Artificial Intelligence Reveals Protein|DNA Interactions

AI uncovers the genome's hidden regulatory code

... reveal regulatory code by predicting transcription factor binding from DNA sequences with unprecedented accuracy. BPNet can uncover the ...

Exploring the Unknown: The Application and Prospects of Artificial ...

By analyzing these vectors, mOWL can predict protein interactions and the ... Revealed by Integrated Transcriptomic Analysis and Machine Learning.

AlphaFold, Artificial Intelligence (AI), and Allostery - ACS Publications

... proteins, and shows ability in protein ... Recent advances in predicting protein-protein interactions with the aid of artificial intelligence ...

Machine learning reveals recipe for building artificial proteins

The University of Chicago has developed an artificial intelligence-led process that uses big data to design new proteins.

Deep-Learning AI Program Accurately Predicts Key Rotavirus ...

This domain exhibits a fold resembling that of versatile carbohydrate-binding proteins called galectins. Surprisingly, the VP8* of RVB (VP8*B) ...

Characterization and Prediction of Macromolecular (Protein, DNA ...

Information on current research, courses, and publications of the Artificial Intelligence Research Laboratory at Penn State University.

Artificial intelligence detects a new class of mutations behind autism

... DNA units would have a substantial effect on those protein interactions. ... In the end, it reveals a prioritized list of DNA sequences ...

Artificial Intelligence for Synthetic Biology

Graph convolutional networks have been used to predict functions of proteins from protein-protein interaction networks. Sequence-based ...

Reflecting on DeepMind's AlphaFold artificial intelligence success ...

A powerful AI system that has been applied to predict structures for almost 99% of human proteins – for fundamental research and drug discovery.

Google DeepMind and Isomorphic Labs unveil AlphaFold 3, an AI ...

... AI model that could predict protein structures from DNA sequence data. ... And in protein to protein interactions, it can predict 62 ...

Using AI to find disease-causing genes - Stanford Medicine Scope

... AI program to analyze a database of protein-protein interactions. ... proteins, that could further reveal how genetic changes cause diseases.

New AI tool predicts protein-protein interaction mutations in ...

Modelling protein-protein interactions paves the way for future drug discovery. Dr. Cheng sought to make an artificial intelligence (AI) tool to ...

Artificial intelligence-based HDX (AI-HDX) prediction reveals ... - OUCI

Baek, Accurate prediction of protein structures and interactions using a ... reveals the role of protein dynamics in electron transfer, Proc. Natl ...

Machine Learning and Artificial Intelligence in Bioinformatics

Long noncoding RNAs (lncRNAs) play important roles in multiple biological processes. Identifying LncRNA–protein interactions (LPIs) is key to understanding ...

Knowledge-guided artificial intelligence technologies for decoding ...

... reveals general sequencebased features ... Predicting the sequence specificities of DNA-and RNA-binding proteins by deep learning.

Researchers turn to deep learning to decode protein structures - PNAS

Artificial intelligence is ushering in a revolution in structural biology. ... Recent predictions of complex protein interactions can shed ...

How AI Cracked the Protein Folding Code and Won a Nobel Prize

This is the inside story of how David Baker, Demis Hassabis and John Jumper won the 2024 Nobel Prize in Chemistry for advances in ...

Artificial intelligence in the prediction of protein–ligand interactions

novel prediction methods. Existing databases for AI-driven. protein–ligand interaction models. The main purpose of ML/AI algorithms is to reveal ...

AI-guided pipeline for protein-protein interaction drug discovery ...

We have developed a machine learning approach that prioritizes interactions by analyzing quantitative data from binary PPI assays and AlphaFold- ...

Significance of Artificial Intelligence in the Study of Virus–Host Cell ...

Within this gene, the highest mutation prevalence is in the S1 subunit, specifically in the receptor binding domain (RBD). A 3D view of the spike protein shows ...