Browsing by Author "Mahmood K"

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    Bio-Inspired Energy-Efficient Cluster-Based Routing Protocol for the IoT in Disaster Scenarios.
    (MDPI (Basel, Switzerland), 2024-08-19) Ahmed S; Hossain MA; Chong PHJ; Ray SK; Farhan M; Mahmood K; Jabbar S
    The Internet of Things (IoT) is a promising technology for sensing and monitoring the environment to reduce disaster impact. Energy is one of the major concerns for IoT devices, as sensors used in IoT devices are battery-operated. Thus, it is important to reduce energy consumption, especially during data transmission in disaster-prone situations. Clustering-based communication helps reduce a node's energy decay during data transmission and enhances network lifetime. Many hybrid combination algorithms have been proposed for clustering and routing protocols to improve network lifetime in disaster scenarios. However, the performance of these protocols varies widely based on the underlying network configuration and the optimisation parameters considered. In this research, we used the clustering parameters most relevant to disaster scenarios, such as the node's residual energy, distance to sink, and network coverage. We then proposed the bio-inspired hybrid BOA-PSO algorithm, where the Butterfly Optimisation Algorithm (BOA) is used for clustering and Particle Swarm Optimisation (PSO) is used for the routing protocol. The performance of the proposed algorithm was compared with that of various benchmark protocols: LEACH, DEEC, PSO, PSO-GA, and PSO-HAS. Residual energy, network throughput, and network lifetime were considered performance metrics. The simulation results demonstrate that the proposed algorithm effectively conserves residual energy, achieving more than a 17% improvement for short-range scenarios and a 10% improvement for long-range scenarios. In terms of throughput, the proposed method delivers a 60% performance enhancement compared to LEACH, a 53% enhancement compared to DEEC, and a 37% enhancement compared to PSO. Additionally, the proposed method results in a 60% reduction in packet drops compared to LEACH and DEEC, and a 30% reduction compared to PSO. It increases network lifetime by 10-20% compared to the benchmark algorithms.
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    Identifying colorectal cancer caused by biallelic MUTYH pathogenic variants using tumor mutational signatures
    (Springer Nature Limited, 6/06/2022) Georgeson P; Harrison TA; Pope BJ; Zaidi SH; Qu C; Steinfelder RS; Lin Y; Joo JE; Mahmood K; Clendenning M; Walker R; Amitay EL; Berndt SI; Brenner H; Campbell PT; Cao Y; Chan AT; Chang-Claude J; Doheny KF; Drew DA; Figueiredo JC; French AJ; Gallinger S; Giannakis M; Giles GG; Gsur A; Gunter MJ; Hoffmeister M; Hsu L; Huang W-Y; Limburg P; Manson JE; Moreno V; Nassir R; Nowak JA; Obón-Santacana M; Ogino S; Phipps AI; Potter JD; Schoen RE; Sun W; Toland AE; Trinh QM; Ugai T; Macrae FA; Rosty C; Hudson TJ; Jenkins MA; Thibodeau SN; Winship IM; Peters U; Buchanan DD
    Carriers of germline biallelic pathogenic variants in the MUTYH gene have a high risk of colorectal cancer. We test 5649 colorectal cancers to evaluate the discriminatory potential of a tumor mutational signature specific to MUTYH for identifying biallelic carriers and classifying variants of uncertain clinical significance (VUS). Using a tumor and matched germline targeted multi-gene panel approach, our classifier identifies all biallelic MUTYH carriers and all known non-carriers in an independent test set of 3019 colorectal cancers (accuracy = 100% (95% confidence interval 99.87-100%)). All monoallelic MUTYH carriers are classified with the non-MUTYH carriers. The classifier provides evidence for a pathogenic classification for two VUS and a benign classification for five VUS. Somatic hotspot mutations KRAS p.G12C and PIK3CA p.Q546K are associated with colorectal cancers from biallelic MUTYH carriers compared with non-carriers (p = 2 × 10-23 and p = 6 × 10-11, respectively). Here, we demonstrate the potential application of mutational signatures to tumor sequencing workflows to improve the identification of biallelic MUTYH carriers.