DCGAN-DTA: Predicting drug-target binding affinity with deep convolutional generative adversarial networks
Mahmood Kalemati,
Mojtaba Zamani Emani,
Somayyeh Koohi
Abstract:Background
In recent years, there has been a growing interest in utilizing computational approaches to predict drug-target binding affinity, aiming to expedite the early drug discovery process. To address the limitations of experimental methods, such as cost and time, several machine learning-based techniques have been developed. However, these methods encounter certain challenges, including the limited availability of training data, reliance on human intervention for feature selection and engi… Show more
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