Browsing by Author "Ahsan, Asif"

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    Automate crime news segmentation, knowledge-based generation and public opinion mining for social awareness
    (BRAC University, 2021-06) Sabit, Ahmed Bin; Ahsan, Asif; Tasnim, Zarin; Rasel, Annajiat Alim; Alam, Md. Golam Rabiul
    In the context of the crime scenario in Bangladesh, people face enormous crime situations which can be eradicated by applying some technological solution. For this a research work needs to be conducted by news segmentation and knowledge base generation. This study aims to determine how authority can target crime scenarios based on public opinion for increasing social awareness. Based on this context there will be an algorithm which will sort out the data sheet as well as the mined data will figure out solutions for respective crime scenarios. These data will be collected from news articles from which a data library will be generated by using natural language processing. After analyzing all data, it will automatically notify the authority with a precise report. Further research is needed to identify other factors that could strengthen the effectiveness of this report.
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    Unraveling the potential effects of non-synonymous single nucleotide polymorphisms (nsSNPs) on the Protein structure and function of the human SLC30A8 gene on type 2 diabetes and colorectal cancer: An In silico approach
    (Scopus, 2024-08-31) Uddin, Md Moin; Hossain, Md Tanvir; Hossain, Md Arju; Ahsan, Asif; Shamim, Kamrul Hasan; Hossen, Md Arif; Rahman, Md Shahinur; Rahman, Md Habibur; Ahmed, Kawsar; Bui, Francis M; Zahran, Fahad Ahmed Al-
    Background and aims: The single nucleotide polymorphisms (SNPs) in SLC30A8 gene have been recognized as contributing to type 2 diabetes (T2D) susceptibility and colorectal cancer. This study aims to predict the structural stability, and functional impacts on variations in non-synonymous SNPs (nsSNPs) in the human SLC30A8 gene using various computational techniques. Materials and methods: Several in silico tools, including SIFT, Predict-SNP, SNPs&GO, MAPP, SNAP2, PhD-SNP, PANTHER, PolyPhen-1,PolyPhen-2, I-Mutant 2.0, and MUpro, have been used in our study. Results: After data analysis, out of 336 missenses, the eight nsSNPs, namely R138Q, I141N, W136G, I349N, L303R, E140A, W306C, and L308Q, were discovered by ConSurf to be in highly conserved regions, which could affect the stability of their proteins. Project HOPE determines any significant molecular effects on the structure and function of eight mutated proteins and the three-dimensional (3D) structures of these proteins. The two pharmacologically significant compounds, Luzonoid B and Roseoside demonstrate strong binding affinity to the mutant proteins, and they are more efficient in inhibiting them than the typical SLC30A8 protein using Autodock Vina and Chimera. Increased binding affinity to mutant SLC30A8 proteins has been determined not to influence drug resistance. Ultimately, the Kaplan-Meier plotter study revealed that alterations in SLC30A8 gene expression notably affect the survival rates of patients with various cancer types. Conclusion: Finally, the study found eight highly deleterious missense nsSNPs in the SLC30A8 gene that can be helpful for further proteomic and genomic studies for T2D and colorectal cancer diagnosis. These findings also pave the way for personalized treatments using biomarkers and more effective healthcare strategies.