IO Informatics (Berkeley, California) recently entered into a strategic partnership with Sage-N Research, Inc. (Milpitas, California).
IO Informatics (Berkeley, California) recently entered into a strategic partnership with Sage-N Research, Inc. (Milpitas, California). This partnership includes the integration of Sage-N's SORCERER Enterprise with the IO Informatics' Sentient software suite. The combination of these technologies creates a Semantic application framework that has been used to quickly develop a specialized, large-scale application that leverages mass-spectrometry based proteomics with content enrichment, interoperability, and flexibility with semantic data integration.
Sage-N’s Ali Pervez, vice president of marketing said in a statement, "One application of this novel approach is to identify peptides from different microorganism with common mechanism of actions, and to categorize them as potential biomarkers, and it also has the capability to detect microbial threats prior to onset of disease symptoms."
The alliance was announced at the Human Proteome Organization (HUPO) 8th Annual Conference: The Future of Proteomics in San Francisco, California. Using customer data and the newly combined technologies, Dr. Erich A. Gombocz, CSO of IO Informatics, highlighted the workflow in a talk entitled, "A Novel Approach to Recognize Peptide Functions in Microorganisms: Establishing Systems Biology-based Relationship Networks to Better Understand Disease Causes and Prevention."
"Future applications of this technology will enable automated screening for biological threats, to characterize origin and type of disease and to develop preventive measures (drugs or vaccines) effective for several classes of microorganism," said Robert Stanley, president of IO Informatics.
Get essential updates on the latest spectroscopy technologies, regulatory standards, and best practices—subscribe today to Spectroscopy.
Rapid Sweetener Detection Achieved Through Raman Spectroscopy and Machine Learning
July 10th 2025Researchers at Heilongjiang University have developed a rapid and accurate method for detecting sweeteners in food using Raman spectroscopy combined with a Random Forest machine learning algorithm, offering a powerful tool for improving food safety.