Identifying genetic susceptibility loci associated with human coronary artery disease.

Coronary artery disease (CAD) is a multigenic condition influenced by both nature and nurture (60% to 40%). Prognosis of CAD is based on familial patterns. This study examined and analyzed the susceptibility of CAD to genetic variants in various Pakistani families.

IoT-based framework for optimizing energy efficiency and reliability in acoustic sensor networks using mobile sinks.

In today's world, there is an increasing demand for environmental monitoring, surveillance, and oceanographic research, which poses challenges in improving energy efficiency and data transfer reliability in Acoustic Sensor Networks. Existing methods face hurdles due to limited energy resources and unreliable data transmission. We propose a Reliable and Energy-Efficient Framework with Sink Mobility (REEFSM) to address these issues.

Revolutionizing Diabetes Diagnosis: Machine Learning Techniques Unleashed.

The intricate and multifaceted nature of diabetes disrupts the body's crucial glucose processing mechanism, which serves as a fundamental energy source for the cells. This research aims to predict the occurrence of diabetes in individuals by harnessing the power of machine learning algorithms, utilizing the PIMA diabetes dataset. The selected algorithms employed in this study encompass Decision Tree, K-Nearest Neighbor, Random Forest, Logistic Regression, and Support Vector Machine.

An Adaptive Topology Management Scheme to Maintain Network Connectivity in Wireless Sensor Networks.

The roots of Wireless Sensor Networks (WSNs) are tracked back to US military developments, and, currently, WSNs have paved their way into a vast domain of civil applications, especially environmental, critical infrastructure, habitat monitoring, etc. In the majority of these applications, WSNs have been deployed to monitor critical and inaccessible terrains; however, due to their unique and resource-constrained nature, WSNs face many design and deployment challenges in these difficult-to-access working environments, including connectivity maintenance, topology management, reliability, etc. However, for WSNs, topology management and connectivity still remain a major concern in WSNs that hampers their operations, with a direct impact on the overall application performance of WSNs.

Immunoinformatics approaches to explore B and T cell epitope-based vaccine designing for SARS-CoV-2 Virus.

SARS-CoV-2, a new world coronavirus belonging to class Nidovirales of Coronaviridae family causes COVID-19 infection which is the leading cause of death worldwide. Currently there are no approved drugs and vaccines available for the prevention of COVID-19 infection, although couples of immunizations are being tested in clinical trials. However, the present efforts are focused on computational vaccination technique for evaluating candidates to design multi-epitope-based vaccine against pathogenic mechanism of novel SARS-COV-2.

Novel hybrid genetic algorithm for progressive multiple sequence alignment.

The family of evolutionary or genetic algorithms is used in various fields of bioinformatics. Genetic algorithms (GAs) can be used for simultaneous comparison of a large pool of DNA or protein sequences. This article explains how the GA is used in combination with other methods like the progressive multiple sequence alignment strategy to get an optimal multiple sequence alignment (MSA).