusing on characterizing cell types to better understand their heterogeneity. With large volumes of cellular data being generated, innovative methods are needed to structure the resulting data analyses."
Our news editors obtained a quote from the research from the State University of New York, "Here, we describe an 'Ontologically BAsed Molecular Signature' (OBAMS) method that identifies novel cellular biomarkers and infers biological functions as characteristics of particular cell types. This method finds molecular signatures for immune cell types based on mapping biological samples to the Cell Ontology (CL) and navigating the space of all possible pairwise comparisons between cell types to find genes whose expression is core to a particular cell type's identity. We illustrate this ontological approach by evaluating expression data available from the Immunological Genome project (IGP) to identify unique biomarkers of mature B cell subtypes. We find that using OBAMS, candidate biomarkers can be identified at every strata of cellular identity from broad classifications to very granular. Furthermore, we show that Gene Ontology can be used to cluster cell types by shared biological processes in order to find candidate genes responsible for somatic hypermutation in germinal center B cells. Moreover, through in silico experiments based on this approach, we have identified genes sets that represent genes overexpressed in germinal center B cells and identify genes uniquely expressed in these B cells compared to other B cell types."
According to the news editors, the research concluded: "This work demonstrates the utility of incorporating structured ontological knowledge into biological data analysis -providing a new method for defining novel biomarkers and providing an opportunity for new biological insights."
For more information on this research see: Ontology based molecular signatures for immune cell types via gene expression analysis. Bmc Bioinformatics, 2013;14():263. (BioMed Central - www.biomedcentral.com/; Bmc Bioinformatics - www.biomedcentral.com/bmcbioinformatics/)
The news editors report that additional information may be obtained by contacting T.F. Meehan, Dept. of Neurology, University at Buffalo School of Medicine and Biomedical Sciences, 100 High Street, Buffalo, NY 14203, United States. Additional authors for this research include N.A. Vasilevsky, C.J. Mungall, D.S. Dougall, M.A. Haendel, J.A. Blake and A.D Diehl.
Keywords for this news article include: Buffalo, New York, United States, Bioinformatics, Machine Learning, Emerging Technologies, Gene Expression Analysis, North and Central America.
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