no code implementations • 24 Oct 2022 • Sara Mohammad-Taheri, Vartika Tewari, Rohan Kapre, Ehsan Rahiminasab, Karen Sachs, Charles Tapley Hoyt, Jeremy Zucker, Olga Vitek
Therefore, designing an experiment based on a well-chosen subset of network components can increase estimation accuracy, and reduce experimental and computational costs.
no code implementations • 14 Oct 2022 • Hector Garcia Martin, Tijana Radivojevic, Jeremy Zucker, Kristofer Bouchard, Jess Sustarich, Sean Peisert, Dan Arnold, Nathan Hillson, Gyorgy Babnigg, Jose Manuel Marti, Christopher J. Mungall, Gregg T. Beckham, Lucas Waldburger, James Carothers, Shivshankar Sundaram, Deb Agarwal, Blake A. Simmons, Tyler Backman, Deepanwita Banerjee, Deepti Tanjore, Lavanya Ramakrishnan, Anup Singh
Self-driving labs (SDLs) combine fully automated experiments with artificial intelligence (AI) that decides the next set of experiments.
1 code implementation • 12 Feb 2021 • Sara Mohammad-Taheri, Jeremy Zucker, Charles Tapley Hoyt, Karen Sachs, Vartika Tewari, Robert Ness, and Olga Vitek
This has limited the use of LVMs for causal inference in biomolecular pathways.
1 code implementation • 13 Jan 2021 • Jeremy Zucker, Kaushal Paneri, Sara Mohammad-Taheri, Somya Bhargava, Pallavi Kolambkar, Craig Bakker, Jeremy Teuton, Charles Tapley Hoyt, Kristie Oxford, Robert Ness, Olga Vitek
This manuscript proposes a general approach for querying a causal biological knowledge graph, and converting the qualitative result into a quantitative structural causal model that can learn from data to answer the question.