Publications by authors named "Syed Md Galib"
Article Synopsis
- The Bay of Bengal, the largest bay in the world, is rich in natural resources and diverse ecosystems, but its microbial diversity remains underexplored.
- Research focused on microbial communities from Bangladesh's eastern coast, specifically Saint Martin and Cox's Bazar, found that Proteobacteria were the dominant phylum, with specific genera like Alteromonas and Vibrio being prevalent.
- The study highlights the functional capabilities of these microbial communities, including biofilm formation and antimicrobial resistance, providing essential insights for understanding their role in ecological health and the impacts of environmental changes.
The dataset of Leaf Color Chart (PaddyNet) is publicly unavailable. As far as the author's knowledge, this is the first dataset about paddy leaves based on LCC. This dataset has been generated by collecting images from a particular location such as Sajiali, Dogachia and Shyamnagar at Jashore, Bangladesh.
View Article and Find Full Text PDFBackground And Aims: Since the beginning of the SARS-CoV-2 pandemic, multiple new variants have emerged posing an increased risk to global public health. This study aimed to investigate SARS-CoV-2 variants, their temporal dynamics, infection rate (IFR) and case fatality rate (CFR) in Bangladesh by analyzing the published genomes.
Methods: We retrieved 6610 complete whole genome sequences of the SARS-CoV-2 from the GISAID (Global Initiative on Sharing all Influenza Data) platform from March 2020 to October 2022, and performed different in-silico bioinformatics analyses.
Populations of different South Asian nations including Bangladesh reportedly have a high risk of developing diabetes in recent years. This study aimed to investigate the differences in the gut microbiome of COVID-19-positive participants with or without type 2 diabetes mellitus (T2DM) compared with healthy control subjects. Microbiome data of 30 participants with T2DM were compared with 22 age-, sex-, and body mass index (BMI)-matched individuals.
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