Computational Approaches in Agricultural Research

Schleifer, Klaus‐Jürgen

doi:10.1002/9783527806539.ch7

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Agricultural Research1

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2020

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“…This has led to a situation where the development of a new agrochemical uses much the same methods as drug discovery. [64,65] Thus, both ligand-based and structure-based methods are used. Furthermore, adverse effects like toxicity have to be estimated without using animal testing.…”

Section: Agricultural Researchmentioning

confidence: 99%

Chemistry in Times of Artificial Intelligence

Gasteiger

2020

ChemPhysChem

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Chemists have to a large extent gained their knowledge by doing experiments and thus gather data. By putting various data together and then analyzing them, chemists have fostered their understanding of chemistry. Since the 1960s, computer methods have been developed to perform this process from data to information to knowledge. Simultaneously, methods were developed for assisting chemists in solving their fundamental questions such as the prediction of chemical, physical, or biological properties, the design of organic syntheses, and the elucidation of the structure of molecules. This eventually led to a discipline of its own: chemoinformatics. Chemoinformatics has found important applications in the fields of drug discovery, analytical chemistry, organic chemistry, agrichemical research, food science, regulatory science, material science, and process control. From its inception, chemoinformatics has utilized methods from artificial intelligence, an approach that has recently gained more momentum.

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Section: Agricultural Researchmentioning

confidence: 99%

Chemistry in Times of Artificial Intelligence

Gasteiger

2020

ChemPhysChem

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Computational Approaches in Agricultural Research

Cited by 1 publication

References 30 publications

Chemistry in Times of Artificial Intelligence

Chemistry in Times of Artificial Intelligence

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