M
Md. Mukthar Mia
Researcher at Sylhet Agricultural University
Publications - 4
Citations - 9
Md. Mukthar Mia is an academic researcher from Sylhet Agricultural University. The author has contributed to research in topics: Mortality rate & Prevalence. The author has an hindex of 1, co-authored 4 publications receiving 1 citations.
Papers
More filters
Journal ArticleDOI
A systematic review and meta-analysis on prevalence and epidemiological risk factors of zoonotic Fascioliasis infection among the ruminants in Bangladesh
TL;DR: In this article, the authors conducted a systematic review and meta-analysis to determine the authentic knowledge of potential risk factors and prevalence of zoonotic Fascioliasis among livestock populations in Bangladesh.
Journal ArticleDOI
Update on Canine Parvovirus Infection: A Review from the Literature
Md. Mukthar Mia,Mahamudul Hasan +1 more
TL;DR: The literature review encompassed comprehensive knowledge concerning contemporary disease occurrence with causes and transmission imperative for management practice, which can be a baseline for the policymaker, veterinarians and pet owner to limit further outbreaks.
Journal ArticleDOI
Multi-epitope based subunit vaccine construction against Banna virus targeting on two outer proteins (VP4 and VP9): A computational approach.
Md. Mukthar Mia,Mahamudul Hasan,Md. Mahadi Hasan,Sumaya Shargin Khan,Mohammad Nahian Rahman,Shakil Ahmed,Ankita Basak,Md. Nazmuj Sakib,Shrabonti Banik +8 more
TL;DR: In this article, a unique multi-epitope-based peptide vaccine candidate is constructed using bioinformatics tools that efficiently instigate immune cells for generating BAV antibodies.
Journal ArticleDOI
Discovery of mushroom-derived bioactive compound's draggability against nsP3 macro domain, nsP2 protease and envelope glycoprotein of Chikungunya virus: An in silico approach
Md. Mukthar Mia,Mahamudul Hasan,Md. Abir Hasan,Mohammad Abdus Shahid Hossain,Md. Mazharul Islam,Md. Sawkat Hasan Saraf +5 more
TL;DR: In this article, the authors performed molecular docking and dynamics simulation to identify the top candidates for nsP3 macro domains, nsP2 protease, and envelope glycoprotein complex inhibitors, as well as to predict possible therapeutic candidates.