EventsMOL2NET'15, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 1st ed.
Published
This submission belongs to the session 04. NICEXSM-01: North-Ibero-American Congress on Exp. and Simul. Methods, Valencia-Miami, USA, 2015 of the event MOL2NET'15, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 1st ed.
Published date
02 Dec, 2015
Citation
Zhi Liang Tan, Claudia Giovanna Peñuelas-Rivas, Esvieta Tenorio-Borroto, Yong Liu, Fatty Acids Distribution Networks in Ruminal Membrane by Computational and Experimental Studies, in Proceedings of MOL2NET'15, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 1st ed., 5 December–15 December 2015, MDPI: Basel, Switzerland, doi: 10.3390/MOL2NET-1-b004
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Fatty Acids Distribution Networks in Ruminal Membrane by Computational and Experimental Studies

Claudia Giovanna Peñuelas-Rivas 3
1. Key Laboratory of Subtropical Agro-ecological Engineering, Institute of Subtropical Agriculture, the Chinese Academy of Sciences, Changsha, Hunan, 410125, P. R. China
2. Computer Science Faculty, University of A Coruña, Campus de Elviña s/n, A Coruña, 15071, Spain
3. Faculty of Veterinary Medicine and Animal Science, Autonomous University of the State of Mexico, Toluca, 50090, México
Abstract

The present communication introduces a new classification model for fatty acids (FA) distribution networks in ruminal microbe membrane based on experimental and computational studies. In the experimental part, long chain fatty acids and volatile fatty acids in ruminal microbe membrane or liquid phase were investigated by supplementation of different ratios of Omega-6 / Omega-3 and in the processes of base- / acid- methylation. In the computational part, Perturbation Theory (PT) and Linear Free-Energy Relationships (LFER), combined with corresponding Box-Jenkins (ΔVkj) and PT Operators (ΔΔVkj) were applied into the calculation of physicochemical parameters (Vk) of fatty acids. The best PT-LFER model found to predict the effects of perturbations over the FA distribution network with Sensitivity, Specificity, and Accuracy > 80% for 407,655 cases. In final, PT-LFER model based on LDA was used to reconstruct the complex networks of perturbations in the FA distribution and compared with random Erdős–Rényi network models. The detail results have been published in Mol. BioSyst., 2015, Aug., the present is a short communications.

Keywords
Fatty acids
Distribution networks
Computational
Experimental
Ruminal membrane
Manuscript
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