Multiple sequence alignment (MSA) is a cornerstone of computational biology, facilitating the exploration of functional, structural and evolutionary relationships among biological sequences.

The authors argue that generative AI introduces a new class of alignment risks because interaction itself becomes a mechanism of influence. Humans adapt their behavior in response to AI outputs, ...

Artificial intelligence systems that look nothing alike on the surface are starting to behave as if they share a common ...

New Analysis Platform Explores Why Household Tasks and Physical Automation Require Embodied Intelligence Beyond Traditional Computer Approaches The next wave of AI is physical AI. AI that understands ...

Enterprise sales organizations operate in an environment defined by scale, complexity, and constant pressure to deliver ...

The integration of bioinformatics, machine learning and multi-omics has transformed soil science, providing powerful tools to ...

Artificial intelligence (AI), using a simple blood test combined with standard brain images has, for the first time, been ...

For leaders preparing for 2026, a critical step is to map where processes should remain human or become automated. Audit your ...

Recent developments in machine learning techniques have been supported by the continuous increase in availability of high-performance computational resources and data. While large volumes of data are ...

Learn how root cause analysis and integrated data prevent hydropower bearing failures, reduce costly downtime, and improve ...

Scientists have identified two previously unknown biological subtypes of multiple sclerosis (MS) using artificial ...

Spatiotemporal Evolution Patterns and Intelligent Forecasting of Passenger Flow in Megacity High-Speed Rail Hubs: A Case ...