Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/11674
Title: PREDICTION OF FUNCTIONAL REGIONS OF A GENE USING SEQUENCE ALIGNMENT
Authors: Smit, Charu
Keywords: ELECTRONICS AND COMPUTER ENGINEERING;SEQUENCE ALIGNMENT;FUNCTIONAL REGIONS;COMPUTING
Issue Date: 2006
Abstract: While the genomes of many organisms have been sequenced over the last few years, transforming such raw sequence data into knowledge remains a hard task. Gene Prediction is of great relevance for all the genomic projects. It is the problem of understanding the way genes are specified in the genome. All the traditional approaches to gene prediction depend on the statistical models and features derived from already known genes thus making it difficult to detect new genes with different properties. Moreover, wrongly annotated genes are automatically used to build new models for gene prediction tools that will then, in turn, pick up even more false genes thereby leading to a vicious circle of wrong sequence annotation. By contrast, comparative sequence analysis is a powerful approach to identify functional elements in genomic sequences. In this thesis a new approach for gene prediction using pairwise sequence alignment and sequence analysis has been proposed. This method is based on the concept of phylogenetic footprinting which states that functional regions in genomic sequences are usually more - conserved than non-functional regions. The program identifies the local sequence homologies and detects the contender regions near the conserved splice junctions. These contender regions are then used to assemble complete gene. In addition to predicting genes the program also gives the alignment of the two sequences which may be used for further comparisons and analysis. The program also has the flexibility to take the aligned sequences as input. With this the run time of the program can be significantly reduced, if a precomputed alignment is provided as input.
URI: http://hdl.handle.net/123456789/11674
Other Identifiers: M.Tech
Research Supervisor/ Guide: Joshi, R. C.
metadata.dc.type: M.Tech Dessertation
Appears in Collections:MASTERS' THESES (E & C)

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