Simulation and human-computer interaction to analyze gene regulatory networks
With rapid development in information technology, it has also become a great help to biological research and studies. Among the plentiful software applications developed to analyze Gene Regulatory Networks (GRN), GeneNetWeaver (GNW) is one of the most useful applications with its rich features and i...
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sg-ntu-dr.10356-589732023-03-03T20:49:18Z Simulation and human-computer interaction to analyze gene regulatory networks Linn, Htet Oo School of Computer Engineering Bioinformatics Research Centre Zheng Jie DRNTU::Engineering::Computer science and engineering::Information systems::Information interfaces and presentation With rapid development in information technology, it has also become a great help to biological research and studies. Among the plentiful software applications developed to analyze Gene Regulatory Networks (GRN), GeneNetWeaver (GNW) is one of the most useful applications with its rich features and interactive Graphical User Interface (GUI). In order to make it the best out of the best ones, in this project, functionality of GNW has been enhanced by integrating more features into it. With these, the efficiency and effectiveness of the application will be fully utilized. In this project, we have integrated important features such as visualizing the gene expression datasets generated from GRN, which would greatly improve users’ convenience. Another essential feature we have developed is allowing users to modify the structure of GRN by deleting nodes (genes) or edges (interactions), which could simulate ‘knock-out’ experiments. Moreover, to help users realize the effects of particular modification to GRN structure, we have implemented the feature to compare the gene expression data before and after the modification. These new features will offer users great help to gain further understanding into the function of GRN. Bachelor of Engineering (Computer Science) 2014-04-17T07:10:51Z 2014-04-17T07:10:51Z 2014 2014 Final Year Project (FYP) http://hdl.handle.net/10356/58973 en Nanyang Technological University 62 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering::Information systems::Information interfaces and presentation Linn, Htet Oo Simulation and human-computer interaction to analyze gene regulatory networks |
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With rapid development in information technology, it has also become a great help to biological research and studies. Among the plentiful software applications developed to analyze Gene Regulatory Networks (GRN), GeneNetWeaver (GNW) is one of the most useful applications with its rich features and interactive Graphical User Interface (GUI). In order to make it the best out of the best ones, in this project, functionality of GNW has been enhanced by integrating more features into it. With these, the efficiency and effectiveness of the application will be fully utilized. In this project, we have integrated important features such as visualizing the gene expression datasets generated from GRN, which would greatly improve users’ convenience. Another essential feature we have developed is allowing users to modify the structure of GRN by deleting nodes (genes) or edges (interactions), which could simulate ‘knock-out’ experiments. Moreover, to help users realize the effects of particular modification to GRN structure, we have implemented the feature to compare the gene expression data before and after the modification. These new features will offer users great help to gain further understanding into the function of GRN. |
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School of Computer Engineering |
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School of Computer Engineering Linn, Htet Oo |
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Final Year Project |
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Linn, Htet Oo |
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Linn, Htet Oo |
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Simulation and human-computer interaction to analyze gene regulatory networks |
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Simulation and human-computer interaction to analyze gene regulatory networks |
title_full |
Simulation and human-computer interaction to analyze gene regulatory networks |
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Simulation and human-computer interaction to analyze gene regulatory networks |
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Simulation and human-computer interaction to analyze gene regulatory networks |
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simulation and human-computer interaction to analyze gene regulatory networks |
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2014 |
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http://hdl.handle.net/10356/58973 |
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1759855133518200832 |