Machine Learning in Drug Discovery
نویسندگان
چکیده
منابع مشابه
Drug Discovery by Machine Learning Method
The aim of this work is to create a one-class classification model using the method of support vector clustering and evaluate its usefulness in drug discovery. The one-class classification model is tested on both sonar data and 5-HT2A-binding compound data. From the results, 88.99 % accuracy is obtained for sonar data and 93.269 % testing accuracy is obtained for classification of 5-HT2Abinding...
متن کاملMachine-learning approaches in drug discovery: methods and applications.
During the past decade, virtual screening (VS) has evolved from traditional similarity searching, which utilizes single reference compounds, into an advanced application domain for data mining and machine-learning approaches, which require large and representative training-set compounds to learn robust decision rules. The explosive growth in the amount of public domain-available chemical and bi...
متن کاملApplication of Machine Learning in Drug Discovery and Development
Machine learning techniques have been widely used in drug discovery and development, particularly in the areas of cheminformatics, bioinformatics and other types of pharmaceutical research. It has been demonstrated they are suitable for large high dimensional data, and the models built with these methods can be used for robust external predictions. However, various problems and challenges still...
متن کاملApplication of Machine Learning in Knowledge Discovery for Pharmaceutical Drug-drug Interactions
Artificial neural networks (ANNs) have been developed to predict the clinical significance of drug-drug interactions (DDIs) for a set of 35 pharmaceutical drugs using data compiled from the Web-based resources, Lexicomp® and Vidal®, with inputs furnished by various drug pharmacokinetic (PK) and/or pharmacodynamic (PD) properties, and/or drug-enzyme interaction data. Success in prediction of DDI...
متن کاملHuman Discovery and Machine Learning
Submission to IJCINI This paper studies machine learning paradigms from the point of view of human cognition. Indeed, conceptions in both mahine learning and human learning evolved from a passive to an active conception of learning. Our objective is to provide an interaction protocol suited to both humans and machines, to enable assisting human discoveries by learning machines. We identify the ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Chemical Information and Modeling
سال: 2019
ISSN: 1549-9596,1549-960X
DOI: 10.1021/acs.jcim.9b00136