Three applications for gene editing in conservation are restoring lost variation and facilitated adaptation as well as ...

moPepGen leverages a graph-based approach to improve the detection of hidden protein variants in a computationally efficient manner.

Deep learning algorithm used to pinpoint potential disease-causing variants in non-coding regions of the human genome The methods help identify 'footprints' that indicate binding sites and reveal ...

Our automated refactoring solution recommends ways to improve the modularity of existing software, significantly increasing ...

This paper proposes a Random Forest grid fault prediction model based on Genetic Algorithm optimization (GA-RF) to classify the grid fault types, which improves the distribution network fault ...

Genetic algorithms evaluate potential solutions by evolving them over many generations and keeping the ones which work best each time.

However, genetic algorithms can suffer from slow convergence, and might yield suboptimal solutions. In response to these challenges, this work presents a method to fine-tune a genetic algorithm for ...

Scientists in Spain have used genetic algorithms to optimize a feedforward artificial neural network for the prediction of energy generation of PV systems. Genetic algorithms use “parents” and ...

This article presents a novel knowledge-based genetic algorithm (GA) to generate a collision-free path in complex environments. The proposed algorithm infuses specific domain knowledge into robot path ...

This project simulates and optimizes traffic flow at a four-way intersection, employing Petri nets (Java) for simulation and a genetic algorithm (Java) to determine optimal traffic light phase ...

We present an artificial intelligence-guided approach to design durable and chemically recyclable ring-opening polymerization (ROP) class polymers. This approach employs a genetic algorithm (GA) that ...