{"id":212682,"date":"2025-04-29T01:31:30","date_gmt":"2025-04-29T06:31:30","guid":{"rendered":"https:\/\/lifeboat.com\/blog\/2025\/04\/light-signature-algorithm-offers-precise-insight-on-viral-proteins-brain-disease-markers-and-semiconductors"},"modified":"2025-04-29T01:31:30","modified_gmt":"2025-04-29T06:31:30","slug":"light-signature-algorithm-offers-precise-insight-on-viral-proteins-brain-disease-markers-and-semiconductors","status":"publish","type":"post","link":"https:\/\/lifeboat.com\/blog\/2025\/04\/light-signature-algorithm-offers-precise-insight-on-viral-proteins-brain-disease-markers-and-semiconductors","title":{"rendered":"Light signature algorithm offers precise insight on viral proteins, brain disease markers and semiconductors"},"content":{"rendered":"

<\/a><\/p>\n

Researchers at Rice University have developed a new machine learning (ML) algorithm that excels at interpreting the \u201clight signatures\u201d (optical spectra) of molecules, materials and disease biomarkers, potentially enabling faster and more precise medical diagnoses and sample analysis.<\/p>\n

\u201cImagine being able to detect early signs of diseases like Alzheimer\u2019s or COVID-19 just by shining a light on a drop of fluid or a tissue sample<\/a>,\u201d said Ziyang Wang, an electrical and computer engineering doctoral student at Rice who is a first author on a study<\/a> published in ACS Nano<\/i>. \u201cOur work makes this possible by teaching computers how to better \u2018read\u2019 the signal of light scattered from tiny molecules.\u201d<\/p>\n

Every material or molecule interacts with light in a unique way, producing a distinct pattern, like a fingerprint. Optical spectroscopy, which entails shining a laser on a material to observe how light interacts with it, is widely used in chemistry, materials science and medicine. However, interpreting spectral data can be difficult and time-consuming, especially when differences between samples are subtle. The new algorithm, called Peak-Sensitive Elastic-net Logistic Regression (PSE-LR), is specially designed to analyze light-based data.<\/p>\n","protected":false},"excerpt":{"rendered":"

Researchers at Rice University have developed a new machine learning (ML) algorithm that excels at interpreting the \u201clight signatures\u201d (optical spectra) of molecules, materials and disease biomarkers, potentially enabling faster and more precise medical diagnoses and sample analysis. \u201cImagine being able to detect early signs of diseases like Alzheimer\u2019s or COVID-19 just by shining a [\u2026]<\/p>\n","protected":false},"author":427,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[11,19,41,6],"tags":[],"class_list":["post-212682","post","type-post","status-publish","format-standard","hentry","category-biotech-medical","category-chemistry","category-information-science","category-robotics-ai"],"_links":{"self":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/212682","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/users\/427"}],"replies":[{"embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/comments?post=212682"}],"version-history":[{"count":0,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/posts\/212682\/revisions"}],"wp:attachment":[{"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/media?parent=212682"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/categories?post=212682"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/lifeboat.com\/blog\/wp-json\/wp\/v2\/tags?post=212682"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}