This paper presents a novel evolutionary algorithm inspired by protein/substrate binding exploited in enzyme genetic programming (EGP) and artificial immune networks. The immune network-inspired evolutionary algorithm has been developed in direct response to an application in clinical neurology, the diagnosis of Parkinson's disease. The inspiration for, and implementation of the algorithm is described and its performance to the application area considered.
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http://dx.doi.org/10.1016/j.biosystems.2008.05.024 | DOI Listing |
Sensors (Basel)
January 2025
College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China.
As the Internet of Things (IoT) expands globally, the challenge of signal transmission in remote regions without traditional communication infrastructure becomes prominent. An effective solution involves integrating aerial, terrestrial, and space components to form a Space-Air-Ground Integrated Network (SAGIN). This paper discusses an uplink signal scenario in which various types of data collection sensors as IoT devices use Unmanned Aerial Vehicles (UAVs) as relays to forward signals to low-Earth-orbit satellites.
View Article and Find Full Text PDFDiagnostics (Basel)
January 2025
Cybersecurity Laboratory, Luleå University of Technology, 97187 Luleå, Sweden.
Alzheimer's disease (AD) leads to severe cognitive impairment and functional decline in patients, and its exact cause remains unknown. Early diagnosis of AD is imperative to enable timely interventions that can slow the progression of the disease. This research tackles the complexity and uncertainty of AD by employing a multimodal approach that integrates medical imaging and demographic data.
View Article and Find Full Text PDFCortex
December 2024
Departments of Neurology and Nuclear Medicine, Hospital Clinico San Carlos, Instituto de Investigación Sanitaria San Carlos (IdISSC), Spain. Electronic address:
Background: This study aimed to evaluate the capacity of neuropsychological assessment to predict the regional brain metabolism in a cohort of patients with amnestic Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) using Machine Learning algorithms.
Methods: We included 360 subjects, consisting of 186 patients with AD, 87 with bvFTD, and 87 cognitively healthy controls. All participants underwent a neuropsychological assessment using the Addenbrooke's Cognitive Examination and the Neuronorma battery, in addition to [F]-fluorodeoxyglucose positron emission tomography (FDG-PET) imaging.
Brief Bioinform
November 2024
Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences, No. 97 Buxin Road, Dapeng New District, Shenzhen 518124, China.
Identifying the regulatory effects of noncoding variants presents a significant challenge. Recently, the accumulation of epigenomic profiling data in wheat has provided an opportunity to model the functional impacts of these variants. In this study, we introduce Language of Genome for Wheat (LOGOWheat), a deep learning-based tool designed to predict the regulatory effects of noncoding variants in wheat.
View Article and Find Full Text PDFNat Cancer
January 2025
Cancer Research UK Lung Cancer Centre of Excellence, University College London Cancer Institute, London, UK.
Human tumors are diverse in their natural history and response to treatment, which in part results from genetic and transcriptomic heterogeneity. In clinical practice, single-site needle biopsies are used to sample this diversity, but cancer biomarkers may be confounded by spatiogenomic heterogeneity within individual tumors. Here we investigate clonally expressed genes as a solution to the sampling bias problem by analyzing multiregion whole-exome and RNA sequencing data for 450 tumor regions from 184 patients with lung adenocarcinoma in the TRACERx study.
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