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Artificial Neural Network - Multi-Objective Genetic Algorithm based optimization for the enhanced pigment accumulation in Synechocystis sp. PCC 6803.

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第一作者： Namrata,Bhagat

第一单位： Enzyme Technology and Protein Bioinformatics Laboratory, School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi, 221005, India.

作者： Namrata,Bhagat ^[1] ; Guddu Kumar,Gupta ^[1] ; Amritpreet Kaur,Minhas ^[2] ; Deepak,Chhabra ^[3] ; Pratyoosh,Shukla ^[4]

作者单位： Enzyme Technology and Protein Bioinformatics Laboratory, School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi, 221005, India. ^[1] TERI Deakin Nanobiotechnology Centre, Sustainable Agriculture Division, The Energy and Resources Institute, New Delhi, India. ^[2] Department of Mechanical Engineering, University Institute of Engineering and Technology (UIET), Maharshi Dayanand University, Rohtak, Haryana, 124001, India. ^[3] Enzyme Technology and Protein Bioinformatics Laboratory, School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi, 221005, India. pratyoosh.shukla@gmail.com. ^[4]

关键词 Synechocystis sp. PCC 6803 Abiotic stress Artificial neural network (ANN)Carotenoids Cyanobacteria Multi-objective genetic algorithm (MOGA)

医学主题词集胞藻属(Synechocystis);算法(Algorithms);色素类, 生物学(Pigments, Biological);藻青蛋白(Phycocyanin);类胡萝卜素类(Carotenoids);叶绿素(Chlorophyll)

DOI 10.1186/s12896-025-00955-9

PMID 40089695

发布时间 2025-07-24

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