Discovering research articles containing evolutionary timetrees by machine learning
Abstract
Timetrees depict evolutionary relationships between species and the geological times of their divergence. Hundreds of research articles containing timetrees are published in scientific journals every year. The TimeTree (TT) project has been manually locating, curating and synthesizing timetrees from these articles for almost two decades into a TimeTree of Life, delivered through a unique, user-friendly web interface (timetree.org). The manual process of finding articles containing timetrees is becoming increasingly expensive and time-consuming. So, we have explored the effectiveness of text-mining approaches and developed optimizations to find research articles containing timetrees automatically.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Jan 01, 2023
- Source ID
- 10.1093/bioinformatics/btad035
Entities
People
- Adrienne Kasprowicz
- Jennifer Chao
- Jovan Andjelkovic
- Louise A Huuki
- Marija Stanojević
- S Blair Hedges
- Sudhir Kumar
- Zoran Obradović
Organizations
- National Science Foundation
- Temple University
- United States Army Research Laboratory