A5080582720- Artificial Immune Systems Applications
- Gene Regulatory Network Analysis
- Modular Robots and Swarm Intelligence
- T-cell and B-cell Immunology
- Evolutionary Algorithms and Applications
- vaccines and immunoinformatics approaches
- Reinforcement Learning in Robotics
- Immune Cell Function and Interaction
- Anomaly Detection Techniques and Applications
- Diabetes and associated disorders
- Distributed Control Multi-Agent Systems
- Machine Learning in Bioinformatics
- Influenza Virus Research Studies
- Advanced Memory and Neural Computing
- Evolution and Genetic Dynamics
- Neural dynamics and brain function
- Robotic Path Planning Algorithms
- Neuroscience and Neural Engineering
- Metaheuristic Optimization Algorithms Research
- Receptor Mechanisms and Signaling
- Robot Manipulation and Learning
- Mathematical and Theoretical Epidemiology and Ecology Models
- Research on Leishmaniasis Studies
- Advanced Software Engineering Methodologies
- DNA and Biological Computing
Aberystwyth University
1999-2024
University of Sunderland
2019-2023
University of York
2011-2020
University of Southampton
2019
Maersk (Denmark)
2019
University of Southern Denmark
2019
Iscte – Instituto Universitário de Lisboa
2019
London School of Hygiene & Tropical Medicine
2019
The University of Tokyo
2019
Jawaharlal Institute of Post Graduate Medical Education and Research
2019
This paper presents the adaptation of an immune network model, originally proposed to perform information compression and data clustering, solve multimodal function optimization problems. The algorithm is described theoretically empirically compared with similar approaches from literature. main features include: automatic determination population size, combination local global search (exploitation plus exploration fitness landscape), defined convergence criterion, capability locating...
We report on a theoretical framework for magnetic hyperthermia where the amount of heat generated by nanoparticles can be understood when both physical and hydrodynamic size distributions are known accurately. The model is validated studying magnetic, colloidal heating properties magnetite/maghemite different sizes dispersed in solvents varying viscosity. show that arising due to susceptibility losses neglected with hysteresis loss being dominant mechanism. it crucial measure specific...
We present an immune algorithm (IA) inspired by the clonal selection principle, which has been designed for protein structure prediction problem (PSP). The proposed IA employs two special mutation operators, hypermutation and hypermacromutation to allow effective searching, aging mechanism is a new operator that devised enforce diversity in population during evolution. When cast as optimization problem, PSP can be seen discovering conformation with minimal energy. was tested on well-known...
Negative selection algorithms for hamming and real-valued shape-spaces are reviewed. Problems identified with the use of these shape-spaces, negative algorithm in general, when applied to anomaly detection. A straightforward self detector classification principle is proposed its performance compared a one-class support vector machine. Earlier work suggests that real-value requires single class learn from. The investigations presented this paper reveal, however, detection, techniques require...
Robots are becoming ubiquitous: from vacuum cleaners to driverless cars, there is a wide variety of applications, many with potential safety hazards. The work presented in this paper proposes set constructs suitable for both modelling robotic applications and supporting verification via model checking theorem proving. Our goal support roboticists writing models applying modern techniques using language familiar them. To that end, we present RoboChart, domain-specific based on UML, but...
Abstract Through the formation of concentration gradients, morphogens drive graded responses to extracellular signals, thereby fine-tuning cell behaviors in complex tissues. Here we show that chemokine CXCL13 forms both soluble and immobilized gradients. Specifically, + follicular reticular cells form a small-world network guidance structures, with computer simulations optimization analysis predicting gradients created by this promote B trafficking. Consistent prediction, imaging binds...
This paper advocates a problem-oriented approach for the design of artificial immune systems (AIS) data mining. By we mean that, in real-world mining applications an AIS should take into account characteristics to be mined together with application domain: components - such as its representation, affinity function, and process tailored application. is contrast majority literature, where very generic algorithm developed there little or no concern tailoring domain. To support this approach,...
Abstract Motivation: G protein-coupled receptors (GPCRs) play an important role in many physiological systems by transducing extracellular signal into intracellular response. Over 50% of all marketed drugs are targeted towards a GPCR. There is considerable interest developing algorithm that could effectively predict the function GPCR from its primary sequence. Such useful not only identifying novel sequences but characterizing interrelationships between known GPCRs. Results: An...
Integrating computer simulation with conventional wet-lab research has proven to have much potential in furthering the understanding of biological systems. Success requires relationship between and real-world system be established: substantial aspects are typically unknown, abstract nature can complicate interpretation silico results terms biology. Here we present spartan (Simulation Parameter Analysis R Toolkit ApplicatioN), a package statistical techniques specifically designed help...