Browsing by Author "Melamud, Eugene"

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    BIOINFORMATIC ANALYSIS OF THE FUNCTIONAL AND STRUCTURAL IMPLICATIONS OF ALTERNATIVE SPLICING.
    (2007-01-23) Melamud, Eugene; Moult, John; Molecular and Cell Biology; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)
    In higher Eukaryotes, upon transcription of a gene, a complex set of reactions take place to remove fragments of a sequence (introns) from transcribed RNA. A large macro-molecular machine (the spliceosome) recognizes the ends of introns, brings ends into close proximity and catalyzes the splicing reaction. The selection of the location of the ends of introns (splice sites) determines the final message produced at the end of the process. In some cases, an alternative set of splice sites are chosen, and as a consequence different message is produced. This phenomenon is known as alternative splicing. It is now realized that nearly every Human gene undergoes alternative splicing, producing large variability in types and number of transcripts produced. In this thesis, we examine the functional and structural consequences of alternative splicing on proteins, we look into the mechanism of formation of complex splicing patterns, and examine the role of noise in the process.
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    SNPs3D: Candidate gene and SNP selection for association studies
    (Springer Nature, 2006-03-22) Yue, Peng; Melamud, Eugene; Moult, John
    The relationship between disease susceptibility and genetic variation is complex, and many different types of data are relevant. We describe a web resource and database that provides and integrates as much information as possible on disease/gene relationships at the molecular level. The resource http://www.SNPs3D.org has three primary modules. One module identifies which genes are candidates for involvement in a specified disease. A second module provides information about the relationships between sets of candidate genes. The third module analyzes the likely impact of non-synonymous SNPs on protein function. Disease/candidate gene relationships and gene-gene relationships are derived from the literature using simple but effective text profiling. SNP/protein function relationships are derived by two methods, one using principles of protein structure and stability, the other based on sequence conservation. Entries for each gene include a number of links to other data, such as expression profiles, pathway context, mouse knockout information and papers. Gene-gene interactions are presented in an interactive graphical interface, providing rapid access to the underlying information, as well as convenient navigation through the network. Use of the resource is illustrated with aspects of the inflammatory response and hypertension. The combination of SNP impact analysis, a knowledge based network of gene relationships and candidate genes, and access to a wide range of data and literature allow a user to quickly assimilate available information, and so develop models of gene-pathway-disease interaction.