Machine learning method improves accuracy of inverse protein folding for drug design
An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design proteins needed for new treatments.
Bioinformatics is a computational and analytical technique that applies algorithms, statistical methods, and database technologies to the acquisition, storage, processing, and interpretation of biological data, particularly large-scale omics datasets such as genomes, transcriptomes, and proteomes. It encompasses sequence alignment, gene prediction, variant calling, structural modeling, functional annotation, and systems-level network analysis. Bioinformatics pipelines integrate heterogeneous data types, automate quality control, and support reproducible research through workflow management and version-controlled code. As a technique, it enables hypothesis generation, biomarker discovery, and rational design in fields including molecular biology, genomics, pharmacology, and systems biology by transforming raw high-throughput experimental outputs into interpretable, quantitative biological insight.
An AI approach developed by researchers from the University of Sheffield and AstraZeneca, could make it easier to design proteins needed for new treatments.
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Researchers Tomohito Amano and Shinji Tsuneyuki of the University of Tokyo with Tamio Yamazaki of CURIE (JSR-UTokyo Collaboration Hub) have developed a new machine learning model to predict the dielectric function of materials, ...
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In a study published in Nature Nanotechnology, scientists from Delft University of Technology present a new technique to identify proteins. Proteins carry out essential functions in our cells, while playing a crucial role ...
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