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Hamid D Ismail

Showing results (1-10 of 12) with videos related to

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IEEE/ACM Transactions on Computational Biology and Bioinformatics|July 11, 2018
RF-NR: Random Forest Based Approach for Improved Classification of Nuclear ReceptorsHamid D Ismail, Hiroto Saigo, Dukka B Kc
Molecular Biosystems|June 14, 2016
RF-Hydroxysite: a random forest based predictor for hydroxylation sitesHamid D Ismail, Robert H Newman, Dukka B Kc
BMC Bioinformatics|January 4, 2018
CNN-BLPred: a Convolutional neural network based predictor for β-Lactamases (BL) and their classesClarence White, Hamid D Ismail, Hiroto Saigo, et al.
International Journal of Molecular Sciences|August 7, 2021
A Review of the Neutrophil Extracellular Traps (NETs) from Cow, Sheep and Goat ModelsMulumebet Worku, Djaafar Rehrah, Hamid D Ismail, et al.
Bioinformatics (Oxford, England)|April 25, 2024
LMCrot: an enhanced protein crotonylation site predictor by leveraging an interpretable window-level embedding from a transformer-based protein language modelPawel Pratyush, Soufia Bahmani, Suresh Pokharel, et al.
International Journal of Molecular Sciences|November 14, 2023
Integrating Embeddings from Multiple Protein Language Models to Improve Protein <i>O</i>-GlcNAc Site PredictionSuresh Pokharel, Pawel Pratyush, Hamid D Ismail, et al.
Methods in Molecular Biology (Clifton, N.J.)|November 22, 2024
LMPTMSite: A Platform for PTM Site Prediction in Proteins Leveraging Transformer-Based Protein Language ModelsPawel Pratyush, Suresh Pokharel, Hamid D Ismail, et al.
Biomed Research International|April 12, 2016
RF-Phos: A Novel General Phosphorylation Site Prediction Tool Based on Random ForestHamid D Ismail, Ahoi Jones, Jung H Kim, et al.
Bioinformatics (Oxford, England)|March 21, 2025
CaLMPhosKAN: prediction of general phosphorylation sites in proteins via fusion of codon aware embeddings with amino acid aware embeddings and wavelet-based Kolmogorov-Arnold networkPawel Pratyush, Callen Carrier, Suresh Pokharel, et al.
Journal of Proteome Research|July 17, 2023
LMPhosSite: A Deep Learning-Based Approach for General Protein Phosphorylation Site Prediction Using Embeddings from the Local Window Sequence and Pretrained Protein Language ModelSubash C Pakhrin, Suresh Pokharel, Pawel Pratyush, et al.
Pageof 2

Showing results (1-10 of 12) with videos related to

Sort By:
Pageof 2
IEEE/ACM Transactions on Computational Biology and Bioinformatics|July 11, 2018
RF-NR: Random Forest Based Approach for Improved Classification of Nuclear ReceptorsHamid D Ismail, Hiroto Saigo, Dukka B Kc
Molecular Biosystems|June 14, 2016
RF-Hydroxysite: a random forest based predictor for hydroxylation sitesHamid D Ismail, Robert H Newman, Dukka B Kc
BMC Bioinformatics|January 4, 2018
CNN-BLPred: a Convolutional neural network based predictor for β-Lactamases (BL) and their classesClarence White, Hamid D Ismail, Hiroto Saigo, et al.
International Journal of Molecular Sciences|August 7, 2021
A Review of the Neutrophil Extracellular Traps (NETs) from Cow, Sheep and Goat ModelsMulumebet Worku, Djaafar Rehrah, Hamid D Ismail, et al.
Bioinformatics (Oxford, England)|April 25, 2024
LMCrot: an enhanced protein crotonylation site predictor by leveraging an interpretable window-level embedding from a transformer-based protein language modelPawel Pratyush, Soufia Bahmani, Suresh Pokharel, et al.
International Journal of Molecular Sciences|November 14, 2023
Integrating Embeddings from Multiple Protein Language Models to Improve Protein <i>O</i>-GlcNAc Site PredictionSuresh Pokharel, Pawel Pratyush, Hamid D Ismail, et al.
Methods in Molecular Biology (Clifton, N.J.)|November 22, 2024
LMPTMSite: A Platform for PTM Site Prediction in Proteins Leveraging Transformer-Based Protein Language ModelsPawel Pratyush, Suresh Pokharel, Hamid D Ismail, et al.
Biomed Research International|April 12, 2016
RF-Phos: A Novel General Phosphorylation Site Prediction Tool Based on Random ForestHamid D Ismail, Ahoi Jones, Jung H Kim, et al.
Bioinformatics (Oxford, England)|March 21, 2025
CaLMPhosKAN: prediction of general phosphorylation sites in proteins via fusion of codon aware embeddings with amino acid aware embeddings and wavelet-based Kolmogorov-Arnold networkPawel Pratyush, Callen Carrier, Suresh Pokharel, et al.
Journal of Proteome Research|July 17, 2023
LMPhosSite: A Deep Learning-Based Approach for General Protein Phosphorylation Site Prediction Using Embeddings from the Local Window Sequence and Pretrained Protein Language ModelSubash C Pakhrin, Suresh Pokharel, Pawel Pratyush, et al.
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