Tiffany J Callahan, Ignacio J Tripodi, Adrianne L Stefanski, Luca Cappelletti, Sanya B Taneja, Jordan M Wyrwa, Elena Casiraghi, Nicolas A Matentzoglu, Justin Reese, Jonathan C Silverstein, Charles Tapley Hoyt, Richard D Boyce, Scott A Malec, Deepak R Unni, Marcin P Joachimiak, Peter N Robinson, Christopher J Mungall, Emanuele Cavalleri, Tommaso Fontana, Giorgio Valentini, Marco Mesiti, Lucas A Gillenwater, Brook Santangelo, Nicole A Vasilevsky, Robert Hoehndorf, Tellen D Bennett, Patrick B Ryan, George Hripcsak, Michael G Kahn, Michael Bada, William A Baumgartner, Lawrence E Hunter
Translational research requires data at multiple scales of biological organization. Advancements in sequencing and multi-omics technologies have increased the availability of these data, but researchers face significant integration challenges. Knowledge graphs (KGs) are used to model complex phenomena, and methods exist to construct them automatically. However, tackling complex biomedical integration problems requires flexibility in the way knowledge is modeled. Moreover, existing KG construction methods provide robust tooling at the cost of fixed or limited choices among knowledge representation models...
April 11, 2024: Scientific Data