pLMSNOSite: an ensemble-based approach for predicting protein S-nitrosylation sites by integrating supervised word embedding and embedding from pre-trained protein language model von Pratyush, Pawel, Pokharel, Suresh, Saigo, Hiroto, Kc, Dukka B

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DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction von Thapa, Niraj, Chaudhari, Meenal, McManus, Sean, Roy, Kaushik, Newman, Robert H., Saigo, Hiroto, KC, Dukka B.

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DeepNGlyPred: A Deep Neural Network-Based Approach for Human N-Linked Glycosylation Site Prediction von Pakhrin, Subash C., Aoki-Kinoshita, Kiyoko F., Caragea, Doina, Dukka, B. K. C.

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Deep Learning-Based Advances in Protein Structure Prediction von Pakhrin, Subash C., Shrestha, Bikash, Adhikari, Badri, KC, Dukka B.

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Improving protein succinylation sites prediction using embeddings from protein language model von Pokharel, Suresh, Pratyush, Pawel, Heinzinger, Michael, Newman, Robert H., KC, Dukka B.

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Experimental Study: Deep Learning-Based Fall Monitoring among Older Adults with Skin-Wearable Electronics von Lee, Yongkuk, Pokharel, Suresh, Muslim, Asra Al, Kc, Dukka B, Lee, Kyoung Hag, Yeo, Woon-Hong

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DFT-aided machine learning-based discovery of magnetism in Fe-based bimetallic chalcogenides von Pant, Dharmendra, Pokharel, Suresh, Mandal, Subhasish, KC, Dukka B., Pati, Ranjit

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Einstein–Roscoe regression for the slag viscosity prediction problem in steelmaking von Saigo, Hiroto, KC, Dukka B., Saito, Noritaka

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Deep Learning–Based Advances In Protein Posttranslational Modification Site and Protein Cleavage Prediction von Pakhrin, Subash C., Pokharel, Suresh, Saigo, Hiroto, KC, Dukka B.

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RF-GlutarySite: a random forest based predictor for glutarylation sites von AL-barakati, Hussam J, Saigo, Hiroto, Newman, Robert H, KC, Dukka B

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Comparison of Machine Learning and Deep Learning Models for Network Intrusion Detection Systems von Thapa, Niraj, Liu, Zhipeng, KC, Dukka B., Gokaraju, Balakrishna, Roy, Kaushik

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Computational Methods for Predicting Post-Translational Modification Sites von KC, Dukka B

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A deep learning based approach for prediction of Chlamydomonas reinhardtii phosphorylation sites von Thapa, Niraj, Chaudhari, Meenal, Iannetta, Anthony A., White, Clarence, Roy, Kaushik, Newman, Robert H., Hicks, Leslie M., KC, Dukka B.

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CNN-BLPred: a Convolutional neural network based predictor for β-Lactamases (BL) and their classes von White, Clarence, Ismail, Hamid D, Saigo, Hiroto, Kc, Dukka B

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Integrating Embeddings from Multiple Protein Language Models to Improve Protein O-GlcNAc Site Prediction von Pokharel, Suresh, Pratyush, Pawel, Ismail, Hamid D., Ma, Junfeng, KC, Dukka B.

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RF-Phos: A Novel General Phosphorylation Site Prediction Tool Based on Random Forest von Newman, Robert H., Kim, Jung H., Jones, Ahoi, Ismail, Hamid D., KC, Dukka B.

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SVM-SulfoSite: A support vector machine based predictor for sulfenylation sites von AL-barakati, Hussam J., McConnell, Evan W., Hicks, Leslie M., Poole, Leslie B., Newman, Robert H., KC, Dukka B.

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Hydrogen peroxide-dependent oxidation of ERK2 within its D-recruitment site alters its substrate selection von Postiglione, Anthony E., Adams, Laquaundra L., Ekhator, Ese S., Odelade, Anuoluwapo E., Patwardhan, Supriya, Chaudhari, Meenal, Pardue, Avery S., Kumari, Anjali, LeFever, William A., Tornow, Olivia P., Kaoud, Tamer S., Neiswinger, Johnathan, Jeong, Jun Seop, Parsonage, Derek, Nelson, Kimberly J., Kc, Dukka B., Furdui, Cristina M., Zhu, Heng, Wommack, Andrew J., Dalby, Kevin N., Dong, Ming, Poole, Leslie B., Keyes, Jeremiah D., Newman, Robert H.

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Correction: DeepSuccinylSite: a deep learning based approach for protein succinylation site prediction von Thapa, Niraj, Chaudhari, Meenal, McManus, Sean, Roy, Kaushik, Newman, Robert H, Saigo, Hiroto, KC, Dukka B

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DTL-DephosSite: Deep Transfer Learning Based Approach to Predict Dephosphorylation Sites von Chaudhari, Meenal, Thapa, Niraj, Ismail, Hamid, Chopade, Sandhya, Caragea, Doina, Koehn, Maja, Newman, Robert H., KC, Dukka B.

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