Author: Tripathi, Manish Kumar; Nath, Abhigyan; Singh, Tej P.; Ethayathulla, A. S.; Kaur, Punit
Title: Evolving scenario of big data and Artificial Intelligence (AI) in drug discovery Cord-id: 5m7xjfq5 Document date: 2021_6_23
ID: 5m7xjfq5
Snippet: ABSTRACT: The accumulation of massive data in the plethora of Cheminformatics databases has made the role of big data and artificial intelligence (AI) indispensable in drug design. This has necessitated the development of newer algorithms and architectures to mine these databases and fulfil the specific needs of various drug discovery processes such as virtual drug screening, de novo molecule design and discovery in this big data era. The development of deep learning neural networks and their va
Document: ABSTRACT: The accumulation of massive data in the plethora of Cheminformatics databases has made the role of big data and artificial intelligence (AI) indispensable in drug design. This has necessitated the development of newer algorithms and architectures to mine these databases and fulfil the specific needs of various drug discovery processes such as virtual drug screening, de novo molecule design and discovery in this big data era. The development of deep learning neural networks and their variants with the corresponding increase in chemical data has resulted in a paradigm shift in information mining pertaining to the chemical space. The present review summarizes the role of big data and AI techniques currently being implemented to satisfy the ever-increasing research demands in drug discovery pipelines. GRAPHIC ABSTRACT: [Image: see text]
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