Overview of AI Resources for Phenomics
This page provides an overview of essential resources in AI-driven Phenomics, focusing on key areas such as Data Acquisition, Image Processing, Phenomics, and Evolutionary Analysis. Each section offers tools and techniques that help researchers advance their work by leveraging Artificial Intelligence (AI) in the analysis of biological data. From automating data collection to processing complex phenotypic information, this page serves as a gateway to discovering powerful AI methods for understanding the relationship between genotype and phenotype. Please visit regularly for the latest updates.
Citation:
Y. He, J.M. Mulqueeney, E.C. Watt, A. Salili-James, N.S. Barber, M. Camaiti,
E.S.E. Hunt, O. Kippax-Chui, A. Knapp, A. Lanzetti, G. Rangel-de Lázaro,
J.K. McMinn, J. Minus, A.V. Mohan, L.E. Roberts, D. Adhami,
E. Grisan, Q. Gu, V. Herridge, S. Poon, T. West, and A. Goswami. (2024).
Opportunities and challenges in applying AI to evolutionary morphology.
Published in Integrative Organismal Biology, obae036.
Read the article here