Advances in the Application of Machine Learning Techniques in Drug Discovery, Design and Development
| Autor: | William B. Langdon, S. J. Barrett |
|---|---|
| Rok vydání: | 2006 |
| Předmět: |
Drug discovery
business.industry Computer science In silico Particle swarm optimization Context (language use) Genetic programming Feature selection High dimensional Machine learning computer.software_genre Support vector machine ComputingMethodologies_PATTERNRECOGNITION Artificial intelligence business computer |
| Zdroj: | Advances in Intelligent and Soft Computing ISBN: 9783540291237 |
| DOI: | 10.1007/978-3-540-36266-1_10 |
| Popis: | Machine learning tools, in particular support vector machines (SVM), Particle Swarm Optimisation (PSO) and Genetic Programming (GP), are increasingly used in pharmaceuticals research and development. They are inherently suitable for use with ‘noisy’, high dimensional (many variables) data, as is commonly used in cheminformatic (i.e. In silico screening), bioinformatic (i.e. bio-marker studies, using DNA chip data) and other types of drug research studies. These aspects are demonstrated via review of their current usage and future prospects in context with drug discovery activities. |
| Databáze: | OpenAIRE |
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