Bayesian Filtering Approach to Improve Gene Regulatory Networks Inference Using Gene Expression Time Series, M.Sc. Thesis Sharif University of Technology ; Fatemizadeh, Emadoddin (Supervisor) ; Arab, Shahriar (Co-Advisor)
Abstract
Gene regulatory modeling in different species is one of the main aims of Bioinformatics. Regarding the limitations of the data available and the perspectives which should be taken into account for modeling such networks, proposed methods up to now have not yet been successful in yielding a comprehensive model. In one of the recent researches, the Gene regulation process is considered as a nonlinear dynamic stochastic process and described by state space equations. Afterwards, in order for the unknown parameters to be estimated, Extended Kalman Filtering is used. In this thesis, first of all, Gene complexes are taken into consideration instead of genes and afterwards, Extended Kalman...
Cataloging briefBayesian Filtering Approach to Improve Gene Regulatory Networks Inference Using Gene Expression Time Series, M.Sc. Thesis Sharif University of Technology ; Fatemizadeh, Emadoddin (Supervisor) ; Arab, Shahriar (Co-Advisor)
Abstract
Gene regulatory modeling in different species is one of the main aims of Bioinformatics. Regarding the limitations of the data available and the perspectives which should be taken into account for modeling such networks, proposed methods up to now have not yet been successful in yielding a comprehensive model. In one of the recent researches, the Gene regulation process is considered as a nonlinear dynamic stochastic process and described by state space equations. Afterwards, in order for the unknown parameters to be estimated, Extended Kalman Filtering is used. In this thesis, first of all, Gene complexes are taken into consideration instead of genes and afterwards, Extended Kalman...
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