AIMC Topic: Computer Simulation

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In silico prediction of variant effects: promises and limitations for precision plant breeding.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Sequence-based AI models show great potential for prediction of variant effects at high resolution, but their practical value in plant breeding remains to be confirmed through rigorous validation studies. Plant breeding has traditionally relied on ph...

Reinforced Odor Representations in the Anterior Olfactory Nucleus Can Serve as Memory Traces for Conspecifics.

eNeuro
Recognition of conspecific individuals in mammals is an important skill, thought to be mediated by a distributed array of neural networks, including those processing olfactory cues. Recent data from our groups have shown that social memory can be sup...

Wave Propagation Phenomena in Nonlinear Hierarchical Neural Networks with Predictive Coding Feedback Dynamics.

Bulletin of mathematical biology
We propose a mathematical framework to systematically explore the propagation properties of a class of continuous in time nonlinear neural network models comprising a hierarchy of processing areas, mutually connected according to the principles of pr...

Spatio-Temporal SIR Model of Pandemic Spread During Warfare with Optimal Dual-use Health Care System Administration using Deep Reinforcement Learning.

Disaster medicine and public health preparedness
OBJECTIVES: Large-scale crises, including wars and pandemics, have repeatedly shaped human history, and their simultaneous occurrence presents profound challenges to societies. Understanding the dynamics of epidemic spread during warfare is essential...

Resource trading strategies with risk selection in collaborative training market.

PloS one
The rapid development of edge computing and artificial intelligence has brought growing interest in collaborative training. While prior research has addressed technical aspects of resource allocation, less attention has been paid to the underlying ec...

Ecosystem-based reservoir computing. Hypothesis paper.

Bio Systems
Reservoir computing (RC) has emerged as a powerful computational paradigm, leveraging the intrinsic dynamics of complex systems to process temporal data efficiently. Here we propose to extend RC into ecological domains, where the ecosystems themselve...

An in silico to in vivo approach identifies retinoid-X receptor activating tert-butylphenols used in food contact materials.

Scientific reports
The potential for food contact chemicals to disrupt genetic programs in development and metabolism raises concerns. Nuclear receptors (NRs) control many of these programs, and the retinoid-X receptor (RXR) is a DNA-binding partner for one-third of th...

Computational protein design: Advancing biotechnology through in silico engineering.

Progress in biophysics and molecular biology
Currently, computational protein design (CPD) is a disruptive force in biotechnology, changing the paradigm by which proteins are engineered for many applications. In this article, the evolution of CPD has been tracked from its initial forays in the ...

Machine learning analysis of drug solubility via green approach to enhance drug solubility for poor soluble medications in continuous manufacturing.

Scientific reports
The development of continuous pharmaceutical manufacturing is crucial and can be analyzed via advanced computational models. Machine learning is a strong computational paradigm that can be integrated into a continuous process to enhance the drugs' so...

In Silico Design and Analysis of Cyanobacterial Pseudo Natural Products.

Journal of natural products
Marine cyanobacteria produce natural products (NPs) with potent and selective bioactivity against a broad range of diseases. However, like many NPs, most exhibit poor drug-like physicochemical properties, and the discovery of structurally novel NPs i...