AlphaGenome, accessible via API, cracks the “junk DNA” code, outperforms top rivals in key tests, and puts advanced genomics ...

Iya Khalil, PhD, discusses Merck & Co.’s approach to artificial intelligence (AI), and success in applying the technology, ...

Google DeepMind builds on its AlphaFold success with AlphaGenome, a new AI that deciphers the non-coding genome to predict ...

We use genetic algorithms for the optimization of training set composition consisting of tens of thousands of small organic molecules. The resulting machine learning models are considerably more ...

In real world applications it can often be difficult to determine which optimization algorithm to use. This is especially true if the problem has multiple objectives, which is a common occurrence in ...

This study explores the development of two predictive models for the yield sooting index (YSI) of various fuels using the advanced capabilities of machine learning (ML), particularly multilayer ...

OptFrame - C++17/C++20/C++23 Optimization Framework in Single or Multi-Objective. Supports classic metaheuristics and hyperheuristics: Genetic Algorithm, Simulated Annealing, Tabu Search, Iterated ...

2. Genetic Algorithm. The flowchart of the GA used in feedback-based wavefront shaping is schematically shown in Fig. 1, which can be divided into eight different steps.The GA begins by generating an ...

A significant way to reduce the complicated design is by using Automated Machine Learning (AML) that can intelligently optimize the best pipeline suitable for a problem or dataset. This paper ...

Long-read sequencing technologies analyze long, continuous stretches of DNA. These methods have the potential to improve researchers' ability to detect complex genetic alterations in cancer genomes.