Md. Mehedi Hasan

Overview

Best Publications

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

  Md. Mehedi Hasan;Md. Mehedi Hasan;Nalini Schaduangrat;Shaherin Basith;Gwang Lee

  189
  Citations

• 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

  170
  Citations

• PreAIP: Computational Prediction of Anti-inflammatory Peptides by Integrating Multiple Complementary Features

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

  163
  Citations

• 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

  158
  Citations

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

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

  127
  Citations

• 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

  123
  Citations

• SuccinSite: a computational tool for the prediction of protein succinylation sites by exploiting the amino acid patterns and properties

  Md. Mehedi Hasan;Shiping Yang;Yuan Zhou;Md. Nurul Haque Mollah

  122
  Citations

• iBitter-SCM: Identification and characterization of bitter peptides using a scoring card method with propensity scores of dipeptides

  Phasit Charoenkwan;Janchai Yana;Nalini Schaduangrat;Chanin Nantasenamat

  118
  Citations

• iDPPIV-SCM: A Sequence-Based Predictor for Identifying and Analyzing Dipeptidyl Peptidase IV (DPP-IV) Inhibitory Peptides Using a Scoring Card Method.

  Phasit Charoenkwan;Sakawrat Kanthawong;Chanin Nantasenamat;Md. Mehedi Hasan

  91
  Citations

• Computational Identification of Protein Pupylation Sites by Using Profile-Based Composition of k-Spaced Amino Acid Pairs

  Md. Mehedi Hasan;Yuan Zhou;Xiaotian Lu;Jinyan Li

  91
  Citations

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

  Mehedi Hasan;Mehedi Hasan;Ashad Alam;Watshara Shoombuatong;Hong-Wen Deng

  84
  Citations

• i4mC-ROSE, a bioinformatics tool for the identification of DNA N4-methylcytosine sites in the Rosaceae genome.

  Md. Mehedi Hasan;Balachandran Manavalan;Mst. Shamima Khatun;Hiroyuki Kurata

  79
  Citations

• GPSuc: Global Prediction of Generic and Species-specific Succinylation Sites by aggregating multiple sequence features.

  Md. Mehedi Hasan;Hiroyuki Kurata

  72
  Citations

• Improved prediction and characterization of anticancer activities of peptides using a novel flexible scoring card method.

  Phasit Charoenkwan;Wararat Chiangjong;Vannajan Sanghiran Lee;Chanin Nantasenamat

  71
  Citations

• i6mA-Fuse: improved and robust prediction of DNA 6 mA sites in the Rosaceae genome by fusing multiple feature representation

  Md. Mehedi Hasan;Md. Mehedi Hasan;Balachandran Manavalan;Watshara Shoombuatong;Mst. Shamima Khatun

  68
  Citations

• 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

  67
  Citations

• i4mC-Mouse: Improved identification of DNA N4-methylcytosine sites in the mouse genome using multiple encoding schemes.

  Md. Mehedi Hasan;Md. Mehedi Hasan;Balachandran Manavalan;Watshara Shoombuatong;Mst. Shamima Khatun

  63
  Citations

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

  Shaherin Basith;Md. Mehedi Hasan;Md. Mehedi Hasan;Gwang Lee;Leyi Wei;Leyi Wei

  63
  Citations

• Computational identification of protein S-sulfenylation sites by incorporating the multiple sequence features information

  Md. Mehedi Hasan;Dianjing Guo;Hiroyuki Kurata

  53
  Citations

• Prediction of S-nitrosylation sites by integrating support vector machines and random forest.

  Md. Mehedi Hasan;Md. Mehedi Hasan;Balachandran Manavalan;Mst. Shamima Khatun;Hiroyuki Kurata

  52
  Citations