Inferring time-varying generation time, serial interval, and incubation period distributions for COVID-19

Autor: Dongxuan Chen, Yiu-Chung Lau, Xiao-Ke Xu, Lin Wang, Zhanwei Du, Tim K. Tsang, Peng Wu, Eric H. Y. Lau, Jacco Wallinga, Benjamin J. Cowling, Sheikh Taslim Ali

BackgroundThe generation time distribution, reflecting the time between successive infections in transmission chains, is one of the fundamental epidemiological parameters for describing COVID-19 transmission dynamics. However, because exact infection

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a714b5233020b462aaa041d2c1fe656c
https://www.repository.cam.ac.uk/handle/1810/345255

Normalizing and denoising protein expression data from droplet-based single cell profiling

Autor: Matthew P. Mulé, Andrew J. Martins, John S. Tsang

Funder: NIAID Intramural Grant: 1ZIAAI001152
Multimodal single-cell profiling methods that measure protein expression with oligo-conjugated antibodies hold promise for comprehensive dissection of cellular heterogeneity, yet the resulting protein

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::2b7764a038b9c1dbb76b09bcbeda07a5
https://www.repository.cam.ac.uk/handle/1810/337374

Reconstructing Mayaro virus circulation in French Guiana shows frequent spillovers

Autor: Antoine Enfissi, Matthieu Najm, Sarah Bailly, Nathanaël Hozé, Dominique Rousset, Jessica Vanhomwegen, Jean-Claude Manuguerra, Camille Fritzell, Claude Flamand, Simon Cauchemez, Henrik Salje

Publikováno v: Nature Communications, Vol 11, Iss 1, Pp 1-9 (2020)
Nature Communications
Nature Communications, Nature Publishing Group, 2020, 11 (1), pp.2842. ⟨10.1038/s41467-020-16516-x⟩
Nature Communications, 2020, 11 (1), pp.2842. ⟨10.1038/s41467-020-16516-x⟩

Characterizing the circulation of Mayaro virus (MAYV), an emerging arbovirus threat, is essential for risk assessment but challenging due to cross-reactivity with other alphaviruses such as chikungunya virus (CHIKV). Here, we develop an analytical fr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::79e3306db98cb1b89169377d54ab7c08
http://link.springer.com/article/10.1038/s41467-020-16516-x

Decoding accelerometry for classification and prediction of critically ill patients with severe brain injury

Autor: Bhattacharyay, Shubhayu, Rattray, John, Wang, Matthew, Dziedzic, Peter H, Calvillo, Eusebia, Kim, Han B, Joshi, Eshan, Kudela, Pawel, Etienne-Cummings, Ralph, Stevens, Robert D

Publikováno v: Scientific Reports
Scientific Reports, Vol 11, Iss 1, Pp 1-17 (2021)

Funder: Gates Cambridge Trust; doi: http://dx.doi.org/10.13039/501100005370
Funder: Office of the Provost, Johns Hopkins University; doi: http://dx.doi.org/10.13039/100012800
Our goal is to explore quantitative motor features in critically

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3ecd7dbc086661ab18605553f00b05a
http://europepmc.org/articles/PMC8654973

Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen

Autor: Menden M, Wang D, Mason M, Szalai B, Bulusu K, Guan Y, Yu T, Kang J, Jeon M, Wolfinger R, Nguyen T, Zaslavskiy M, Jang I, Ghazoui Z, Ahsen M, Vogel R, Neto E, Norman T, Tang E, Garnett M, Di Veroli G, Fawell S, Stolovitzky G, Guinney J, Dry J, Saez-Rodriguez J, Abante J, Abecassis B, Aben N, Aghamirzaie D, Aittokallio T, Akhtari F, Al-lazikani B, Alam T, Allam A, Allen C, de Almeida M, Altarawy D, Alves V, Amadoz A, Anchang B, Antolin A, Ash J, Aznar V, Ba-alawi W, Bagheri M, Bajic V, Ball G, Ballester P, Baptista D, Bare C, Bateson M, Bender A, Bertrand D, Wijayawardena B, Boroevich K, Bosdriesz E, Bougouffa S, Bounova G, Brouwer T, Bryant B, Calaza M, Calderone A, Calza S, Capuzzi S, Carbonell-Caballero J, Carlin D, Carter H, Castagnoli L, Celebi R, Cesareni G, Chang H, Chen G, Chen H, Cheng L, Chernomoretz A, Chicco D, Cho K, Cho S, Choi D, Choi J, Choi K, Choi M, De Cock M, Coker E, Cortes-Ciriano I, Cserzo M, Cubuk C, Curtis C, Van Daele D, Dang C, Dijkstra T, Dopazo J, Draghici S, Drosou A, Dumontier M, Ehrhart F, Eid F, ElHefnawi M, Elmarakeby H, van Engelen B, Engin H, de Esch I, Evelo C, Falcao A, Farag S, Fernandez-Lozano C, Fisch K, Flobak A, Fornari C, Foroushani A, Fotso D, Fourches D, Friend S, Frigessi A, Gao F, Gao X, Gerold J, Gestraud P, Ghosh S, Gillberg J, Godoy-Lorite A, Godynyuk L, Godzik A, Goldenberg A, Gomez-Cabrero D, Gonen M, de Graaf C, Gray H, Grechkin M, Guimera R, Guney E, Haibe-Kains B, Han Y, Hase T, He D, He L, Heath L, Hellton K, Helmer-Citterich M, Hidalgo M, Hidru D, Hill S, Hochreiter S, Hong S, Hovig E, Hsueh Y, Hu Z, Huang J, Huang R, Hunyady L, Hwang J, Hwang T, Hwang W, Hwang Y, Isayev O, Walk O, Jack J, Jahandideh S, Ji J, Jo Y, Kamola P, Kanev G, Karacosta L, Karimi M, Kaski S, Kazanov M, Khamis A, Khan S, Kiani N, Kim A, Kim J, Kim K, Kim S, Kim Y, Kirk P, Kitano H, Klambauer G, Knowles D, Ko M, Kohn-Luque A, Kooistra A, Kuenemann M, Kuiper M, Kurz C, Kwon M, van Laarhoven T, Laegreid A, Lederer S, Lee H, Lee J, Lee Y, Leppaho E, Lewis R, Li J, Li L, Liley J, Lim W, Lin C, Liu Y, Lopez Y, Low J, Lysenko A, Machado D, Madhukar N, De Maeyer D, Malpartida A, Mamitsuka H, Marabita F, Marchal K, Marttinen P, Mason D, Mazaheri A, Mehmood A, Mehreen A, Michaut M, Miller R, Mitsopoulos C, Modos D, Van Moerbeke M, Moo K, Motsinger-Reif A, Movva R, Muraru S, Muratov E, Mushthofa M, Nagarajan N, Nakken S, Nath A, Neuvial P, Newton R, Ning Z, De Niz C, Oliva B, Olsen C, Palmeri A, Panesar B, Papadopoulos S, Park J, Park S, Pawitan Y, Peluso D, Pendyala S, Peng J, Perfetto L, Pirro S, Plevritis S, Politi R, Poon H, Porta E, Prellner I, Preuer K, Pujana M, Ramnarine R, Reid J, Reyal F, Richardson S, Ricketts C, Rieswijk L, Rocha M, Rodriguez-Gonzalvez C, Roell K, Rotroff D, de Ruiter J, Rukawa P, Sadacca B, Safikhani Z, Safitri F, Sales-Pardo M, Sauer S, Schlichting M, Seoane J, Serra J, Shang M, Sharma A, Sharma H, Shen Y, Shiga M, Shin M, Shkedy Z, Shopsowitz K, Sinai S, Skola D, Smirnov P, Soerensen I, Soerensen P, Song J, Song S, Soufan O, Spitzmueller A, Steipe B, Suphavilai C, Tamayo S, Tamborero D, Tang J, Tanoli Z, Tarres-Deulofeu M, Tegner J, Thommesen L, Tonekaboni S, Tran H, De Troyer E, Truong A, Tsunoda T, Turu G, Tzeng G, Verbeke L, Videla S, Vis D, Voronkov A, Votis K, Wang A, Wang H, Wang P, Wang S, Wang W, Wang X, Wennerberg K, Wernisch L, Wessels L, van Westen G, Westerman B, White S, Willighagen E, Wurdinger T, Xie L, Xie S, Xu H, Yadav B, Yau C, Yeerna H, Yin J, Yu M, Yun S, Zakharov A, Zamichos A, Zanin M, Zeng L, Zenil H, Zhang F, Zhang P, Zhang W, Zhao H, Zhao L, Zheng W, Zoufir A, Zucknick M, AstraZeneca-Sanger Drug Combinatio

Publikováno v: Nature Communications, Vol 10, Iss 1, Pp 1-17 (2019)
Nature Communications
Nature Communications, 10, 2674
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Nature Communications, 10, pp. 1-17
Nature Communications 10, 2674 (2019). doi:10.1038/s41467-019-09799-2
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Universidad de Barcelona
Nature communications, 10 (1
AstraZeneca-Sanger Drug Combination DREAM Consortium 2019, ' Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen ', Nature Communications, vol. 10, no. 1, 2674 . https://doi.org/10.1038/s41467-019-09799-2
Nature Communications, 10:2674. Nature Publishing Group
NATURE COMMUNICATIONS
Nature Communications, 10, 1-17
Nature communications, vol 10, iss 1
Menden, M P, Wang, D, Mason, M J, Szalai, B, Bulusu, K C, Guan, Y, Yu, T, Kang, J, Jeon, M, Wolfinger, R, Nguyen, T, Zaslavskiy, M, AstraZeneca-Sanger Drug Combination DREAM Consortium, Jang, I S, Ghazoui, Z, Ahsen, M E, Vogel, R, Neto, E C, Norman, T, Tang, E K Y, Garnett, M J, Veroli, G Y D, Fawell, S, Stolovitzky, G, Guinney, J, Dry, J R & Saez-Rodriguez, J 2019, ' Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen ', Nature Communications, vol. 10, no. 1, 2674 . https://doi.org/10.1038/s41467-019-09799-2
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Nature Communications, 10(1):2674. Nature Publishing Group
Recercat. Dipósit de la Recerca de Catalunya

PubMed: 31209238
The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1827ac4799243e82b5025526f2e5a77a
http://link.springer.com/article/10.1038/s41467-019-09799-2