2 code implementations • 21 Aug 2021 • Denis Schapiro, Clarence Yapp, Artem Sokolov, Sheila M. Reynolds, Yu-An Chen, Damir Sudar, Yubin Xie, Jeremy L. Muhlich, Raquel Arias-Camison, Sarah Arena, Adam J. Taylor, Milen Nikolov, Madison Tyler, Jia-Ren Lin, Erik A. Burlingame, Human Tumor Atlas Network, Young H. Chang, Samouil L Farhi, Vésteinn Thorsson, Nithya Venkatamohan, Julia L. Drewes, Dana Pe'er, David A. Gutman, Markus D. Herrmann, Nils Gehlenborg, Peter Bankhead, Joseph T. Roland, John M. Herndon, Michael P. Snyder, Michael Angelo, Garry Nolan, Jason R. Swedlow, Nikolaus Schultz, Daniel T. Merrick, Sarah A. Mazzilli, Ethan Cerami, Scott J. Rodig, Sandro Santagata, Peter K. Sorger
The imminent release of tissue atlases combining multi-channel microscopy with single cell sequencing and other omics data from normal and diseased specimens creates an urgent need for data and metadata standards that guide data deposition, curation and release.
2 code implementations • 18 Feb 2021 • Mohamed Amgad, Lamees A. Atteya, Hagar Hussein, Kareem Hosny Mohammed, Ehab Hafiz, Maha A. T. Elsebaie, Ahmed M. Alhusseiny, Mohamed Atef AlMoslemany, Abdelmagid M. Elmatboly, Philip A. Pappalardo, Rokia Adel Sakr, Pooya Mobadersany, Ahmad Rachid, Anas M. Saad, Ahmad M. Alkashash, Inas A. Ruhban, Anas Alrefai, Nada M. Elgazar, Ali Abdulkarim, Abo-Alela Farag, Amira Etman, Ahmed G. Elsaeed, Yahya Alagha, Yomna A. Amer, Ahmed M. Raslan, Menatalla K. Nadim, Mai A. T. Elsebaie, Ahmed Ayad, Liza E. Hanna, Ahmed Gadallah, Mohamed Elkady, Bradley Drumheller, David Jaye, David Manthey, David A. Gutman, Habiba Elfandy, Lee A. D. Cooper
High-resolution mapping of cells and tissue structures provides a foundation for developing interpretable machine-learning models for computational pathology.