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Title: Finding key genes of gene networks
Authors: Se, Ronald Xi Yang.
Keywords: DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences
Issue Date: 2012
Abstract: Huge advancement in the field of bioinformatics has unleashed torrential of biological data that were previously unavailable. With the introduction of new information, researchers are now able to gain more insight and understanding into many biological processes. One such process is gene regulatory networks (GRN). Key regulators have powerful control over GRN compared to other genes. Identifying key regulators allows researchers to manipulate them and thus be able to control many biological processes, ranging from increasing production of bio-fuels and developing treatment for specific diseases. This report will cover a computational approach in identifying key regulators in GRN. GRN is modeled using a graphical approach and algorithms are proposed to transverse the network in order to identify key genes. The algorithms were validated on known GRN. They were proved relatively accurate as they were able to identify the key genes which are similar to the known results.
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

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