Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Ayelet Blass"'
Autor:
Tamar Tayri-Wilk, Moriya Slavin, Joanna Zamel, Ayelet Blass, Shon Cohen, Alex Motzik, Xue Sun, Deborah E. Shalev, Oren Ram, Nir Kalisman
Publikováno v:
Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
Formaldehyde (FA) is a popular cross-linking reagent, but applying it for cross-linking mass spectrometry (XLMS) has been largely unsuccessful. Here, the authors show that cross-links in structured proteins are the product of two FA molecules and ide
Externí odkaz:
https://doaj.org/article/241e25d8cf7443558ebf3920295f87b0
Autor:
Yair Shachar, Dror Suhami, Ofer Benjaminov, Ziv Neeman, Amiel A. Dror, Nogah Shabshin, Majd Hajouj, Nethanel Eizenbach, Philip Levin, Yael Rapson, Israel Aharony, Matti Mizrachi, Eli Atar, Leonid Charbinsky, Daphna Keidar, Daniel Yaron, Elisha Goldstein, Gil N. Bachar, Liza Lifshitz, Yishai M. Elyada, Yonina C. Eldar, Shlomit Tamir, Ahuva Grubstein, Chedva S. Weiss, Ayelet Blass, Dimitri Lumelsky, Eyal Sela, Naama Bogot
Publikováno v:
European Radiology
Objectives In the midst of the coronavirus disease 2019 (COVID-19) outbreak, chest X-ray (CXR) imaging is playing an important role in diagnosis and monitoring of patients with COVID-19. We propose a deep learning model for detection of COVID-19 from
Autor:
Elena Torri, Andrea Smargiassi, Yishai M. Elyada, Nogah Shabshin, Libertario Demi, Ayelet Blass, Eyal Sela, Chedva S. Weiss, Meirav Galun, Oz Frank, Daphna Keidar, Nir Schipper, Tiziano Perrone, Yair Shachar, Naama R. Bogot, Dror Suhami, Amiel A. Dror, Federico Mento, Mordehay Vaturi, Gino Soldati, Shai Bagon, Yonina C. Eldar, Daniel Yaron, Ahuva Grubstein, Riccardo Inchingolo, Elisha Goldstein
Publikováno v:
ICASSP
Early detection of COVID-19 is key in containing the pandemic. Disease detection and evaluation based on imaging is fast and cheap and therefore plays an important role in COVID-19 handling. COVID-19 is easier to detect in chest CT, however, it is ex
Autor:
Matti Mizrachi, Ayelet Blass, Yishai M. Elyada, Shlomit Tamir, Daphna Keidar, Chedva S. Weiss, Ziv Neeman, Gil N. Bachar, Israel Aharony, Elisha Goldstein, Philip Levin, Daniel Yaron, Naama R. Bogot, Amiel A. Dror, Nogah Shabshin, Dror Suhami, Liza Lifshitz, Dimitri Lumelsky, Ahuva Grubstein, Yael Rapson, Yair Shachar, Eyal Sela, Majd Hajouj, Yonina C. Eldar, Ofer Benjaminov, Nethanel Eizenbach, Leonid Charbinsky
In the midst of the coronavirus disease 2019 (COVID-19) outbreak, chest X-ray (CXR) imaging is playing an important role in the diagnosis and monitoring of patients with COVID-19. Machine learning solutions have been shown to be useful for X-ray anal
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e6b9f3be7f851b6476822efe4878f8ca
http://arxiv.org/abs/2010.01362
http://arxiv.org/abs/2010.01362
Autor:
Alex Motzik, Oren Ram, Moriya Slavin, Joanna Zamel, Tamar Tayri-Wilk, Nir Kalisman, Shon Cohen, Deborah E. Shalev, Xue Sun, Ayelet Blass
Publikováno v:
Nature Communications
Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
Whole-cell cross-linking coupled to mass spectrometry is one of the few tools that can probe protein–protein interactions in intact cells. A very attractive reagent for this purpose is formaldehyde, a small molecule which is known to rapidly penetr