Authors :
Jishnu Raj R, Sherin K R, Neelima philopaul, Shilji Rajan, AmbilI M P, Deepthi K
Volume/Issue :
Volume 5 - 2020, Issue 4 - April
Google Scholar :
http://bitly.ws/9nMw
Scribd :
https://bit.ly/36g6rqk
Abstract :
Number of unknown and rare diseases are
increas-ing day by day. There are only 2000 drugs and
more than 35000 known diseases. Existing drugs can be
used to treat new diseases.It is known as drugrepositioning.Since drug discovery is a costly and time
consuming process computational methods are
necessary. Machine learning methods can be applied for
drug repositioning. A deep-neural network is trained
with drug sim-ilarity , disease similarity and known
drug-disease associations. Once trained, the neural
network can be used to predict new drug-disease
associations. The neural network gives new drug-disease
associations with its corresponding probabilities.
Keywords :
Machine learning, Bioinformatics, Drug reposi-tioning.
Number of unknown and rare diseases are
increas-ing day by day. There are only 2000 drugs and
more than 35000 known diseases. Existing drugs can be
used to treat new diseases.It is known as drugrepositioning.Since drug discovery is a costly and time
consuming process computational methods are
necessary. Machine learning methods can be applied for
drug repositioning. A deep-neural network is trained
with drug sim-ilarity , disease similarity and known
drug-disease associations. Once trained, the neural
network can be used to predict new drug-disease
associations. The neural network gives new drug-disease
associations with its corresponding probabilities.
Keywords :
Machine learning, Bioinformatics, Drug reposi-tioning.
