Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Ahmet Can Solak"'
Autor:
Lucas von Chamier, Romain F. Laine, Johanna Jukkala, Christoph Spahn, Daniel Krentzel, Elias Nehme, Martina Lerche, Sara Hernández-Pérez, Pieta K. Mattila, Eleni Karinou, Séamus Holden, Ahmet Can Solak, Alexander Krull, Tim-Oliver Buchholz, Martin L. Jones, Loïc A. Royer, Christophe Leterrier, Yoav Shechtman, Florian Jug, Mike Heilemann, Guillaume Jacquemet, Ricardo Henriques
Publikováno v:
Nature Communications, Vol 12, Iss 1, Pp 1-18 (2021)
Deep learning methods show great promise for the analysis of microscopy images but there is currently an accessibility barrier to many users. Here the authors report a convenient entry-level deep learning platform that can be used at no cost: ZeroCos
Externí odkaz:
https://doaj.org/article/71c9afaf6b9849e787693c838589c312
Autor:
Merlin Lange, Alejandro Granados, Shruthi VijayKumar, Jordao Bragantini, Sarah Ancheta, Sreejith Santhosh, Michael Borja, Hirofumi Kobayashi, Erin McGeever, Ahmet Can Solak, Bin Yang, Xiang Zhao, Yang Liu, Angela Detweiler, Sheryl Paul, Honey Mekonen, Tiger Lao, Rachel Banks, Adrian Jacobo, Keir Balla, Kyle Awayan, Samuel D’Souza, Robert Haase, Alexandre Dizeux, Olivier Pourquie, Rafael Gómez-Sjöberg, Greg Huber, Mattia Serra, Norma Neff, Angela Oliveira Pisco, Loïc A. Royer
Elucidating the developmental process of an organism will require the complete cartography of cellular lineages in the spatial, temporal, and molecular domains. We present Zebrahub, a comprehensive dynamic atlas of zebrafish embryonic development tha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::200f80ba956f87d7f3da8101ab4752cb
https://doi.org/10.1101/2023.03.06.531398
https://doi.org/10.1101/2023.03.06.531398
Autor:
Bin Yang, Merlin Lange, Alfred Millett-Sikking, Xiang Zhao, Jordão Bragantini, Shruthi VijayKumar, Mason Kamb, Rafael Gómez-Sjöberg, Ahmet Can Solak, Wanpeng Wang, Hirofumi Kobayashi, Matthew N. McCarroll, Lachlan W. Whitehead, Reto P. Fiolka, Thomas B. Kornberg, Andrew G. York, Loic A. Royer
Publikováno v:
Nature Methods. 19:461-469
The promise of single-objective light-sheet microscopy is to combine the convenience of standard single-objective microscopes with the speed, coverage, resolution and gentleness of light-sheet microscopes. We present DaXi, a single-objective light-sh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ca83110db587a9f3a1d711ec0a58b655
https://doi.org/10.1038/s41592-022-01417-2
https://doi.org/10.1038/s41592-022-01417-2
Autor:
Saba Nafees, Venkata Naga Pranathi Vemuri, Miles Woollacott, Ahmet Can Solak, Phoenix Logan, Aaron McGeever, Olivia Yoo, Sean H. Rice
MotivationAn important goal in sequence analysis is to understand how parts of DNA, RNA, or protein sequences interact with each other and to predict how these interactions result in given phenotypes. Mapping phenotypes onto underlying sequence space
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7da94094f3900c6ea174477a7536a359
https://doi.org/10.1101/2022.09.14.506443
https://doi.org/10.1101/2022.09.14.506443
Autor:
Pieta K. Mattila, Lucas von Chamier, Yoav Shechtman, Elias Nehme, Guillaume Jacquemet, Johanna Jukkala, Alexander Krull, Daniel Krentzel, Loic Royer, Tim-Oliver Buchholz, Mike Heilemann, Christophe Leterrier, Martina Lerche, Romain F. Laine, Ricardo Henriques, Florian Jug, Sara Hernández-Pérez, Martin L. Jones, Eleni Karinou, Ahmet Can Solak, Christoph Spahn, Seamus Holden
