ACADSTAFF UGM
| Title | : | Modeling Gene Regulation in Graded Hypoxia Using Continuous-Time Markov Chains |
| Author | : |
PUTU INDAH CIPTAYANI (1) Prof. Dr.-Ing. Mhd. Reza M. I. Pulungan, S.Si., M.Sc. (2) |
| Date | : | 0 2013 |
| Keyword | : | Stochastic, Gene regulation, Graded hypoxia, Continuous-time Markov chain, Stochastic hybrid model Stochastic, Gene regulation, Graded hypoxia, Continuous-time Markov chain, Stochastic hybrid model |
| Abstract | : | Hypoxia inducible factor (HIF) is the main protein in hypoxia pathway. The response of HIF to changes of oxygen pressure is regulated by 2 oxygen sensors, prolyl hydroxylase (PHD) and factor inhibiting HIF (FIH). Studies have shown that biochemical reactions at molecular level actually exhibit stochastic and random behaviors. Modeling biochemical reactions using purely deterministic method, therefore, ignore these characteristics. Hence, we use stochastic modeling using CTMC to model this regulation. Nevertheless, the use of pure CTMC on complex biochemical reaction networks, such as hypoxia, results in an infeasible computation time and typically requires very large memory. Therefore, we use a numerical hybrid method that combines pure CTMC and deterministic methods. The purpose is to reduce time complexity and to obtain a better accuracy than deterministic method. Using this model, we can observe that an increase of oxygen pressure results in a decrease in the amount of HIF and that oxygen sensor FIH only inhibits C-TAD activity. The model is also able to classify 84% genes that were observed. |
| Group of Knowledge | : | Ilmu Komputer |
| Original Language | : | English |
| Level | : | Internasional |
| Status | : |
Published
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