iCite

iCite provides bibliometric and citation metrics for biomedical research publications using the NIH Open Citation Collection (NIH-OCC) to quantify influence, translational impact, and open citation relationships.

Key Features:

• Public Access Database: iCite leverages the NIH Open Citation Collection (NIH-OCC), aggregating citation data from unrestricted sources such as MedLine, PubMed Central (PMC), and CrossRef.
• Influence Module: Utilizes the Relative Citation Ratio (RCR), a field- and time-adjusted metric benchmarked against NIH publications to assess scientific influence.
• Translation Module: Evaluates translational impact by tracking how findings move from bench to bedside.
• Open Citations Module: Provides access to open citation links to support transparency and reproducibility in bibliometric analyses.
• Data Accessibility: Accepts PubMed queries or uploaded PubMed IDs and provides bulk data via the iCite database snapshot repository for large-scale analyses.
• Machine Learning Integration: Employs a machine learning pipeline that identifies, extracts, resolves, and disambiguates references from full-text articles accessible online.

Scientific Applications:

• Assessment of Research Impact: Quantifies publication influence and reach using citation metrics such as the Relative Citation Ratio (RCR).
• Translational Research Analysis: Tracks translational progress of research findings toward clinical application using the Translation module.
• Enhanced Data Sharing and Reproducibility: Enables use of open citation data from NIH-OCC to support transparent and reproducible bibliometric studies.

Methodology:

The NIH Open Citation Collection (NIH-OCC) is curated from unrestricted sources including MedLine, PubMed Central (PMC), and CrossRef. A machine learning pipeline identifies, extracts, resolves, and disambiguates references from full-text articles accessible online.