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Methods in Molecular Biology (Clifton, N.J.)|June 13, 2022
iProtGly-SS: A Tool to Accurately Predict Protein Glycation Site Using Structural-Based FeaturesIman Dehzangi, Alok Sharma, Swakkhar ShatabdaProteins|September 6, 2024
DeepPhoPred: Accurate Deep Learning Model to Predict Microbial PhosphorylationFaisal Ahmed, Alok Sharma, Swakkhar Shatabda, et al.Medical & Biological Engineering & Computing|May 3, 2024
SleepBoost: a multi-level tree-based ensemble model for automatic sleep stage classificationAkib Zaman, Shiu Kumar, Swakkhar Shatabda, et al.Scientific Reports|July 6, 2022
A convolutional neural network based tool for predicting protein AMPylation sites from binary profile representationSayed Mehedi Azim, Alok Sharma, Iman Noshadi, et al.Gene|December 12, 2022
CNN-Pred: Prediction of single-stranded and double-stranded DNA-binding protein using convolutional neural networksFarnoush Manavi, Alok Sharma, Ronesh Sharma, et al.Gene|October 22, 2022
Accurately predicting microbial phosphorylation sites using evolutionary and structural featuresFaisal Ahmed, Iman Dehzangi, Md Mehedi Hasan, et al.Journal of Theoretical Biology|September 26, 2017
iPHLoc-ES: Identification of bacteriophage protein locations using evolutionary and structural featuresSwakkhar Shatabda, Sanjay Saha, Alok Sharma, et al.Molecules (Basel, Switzerland)|February 27, 2026
GenReP: An Ensemble Model for Predicting TP53 in Response to Pharmaceutical CompoundsAustin Spadaro, Alok Sharma, Iman DehzangiMethods in Molecular Biology (Clifton, N.J.)|July 2, 2025
CNN-Meth: A Tool to Accurately Predict Lysine Methylation Sites Using Evolutionary Information-Based Protein ModelingAustin Spadaro, Alok Sharma, Iman DehzangiMethods (San Diego, Calif.)|April 11, 2024
Predicting lysine methylation sites using a convolutional neural networkAustin Spadaro, Alok Sharma, Iman DehzangiPageof 42