Quantitative biologists have designed a new machine learning technique for predicting evolutionary pathways. It could prove a valuable tool for biologists studying rapidly evolving viruses or cancer.

April 15 (UPI) --Scientists have developed a new algorithm that can predict how a protein could evolve to become highly effective or totally unproductive. The machine learning model -- detailed this ...

Cosmologists have spent decades trying to pin down exactly how fast the universe is flying apart and whether that rate is ...

Modern humans descended from not one, but at least two ancestral populations that drifted apart and later reconnected, long before modern humans spread across the globe. Using advanced analysis based ...

At the intersection of neuroscience and artificial intelligence (AI) is an alternative approach to deep learning. Evolutionary algorithms (EA) are a subset of evolutionary computation—algorithms that ...

This course will guide students on their own intellectual journey in evolutionary computation. Early lectures provide a jumping off point — an overview of genetic algorithms, evolutionary strategies, ...

The growth and expansion of metropolitan areas has been evident over the past decade. Buildings are getting taller, and urban areas are getting larger. What if there was a way to predict this growth ...

MPN-BP transformation is driven by sequential mutations disrupting genomic stability, with TP53 mutations being strong predictors of progression. TP53 mutations confer a selective growth advantage, ...

Genetic algorithms (GAs) mimic natural selection to solve complex optimization problems across engineering, AI, and science. By evolving a population of solutions through selection, crossover, and ...

For the last few years or so, the story in the artificial intelligence that was accepted without question was that all of the big names in the field needed more compute, more resources, more energy, ...