It was published by researchers at the Universitat Oberta de Catalunya and the Institute of Photonic Sciences, and forms a stunning comparative Raman spectral database. This database is a first step toward making biomolecules easier to find. This exciting new database is now freely available to the scientific community. The BDB holds information on 140 major classes of biomolecular types, such as nucleic acids, proteins, lipids and carbohydrates.
Led by Marcelo Terán, the study is meant to help fill the urgent need of spectral data that’s publicly and freely accessible. This study demonstrates how critical it is for credible information to be circulated throughout our scientific community. The work was published in the journal Chemometrics and Intelligent Laboratory Systems. Researchers have a hard time identifying biomolecules in detail. This challenge comes from their lack of access to detailed spectral data, emphasizing the importance for a strong database, SDB.
To maintain both speed and precision while locating these complex biomolecules, the scientists developed two separate search algorithms. Remarkably, these algorithms demonstrated 100% accuracy in both identifying molecules and classifying them within the top ten results of their respective categories. This kind of precision is key for longitudinal research. Researchers definitely require a more fundamental insight into biomolecule dynamics underlying different biological phenomena, particularly cancer.
Provision of this expert-annotated database enables not only accurate identification of biomolecules of interest, but improves analytical workflow. Since it removes human bias commonly introduced in these types of analyses, it can be a critical tool for researchers. Production of this project was an embodiment of open science. It is the backbone of our most trusted data that powers the key innovations in artificial intelligence applications.
The database is readily accessible on GitHub, allowing scientists worldwide to utilize its resources effectively (https://github.com/mteranm/ramanbiolib). This new open-access initiative is a perfect fit with the increased demand for transparency and reproducibility in collaborative scientific research.