DeepOlf is a deep neural network-based prediction model, developed on a large dataset of odorants, non-odorants and olfactory receptors (ORs), using a potential set of physiochemical properties and molecular fingerprints. It allows accurate inference of an odorant over a set of olfactory receptors.

Download files and follow the software installation tutorial.


Software Installation Tutorial

Step 1

Install Anaconda3-5.2 or above.

Step 2

Install or upgrade following libraries (python, numpy, tensorflow, keras, scikit-learn).

Step 3

Download and extract zipped file.

Step 4

Prepare input file (user_input.csv). Calculate molecular properties and fingerprints from SMILES or sdf format of a chemical compound using software’s like PaDel, alvaDesc (recommended), DRAGON, etc. and save as user_input.csv. Keep the header information (first row) as such in input file.

Step 5

Change value of path variable in to the extracted folder and execute the script.

Citation: Sharma, Anju; Kumar, Rajnish; Semwal, Rahul; Aier, Imlimaong; Tyagi, Pankaj; Varadwaj, Pritish, DeepOlf: Deep neural network based architecture for predicting odorants and their interacting Olfactory Receptors.(Communicated)