Md. Mehedi Hasan

According to our database, Md. Mehedi Hasan authored at least 19 papers between 2018 and 2022.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2022

DeepDNAbP: A deep learning-based hybrid approach to improve the identification of deoxyribonucleic acid-binding proteins.

Md. Faruk Hosen, S. M. Hasan Mahmud, Kawsar Ahmed, Wenyu Chen, Mohammad Ali Moni, Hong-Wen Deng, Watshara Shoombuatong, Md. Mehedi Hasan

Comput. Biol. Medicine, 2022

BERT6mA: prediction of DNA N6-methyladenine site using deep learning-based approaches.

Sho Tsukiyama, Md. Mehedi Hasan, Hong-Wen Deng, Hiroyuki Kurata

Briefings Bioinform., 2022

TACOS: a novel approach for accurate prediction of cell-specific long noncoding RNAs subcellular localization.

Young-Jun Jeon, Md. Mehedi Hasan, Hyun Woo Park, Ki Wook Lee, Balachandran Manavalan

Briefings Bioinform., 2022

2021

IRC-Fuse: improved and robust prediction of redox-sensitive cysteine by fusing of multiple feature representations.

Md. Mehedi Hasan, Md. Ashad Alam, Watshara Shoombuatong, Hiroyuki Kurata

J. Comput. Aided Mol. Des., 2021

Convolutional neural networks with image representation of amino acid sequences for protein function prediction.

Samia Tasnim Sara, Md. Mehedi Hasan, Ahsan Ahmad, Swakkhar Shatabda

Comput. Biol. Chem., 2021

BERT4Bitter: a bidirectional encoder representations from transformers (BERT)-based model for improving the prediction of bitter peptides.

Phasit Charoenkwan, Chanin Nantasenamat, Md. Mehedi Hasan, Balachandran Manavalan, Watshara Shoombuatong

Bioinform., 2021

LSTM-PHV: prediction of human-virus protein-protein interactions by LSTM with word2vec.

Sho Tsukiyama, Md. Mehedi Hasan, Satoshi Fujii, Hiroyuki Kurata

Briefings Bioinform., 2021

Meta-i6mA: an interspecies predictor for identifying DNA N6-methyladenine sites of plant genomes by exploiting informative features in an integrative machine-learning framework.

Md. Mehedi Hasan, Shaherin Basith, Mst. Shamima Khatun, Gwang Lee, Balachandran Manavalan, Hiroyuki Kurata

Briefings Bioinform., 2021

StackIL6: a stacking ensemble model for improving the prediction of IL-6 inducing peptides.

Phasit Charoenkwan, Wararat Chiangjong, Chanin Nantasenamat, Md. Mehedi Hasan, Balachandran Manavalan, Watshara Shoombuatong

Briefings Bioinform., 2021

Integrative machine learning framework for the identification of cell-specific enhancers from the human genome.

Shaherin Basith, Md. Mehedi Hasan, Gwang Lee, Leyi Wei, Balachandran Manavalan

Briefings Bioinform., 2021

NeuroPred-FRL: an interpretable prediction model for identifying neuropeptide using feature representation learning.

Md. Mehedi Hasan, Md. Ashad Alam, Watshara Shoombuatong, Hong-Wen Deng, Balachandran Manavalan, Hiroyuki Kurata

Briefings Bioinform., 2021

2020

iUmami-SCM: A Novel Sequence-Based Predictor for Prediction and Analysis of Umami Peptides Using a Scoring Card Method with Propensity Scores of Dipeptides.

Phasit Charoenkwan, Janchai Yana, Chanin Nantasenamat, Md. Mehedi Hasan, Watshara Shoombuatong

J. Chem. Inf. Model., 2020

ProIn-Fuse: improved and robust prediction of proinflammatory peptides by fusing of multiple feature representations.

Mst. Shamima Khatun, Md. Mehedi Hasan, Watshara Shoombuatong, Hiroyuki Kurata

J. Comput. Aided Mol. Des., 2020

Meta-iPVP: a sequence-based meta-predictor for improving the prediction of phage virion proteins using effective feature representation.

Phasit Charoenkwan, Chanin Nantasenamat, Md. Mehedi Hasan, Watshara Shoombuatong

J. Comput. Aided Mol. Des., 2020

iLBE for Computational Identification of Linear B-cell Epitopes by Integrating Sequence and Evolutionary Features.

Md. Mehedi Hasan, Mst. Shamima Khatun, Hiroyuki Kurata

Genom. Proteom. Bioinform., 2020

Computational prediction of protein ubiquitination sites mapping on <i>Arabidopsis thaliana</i>.

Md. Parvez Mosharaf, Md. Mehedi Hasan, Fee Faysal Ahmed, Mst. Shamima Khatun, Mohammad Ali Moni, Md. Nurul Haque Mollah

Comput. Biol. Chem., 2020

HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation.

Md. Mehedi Hasan, Nalini Schaduangrat, Shaherin Basith, Gwang Lee, Watshara Shoombuatong, Balachandran Manavalan

Bioinform., 2020

2018

SIPMA: A Systematic Identification of Protein-Protein Interactions in Zea mays Using Autocorrelation Features in a Machine-Learning Framework.

Mst. Shamima Khatun, Md. Mehedi Hasan, Md. Nurul Haque Mollah, Hiroyuki Kurata

Proceedings of the 18th IEEE International Conference on Bioinformatics and Bioengineering, 2018

iLMS, Computational Identification of Lysine-Malonylation Sites by Combining Multiple Sequence Features.

Md. Mehedi Hasan, Hiroyuki Kurata

Proceedings of the 18th IEEE International Conference on Bioinformatics and Bioengineering, 2018