Researchers have developed a new machine learning algorithm that excels at interpreting optical spectra, potentially enabling faster and more precise medical diagnoses and sample analysis. Researchers ...

Understanding what complex chemical measurements reveal about materials and reactions can take weeks or months of analysis. But now, an AI-powered platform developed by researchers at the Department ...

A machine learning model has been developed that makes optical spectroscopy data easier and quicker to interpret. Researchers from Rice University (TX, USA) have developed a new machine learning ...

What will you learn on this course? This course is an introduction to mass spectral interpretation, aimed at presenting the fundamental tools and rules when examining high quality full-scan GC-MS data ...

For scientists and engineers, the best way to understand a new or unknown material--whether it's an alloy, a pharmaceutical or a meteorite--is to delve into its atoms. Techniques such as X-ray ...

Explore technical features and comparative strengths of MaxQuant, Proteome Discoverer, FragPipe, and DIA-NN workflows.

Enhancing protein identification accuracy is vital for proteomics; this article explores key technologies and statistical methods involved.

This webinar will discuss advanced techniques in NMR spectroscopy, providing descriptions of one-dimensional and two-dimensional NMR experiment types and data interpretation techniques, with examples ...