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 ...

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

University of Virginia School of Engineering and Applied Science professor Nikolaos Sidiropoulos has introduced a breakthrough in graph mining with the development of a new computational algorithm.

Luke Fox: The goal of using the genetic algorithm was to create an optimal massing that prioritized the creation of a central public square and maximized views for the building's occupants.

In the presented paper, an approach is presented, in which we use the genetic algorithm concept in the discrete cosine transform domain. The Genetic algorithm is quite a popular method because it is ...

PrimateAI-3D was trained on the genetic blueprints of 233 primate species to help scientists sift through millions of variants and find ones that can cause harm.

Aiming at the unsmooth path planning problem of four-wheel intelligent vehicle path planning algorithm, this article proposed an improved genetic and ant colony hybrid algorithm, and the physical ...

Solving Knapsack problem with both Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) with results comparison, using MATLAB. I created a graphic interface to make it easy to use and ...

First, the steady-state thermodynamic model of the chiller unit is constructed on EES software, and MATLAB is connected with EES through an interface; then, MATLAB is used to control the input ...