Prediction of Human Drug Targets and Their Interactions Using Machine Learning Methods: Current and Future Perspectives

  • Abhigyan Nath
  • Priyanka Kumari
  • Radha Chaube
Part of the Methods in Molecular Biology book series (MIMB, volume 1762)


Identification of drug targets and drug target interactions are important steps in the drug-discovery pipeline. Successful computational prediction methods can reduce the cost and time demanded by the experimental methods. Knowledge of putative drug targets and their interactions can be very useful for drug repurposing. Supervised machine learning methods have been very useful in drug target prediction and in prediction of drug target interactions. Here, we describe the details for developing prediction models using supervised learning techniques for human drug target prediction and their interactions.

Key words

Drug target identification Drug target interaction Feature selection Machine learning 



Partial support from UGC-CAS to RC is acknowledged.


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Abhigyan Nath
    • 1
  • Priyanka Kumari
    • 2
  • Radha Chaube
    • 1
  1. 1.Department of Zoology, Institute of ScienceBanaras Hindu UniversityVaranasiIndia
  2. 2.Department of BiotechnologyDelhi Technological UniversityDelhiIndia

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