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User: Mohd Saberi Licence: by-sa
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Blob Reconstructing Metabolic Networks - A Review. Advanc...

Created: 2013-05-12 03:31:42

Credits: User Mohd Saberi

License: Creative Commons Attribution-Share Alike 3.0 Unported License

Y.W. Choon, M.S. Mohamad.  Vol. 1, pp. 26-40. UTM Press. 2011. ISBN: 978-983-52-0822-5.

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Blob Automation of DNA Computing Readout Method Based on...

Created: 2013-05-12 03:29:28

Credits: User Mohd Saberi

License: Creative Commons Attribution-Share Alike 3.0 Unported License

M.F.M. Saaid, S. Sudin, I. Ibrahim, Z.M. Yusof, K. Khalil, J.A.A. Mukred, M.S. Mohamad, N. Mokhtar, Z. Ibrahim, J. Watada. (2012). International Journal of Innovative Computing, Information and Control. Vol. 8, No. 3(A), pp. 1907-1916. ICIC International. Indexed by ISI and SCOPUS.

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Blob An Improved Swarm Optimization for Parameter Estima...

Created: 2013-05-12 03:27:02

Credits: User Mohd Saberi

License: Creative Commons Attribution-Share Alike 3.0 Unported License

A. Abdullah, S. Deris, M.S. Mohamad, S. Anwar. (2013). PLoS ONE, Vol. 8, No. 4, pp. e61258. PLoS. Indexed by ISI and SCOPUS.

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Blob Validation of Hierarchical Gene Clusters Using Repea...

Created: 2013-05-12 03:24:34

Credits: User Mohd Saberi

License: Creative Commons Attribution-Share Alike 3.0 Unported License

L.F. Tee, M.S. Mohamad, S. Deris, A.A.M. Faudzi, M.S.A. Latiff, R. Sallehuddin. (2013). Jurnal Teknologi. Vol. 6. No. 1, pp. 7-12. UTM Press. Index by Scopus. 

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Blob Validation of Hierarchical Gene Clusters Using Repea...

Created: 2013-05-12 03:22:20

Credits: User Mohd Saberi

License: Creative Commons Attribution-Share Alike 3.0 Unported License

 L.F. Tee, M.S. Mohamad, S. Deris, A.A.M. Faudzi, M.S.A. Latiff, R. Sallehuddin. (2013). Jurnal Teknologi. Vol. 6. No. 1, pp. 7-12. UTM Press. Index by Scopus. 

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Blob A Review of Computational Approaches for In Silico M...

Created: 2013-05-12 03:20:56

Credits: User Mohd Saberi

License: Creative Commons Attribution-Share Alike 3.0 Unported License

W. H. Chan, M. S. Mohamad, S. Deris and R. M. Illias.  (2013). Current Bioinformatics. Vol. 8, No. 2, pp. 253-258. Bentham Science Publishers. Indexed by ISI and SCOPUS.

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Blob A New Hybrid Bee Evolution Algorithm for parameter E...

Created: 2013-05-12 03:18:27

Credits: User Mohd Saberi

License: Creative Commons Attribution-Share Alike 3.0 Unported License

A. Abdullah, S. Deris, M.S Mohamad. (2013) ICIC Express Letter Part B: Application, Vol 4 (1), p. 1-6. ICIC International.

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Blob Using A Dynamic Bayesian Network-based Model for Inf...

Created: 2012-07-24 04:51:56

Credits: User Mohd Saberi

License: Creative Commons Attribution-Share Alike 3.0 Unported License

 Largely due to the technological advances in bioinformatics, researchers are now garnering interests in inferring gene regulatory networks (GRNs) from gene expression data which is otherwise unfeasible in the past. This is because of the need of researchers to uncover the potentially vast information and understand the dynamic behavior of the GRNs. In this regard, dynamic Bayesian network (DBN) has been broadly utilized for the inference of GRNs thanks to its ability to handle time-seri...

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Blob Aspartate Biosynthesis Pathway Simulation Using an I...

Created: 2012-07-24 04:49:23

Credits: User Mohd Saberi

License: Creative Commons Attribution-Share Alike 3.0 Unported License

 An improved Differential Evolution algorithm (IDE) is proposed in this paper. It is aimed at enhancing its efficiency in estimating the relevant kinetic parameters for metabolic pathway data to simulate aspartate biosynthesis pathway for plant model Arabidopsis. Metabolic pathway data are anticipated to be of vital help in the development of effectual tools in parameter estimation and kinetic modeling platforms. However, a number of computation algorithms face difficulty, produces low a...

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Blob Gene Knockout Strategies Identification by Using a H...

Created: 2012-07-24 04:48:16

Credits: User Mohd Saberi

License: Creative Commons Attribution-Share Alike 3.0 Unported License

 By optimizing microbial strains it is possible to improve product yield or improve growth characteristics. Microbial strains can be optimized through genetic engineering. It is proven that through genetic engineering it is able to obtain the desirable phenotypes. However, it is difficult to predict the effects of genetic modifications on the resulting phenotype due to the complexity of the networks. Optimization algorithms are implemented in previous works in order to identify the effec...

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