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Elife
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January 18, 2023
Transformer-based deep learning for predicting protein properties in the life sciences
Abel Chandra, Laura Tünnermann, Tommy Löfstedt, et al.
Scientific Reports
|
November 28, 2023
PepCNN deep learning tool for predicting peptide binding residues in proteins using sequence, structural, and language model features
Abel Chandra, Alok Sharma, Iman Dehzangi, et al.
BMC Molecular and Cell Biology
|
December 21, 2019
Bigram-PGK: phosphoglycerylation prediction using the technique of bigram probabilities of position specific scoring matrix
Abel Chandra, Alok Sharma, Abdollah Dehzangi, et al.
NAR Genomics and Bioinformatics
|
October 24, 2025
An ensemble-based model comprising deep learning for predicting peptide-binding residues in proteins
Abel Chandra, Iman Dehzangi, Tatsuhiko Tsunoda, et al.
Scientific Reports
|
December 19, 2018
PhoglyStruct: Prediction of phosphoglycerylated lysine residues using structural properties of amino acids
Abel Chandra, Alok Sharma, Abdollah Dehzangi, et al.
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Search research articles
Search
Showing results (1-10 of 5) with videos related to
Sort By:
Page
of 1
Elife
|
January 18, 2023
Transformer-based deep learning for predicting protein properties in the life sciences
Abel Chandra, Laura Tünnermann, Tommy Löfstedt, et al.
Scientific Reports
|
November 28, 2023
PepCNN deep learning tool for predicting peptide binding residues in proteins using sequence, structural, and language model features
Abel Chandra, Alok Sharma, Iman Dehzangi, et al.
BMC Molecular and Cell Biology
|
December 21, 2019
Bigram-PGK: phosphoglycerylation prediction using the technique of bigram probabilities of position specific scoring matrix
Abel Chandra, Alok Sharma, Abdollah Dehzangi, et al.
NAR Genomics and Bioinformatics
|
October 24, 2025
An ensemble-based model comprising deep learning for predicting peptide-binding residues in proteins
Abel Chandra, Iman Dehzangi, Tatsuhiko Tsunoda, et al.
Scientific Reports
|
December 19, 2018
PhoglyStruct: Prediction of phosphoglycerylated lysine residues using structural properties of amino acids
Abel Chandra, Alok Sharma, Abdollah Dehzangi, et al.
Page
of 1