Isomorphic Lab’s proprietary drug-discovery model is a major advance, but scientists developing open-source tools are left ...

A team of EPFL researchers has developed an AI algorithm that can model complex dynamical processes while taking into account ...

The search space for protein engineering grows exponentially with complexity. A protein of just 100 amino acids has 20^100 ...

The framework predicts how proteins will function with several interacting mutations and finds combinations that work well ...

The workflow encompasses patient datacollection and screening, univariate regression analysis for initial variable selection, systematic comparison of 91 machine learning models,selection and ...

The LinkedIn algorithm can feel like a mysterious gatekeeper, deciding which posts reach only a few connections and which break free into wider feeds. For professionals, creators, and brands, ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

On a scorching July afternoon in Shanghai, dozens of Chinese students hunch over tablet screens, engrossed in English, math and physics lessons. Algorithms track every keystroke, and the seconds spent ...

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...

Abstract: Technical Debt (TD) refers to the long-term costs of suboptimal choices made for short-term gains. Algorithm Debt (AD), a type of TD, refers to the sub-optimal implementation of an algorithm ...