4 papers
ChoiceNet: CNN learning through choice of multiple feature map representations
Farshid Rayhan, Aphrodite Galata, Timothy F. Cootes
We introduce a new architecture called ChoiceNet where each layer of the network is highly connected with skip connections and channelwise concatenations. This enables the network…
FRnet-DTI: Deep Convolutional Neural Networks with Evolutionary and Structural Features for Drug-Target Interaction
Farshid Rayhan, Sajid Ahmed, Zaynab Mousavian +2
The task of drug-target interaction prediction holds significant importance in pharmacology and therapeutic drug design. In this paper, we present FRnet-DTI, an auto encoder and a…
LIUBoost : Locality Informed Underboosting for Imbalanced Data Classification
Sajid Ahmed, Farshid Rayhan, Asif Mahbub +4
The problem of class imbalance along with class-overlapping has become a major issue in the domain of supervised learning. Most supervised learning algorithms assume equal cardinal…
iDTI-ESBoost: Identification of Drug Target Interaction Using Evolutionary and Structural Features with Boosting
Farshid Rayhan, Sajid Ahmed, Swakkhar Shatabda +4
Prediction of new drug-target interactions is extremely important as it can lead the researchers to find new uses for old drugs and to realize the therapeutic profiles or side effe…