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PanMAN Enables Scalable High-Resolution Pangenome Analysis
The study led by researchers from UC San Diego and UC Santa Cruz introduces PanMAN, a new data structure designed to overcome the limitations...
Solving a Long-Standing Genomics Bottleneck: KAIST Proposes AI-Powered Strategy for Gene Function Prediction
KAIST and UCSD researchers proposed AI-driven strategies for microbial gene function discovery, addressing the long-standing bottleneck where many microbial genes remain uncharacterized despite advances...
AI-Powered Metagenomics: How MetagenBERT Predicts Disease From Raw DNA Sequences
Researchers from Sorbonne University and Dauphine University, France, introduced MetagenBERT, a Transformer-based framework for disease prediction directly from raw metagenomic DNA without relying on...
ToposBio Unveils Topos-1: An All-Atom Foundation Model for Intrinsically Disordered Proteins
Intrinsically disordered proteins (IDPs) are proteins that are central to neurodegenerative diseases and aggressive cancers like prostate cancer, have been considered ‘undruggable’ as structures...
CleaveNet Enables Scalable and Targeted Protease Substrate Design for Diagnostics and Therapeutics
Scientists from MIT and Microsoft Research present CleaveNet, an AI-based pipeline that merges predictive and generative modeling for end-to-end peptide (short protein) design. By...