Md Mehedi Hasan
Research Assistant Professor
Department of Pathobiological Sciences
LSU School of Veterinary Medicine
Louisiana State University
Baton Rouge, LA 70803
Hire Date: November 13, 2023
Education
PhD, China Agricultural University, 2016
MSc, Rajshahi University (Bangladesh), 2012
BSc, Rajshahi University (Bangladesh), 2010
Research Interest
My academic training and research experience have equipped me with expertise in multiple disciplines, including statistics, bioinformatics, and genetics. With a background in both Statistics and Bioinformatics, I have conducted research in bioinformatics and data science for several years, focusing on areas such as bulk RNAseq, single-cell RNAseq, single-cell ATACseq, spatial transcriptomics, multi-omics, and protein structure prediction. My research interests are in machine learning, deep learning, NGS data analysis, bioinformatics, and statistics.
Teaching Interest
NGS data analysis, Bioinformatics, and Statistics
Awards and Honors
2011, Merit-based Gold Medal Award based on Bachelor of Science result from Nawab Abdul Latif Hall, Rajshahi University, Rajshahi, Bangladesh
2011, Merit-based student award, Professor Manowar Hossain Scholarship Award Based on Bachelor of Science result, Department of Statistics, Rajshahi University, Bangladesh
2012, MOE scholarship award based on MSC result, Rajshahi University, Bangladesh
2012, PhD scholarship, Chinese Scholarship Council, 2012.
2019, JSPS Postdoctoral Fellowship scholarship award, Japan Society for the Promotion of Sciences
Publications
Kurata H, Harun-Or-Roshid M, Mehedi Hasan M, Tsukiyama S, Maeda K, Manavalan B. MLm5C: A high-precision human RNA 5-methylcytosine sites predictor based on a combination of hybrid machine learning models. Methods. 2024 Jul;227:37-47.
Harrison MAA, Morris SL, Rudman GA, Rittenhouse DJ, Hasan MM, Shamima Khatun M, Wang H, Garfinkel LP, Norton EB, Kim S, Kolls JK, Michal Jazwinski S, Zwezdaryk KJ. Intermittent cytomegalovirus infection alters neurobiological metabolism and induces cognitive deficits in mice. Brain Behav Immun. 2024 Jan 3;117:36-50.
Hasan MM, Tsukiyama S, Cho JY, Kurata H, Alam MA, Liu X, Manavalan B, Deng HW. Deepm5C: A deep-learning-based hybrid framework for identifying human RNA N5-methylcytosine sites using a stacking strategy. Mol Ther. 2022 Aug 3;30(8):2856-2867.
Tsukiyama S, Hasan MM, Fujii S, Kurata H. LSTM-PHV: prediction of human-virus protein-protein interactions by LSTM with word2vec. Brief Bioinform. 2021 Nov 5;22(6):bbab228.
Khatun MS, Shoombuatong W, Alam MA, Mollah MNH, Kurata H, Hasan MM*. Recent development of bioinformatics tools for microRNA target prediction, Current Medicinal Chemistry, 2021,DOI : 10.2174/0929867328666210804090224
Hasan MM, Schaduangrat N, Basith S, Lee G, Shoombuatong W, Manavalan B. HLPpred-Fuse: improved and robust prediction of hemolytic peptide and its activity by fusing multiple feature representation. Bioinformatics. 2020 Jun 1;36(11):3350-3356.
Hasan MM, Basith S, Khatun MS, Lee G, Manavalan B, Kurata K. Meta-i6mA: an interspecies predictor for identifying DNA N6-methyladenine sites of plant genomes by exploiting informative features in an integrative machine-learning framework. Briefings in Bioinformatics 2020. bbaa202, https://doi.org/10.1093/bib/bbaa202. (Impact Factor= 11.922)
Manavalan B, Hasan MM, Basith S, Shin TH, Lee G. Empirical comparison and analysis of web-based DNA N4-methylcytosine site prediction tools. Molecular Therapy - Nucleic Acids 2020. doi.org/10.1016/j.omtn.2020.09.010
Hasan MM, Khatun MS, Kurata H. iLBE for Computational Identification of Linear B-cell Epitopes by Integrating Sequence and Evolutionary Features. Genomics Proteomics Bioinformatics. 2020 Oct;18(5):593-600.
Hasan MM, Manavalan M, Khatun MS, and Kurata H. i4mC-ROSE, A Bioinformatics Tool for the Identification of DNA N4-methylcytosine Sites in the Rosaceae Genome, International Journal of Biological Macromolecules, 2020,157:752-758. doi: 10.1016/j.ijbiomac.2019.12.009.
1Hasan MM, Khatun MS, Mollah MNH, Yong C, and Dianjing G. A systematic identification of species-specific protein succinylation sites using joint element features information. International Journal of Nanomedicine, 12:6303-6315. doi: 10.2147/IJN.S140875 (2017).