About this database

This database(ROSes-DB) has been built by Zhanpeng Shi.

The large-scale data established in this study offer invaluable insights into potential functional details based on ROSes interactions among different intestinal microbiota, accessible through our ROS-DB database. At the strain level, ROSes-DB provides user-friendly data searches, aiding the scientific community in exploring and operating the ROSes-DB system. This understanding can unveil how cells protect themselves from oxidative stress injuries, contributing not only to recognizing the body’s self-repair mechanisms but also offering crucial clues for disease prevention, drug development, and advancements in medical treatments.

Citation

Analysis Methods

We developed the ROSes-Finder framework, which consists of two levels: (i) the “component module,” which obtains prediction results based on three different algorithms and different input information: ROSes-CNN (natural language learning), ROSes-ANN (protein sequence information), and ROSesXGBoost (The composition of k-spaced acid pairs, CKSAAP); and (ii) the “integration module,” which uses a voting algorithm to generate predictions from the “component module” and improve overall performance.

Contract me : rec3327559@gmail.com

Address : College of Veterinary Medicine, Jilin University, Changchun, China