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 ...

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 ...

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 ...

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

In this interview, Kevin Broadbelt of Thermo Fisher Scientific discusses the small molecule applications of process Raman spectroscopy. How do cell therapies differ in complexity compared to ...

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

image: Researchers at the Institute of Industrial Science, The University of Tokyo, use artificial intelligence to help interpret data generated by material science spectroscopy experiments, which can ...

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 ...

Manufacturing better batteries, faster electronics, and more effective pharmaceuticals depends on the discovery of new materials and the verification of their quality. Artificial intelligence is ...