Publikováno v:
Nature Communications
Nature Communications, Nature Publishing Group, 2021, 12, ⟨10.1038/s41467-021-22518-0⟩
Nature Communications, Vol 12, Iss 1, Pp 1-18 (2021)
Nature Communications, 2021, 12, ⟨10.1038/s41467-021-22518-0⟩
Nature Communications, Nature Publishing Group, 2021, 12, ⟨10.1038/s41467-021-22518-0⟩
Nature Communications, Vol 12, Iss 1, Pp 1-18 (2021)
Nature Communications, 2021, 12, ⟨10.1038/s41467-021-22518-0⟩
Deep Learning (DL) methods are powerful analytical tools for microscopy and can outperform conventional image processing pipelines. Despite the enthusiasm and innovations fuelled by DL technology, the need to access powerful and compatible resources
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::020f134a7f24e39c4432fd2895e9d76b
https://hal-amu.archives-ouvertes.fr/hal-03233449/document
https://hal-amu.archives-ouvertes.fr/hal-03233449/document
Autor:
Bin, Yang, Merlin, Lange, Alfred, Millett-Sikking, Xiang, Zhao, Jordão, Bragantini, Shruthi, VijayKumar, Mason, Kamb, Rafael, Gómez-Sjöberg, Ahmet Can, Solak, Wanpeng, Wang, Hirofumi, Kobayashi, Matthew N, McCarroll, Lachlan W, Whitehead, Reto P, Fiolka, Thomas B, Kornberg, Andrew G, York, Loic A, Royer
Publikováno v:
Nature methods. 19(4)
The promise of single-objective light-sheet microscopy is to combine the convenience of standard single-objective microscopes with the speed, coverage, resolution and gentleness of light-sheet microscopes. We present DaXi, a single-objective light-sh
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::2d6cd6f8f2d3cc69528597f8361fd5b2
https://pubmed.ncbi.nlm.nih.gov/35314838
https://pubmed.ncbi.nlm.nih.gov/35314838
Autor:
Merlin Lange, Reto Fiolka, Lachlan Whitehead, Bin Yang, Ahmet Can Solak, Andrew York, Matthew N McCarroll, Hirofumi Kobayashi, Loic Royer, Wanpeng Wang, Shruthi Vijay Kumar, Alfred Millett-Sikking, Thomas B. Kornberg
Recent developments in Oblique Plane Microscopy (OPM) have shown that it can achieve high spatio-temporal resolution. Here we describe a single objective light-sheet microscope based on oblique plane illumination that achieves: (i) large field of vie
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3a5ce952b63896a28848476eb795f87
https://doi.org/10.1101/2020.09.22.309229
https://doi.org/10.1101/2020.09.22.309229
Autor:
Elias Nehme, Martina Lerche, Guillaume Jacquemet, Mike Heilemann, Martin L. Jones, Eleni Karinou, Sara Hernández-Pérez, Alexander Krull, Yoav Shechtman, Chamier Lv, Ricardo Henriques, Florian Jug, Tim-Oliver Buchholz, Daniel Krentzel, Loic Royer, Christophe Leterrier, Christoph Spahn, Pieta K. Mattila, Johanna Jukkala, Seamus Holden, Romain F. Laine, Ahmet Can Solak
The resources and expertise needed to use Deep Learning (DL) in bioimaging remain significant barriers for most laboratories. We present https://github.com/HenriquesLab/ZeroCostDL4Mic/wiki, a platform simplifying access to DL by exploiting the free,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::60d0b376059d439c3d86fbf2e943d6e8
https://doi.org/10.1101/2020.03.20.000133
https://doi.org/10.1101/2020.03.20.000133