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Computational Biology and Chemistry
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February 7, 2021
diSBPred: A machine learning based approach for disulfide bond prediction
Avdesh Mishra, Md Wasi Ul Kabir, Md Tamjidul Hoque
IEEE/ACM Transactions on Computational Biology and Bioinformatics
|
November 13, 2010
Twin removal in genetic algorithms for protein structure prediction using low-resolution model
Md Tamjidul Hoque, Madhu Chetty, Andrew Lewis, et al.
Bioinformatics (Oxford, England)
|
March 8, 2021
ClassifyTE: a stacking-based prediction of hierarchical classification of transposable elements
Manisha Panta, Avdesh Mishra, Md Tamjidul Hoque, et al.
Artificial Intelligence in Medicine
|
March 9, 2021
AIRBP: Accurate identification of RNA-binding proteins using machine learning techniques
Avdesh Mishra, Reecha Khanal, Wasi Ul Kabir, et al.
Methods in Molecular Biology (Clifton, N.J.)
|
April 5, 2019
StackSSSPred: A Stacking-Based Prediction of Supersecondary Structure from Sequence
Michael Flot, Avdesh Mishra, Aditi Sharma Kuchi, et al.
Biorxiv : the Preprint Server for Biology
|
February 6, 2026
ESMDisPred: A Structure-Aware CNN-Transformer Architecture for Intrinsically Disordered Protein Prediction
Md Wasi Ul Kabir, Ayon Dey, Farzeen Nafees, et al.
Journal of Theoretical Biology
|
November 10, 2015
A balanced secondary structure predictor
Md Nasrul Islam, Sumaiya Iqbal, Ataur R Katebi, et al.
Biomed Research International
|
November 14, 2013
Mixing energy models in genetic algorithms for on-lattice protein structure prediction
Mahmood A Rashid, M A Hakim Newton, Md Tamjidul Hoque, et al.
Computational Biology and Chemistry
|
February 16, 2016
Guided macro-mutation in a graded energy based genetic algorithm for protein structure prediction
Mahmood A Rashid, Sumaiya Iqbal, Firas Khatib, et al.
Computers in Biology and Medicine
|
January 31, 2024
DRBpred: A sequence-based machine learning method to effectively predict DNA- and RNA-binding residues
Md Wasi Ul Kabir, Duaa Mohammad Alawad, Pujan Pokhrel, et al.
Page
of 3
Search research articles
Search
Showing results (11-20 of 28) with videos related to
Sort By:
Page
of 3
Computational Biology and Chemistry
|
February 7, 2021
diSBPred: A machine learning based approach for disulfide bond prediction
Avdesh Mishra, Md Wasi Ul Kabir, Md Tamjidul Hoque
IEEE/ACM Transactions on Computational Biology and Bioinformatics
|
November 13, 2010
Twin removal in genetic algorithms for protein structure prediction using low-resolution model
Md Tamjidul Hoque, Madhu Chetty, Andrew Lewis, et al.
Bioinformatics (Oxford, England)
|
March 8, 2021
ClassifyTE: a stacking-based prediction of hierarchical classification of transposable elements
Manisha Panta, Avdesh Mishra, Md Tamjidul Hoque, et al.
Artificial Intelligence in Medicine
|
March 9, 2021
AIRBP: Accurate identification of RNA-binding proteins using machine learning techniques
Avdesh Mishra, Reecha Khanal, Wasi Ul Kabir, et al.
Methods in Molecular Biology (Clifton, N.J.)
|
April 5, 2019
StackSSSPred: A Stacking-Based Prediction of Supersecondary Structure from Sequence
Michael Flot, Avdesh Mishra, Aditi Sharma Kuchi, et al.
Biorxiv : the Preprint Server for Biology
|
February 6, 2026
ESMDisPred: A Structure-Aware CNN-Transformer Architecture for Intrinsically Disordered Protein Prediction
Md Wasi Ul Kabir, Ayon Dey, Farzeen Nafees, et al.
Journal of Theoretical Biology
|
November 10, 2015
A balanced secondary structure predictor
Md Nasrul Islam, Sumaiya Iqbal, Ataur R Katebi, et al.
Biomed Research International
|
November 14, 2013
Mixing energy models in genetic algorithms for on-lattice protein structure prediction
Mahmood A Rashid, M A Hakim Newton, Md Tamjidul Hoque, et al.
Computational Biology and Chemistry
|
February 16, 2016
Guided macro-mutation in a graded energy based genetic algorithm for protein structure prediction
Mahmood A Rashid, Sumaiya Iqbal, Firas Khatib, et al.
Computers in Biology and Medicine
|
January 31, 2024
DRBpred: A sequence-based machine learning method to effectively predict DNA- and RNA-binding residues
Md Wasi Ul Kabir, Duaa Mohammad Alawad, Pujan Pokhrel, et al.
Page
of 3