Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Godoy-Lorite A"'
Publikováno v:
EPJ Data Science 7:48 (2018)
Advancing our understanding of human behavior hinges on the ability of theories to unveil the mechanisms underlying such behaviors. Measuring the ability of theories and models to predict unobserved behaviors provides a principled method to evaluate
Externí odkaz:
http://arxiv.org/abs/2004.12151
Autor:
Godoy-Lorite, Antonia, Jones, Nick S.
Population behaviours, such as voting and vaccination, depend on social networks. Social networks can differ depending on behaviour type and are typically hidden. However, we do often have large-scale behavioural data, albeit only snapshots taken at
Externí odkaz:
http://arxiv.org/abs/2003.07146
Publikováno v:
"Business and Consumer Analytics: New Ideas", edited by Moscato P., de Vries N, (2019)
With the overwhelming online products available in recent years, there is an increasing need to filter and deliver relevant personalized advice for users. Recommender systems solve this problem by modeling and predicting individual preferences for a
Externí odkaz:
http://arxiv.org/abs/2002.03700
Publikováno v:
Phys. Rev. E 99, 032307 (2019)
Many real-world complex systems are well represented as multilayer networks; predicting interactions in those systems is one of the most pressing problems in predictive network science. To address this challenge, we introduce two stochastic block mod
Externí odkaz:
http://arxiv.org/abs/1803.01616
Publikováno v:
Proc. Natl. Acad. Sci. USA 113 (50) , 14207 -14212 (2016)
With ever-increasing amounts of online information available, modeling and predicting individual preferences-for books or articles, for example-is becoming more and more important. Good predictions enable us to improve advice to users, and obtain a b
Externí odkaz:
http://arxiv.org/abs/1604.01170
Publikováno v:
PLoS ONE 11(1): e0146113 (2016)
In social networks, individuals constantly drop ties and replace them by new ones in a highly unpredictable fashion. This highly dynamical nature of social ties has important implications for processes such as the spread of information or of epidemic
Externí odkaz:
http://arxiv.org/abs/1506.01516
Publikováno v:
EPJ Data Science, Vol 7, Iss 1, Pp 1-13 (2018)
Abstract Advancing our understanding of human behavior hinges on the ability of theories to unveil the mechanisms underlying such behaviors. Measuring the ability of theories and models to predict unobserved behaviors provides a principled method to
Externí odkaz:
https://doaj.org/article/9417accafd614e4fb631ad949753f4c9
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
r-IGTP. Repositorio Institucional de Producción Científica del Instituto de Investigación Germans Trias i Pujol
instname
Nature Communications, 10, pp. 1-17
Nature Communications 10, 2674 (2019). doi:10.1038/s41467-019-09799-2
Dipòsit Digital de la UB
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
CONICET Digital (CONICET)
Consejo Nacional de Investigaciones Científicas y Técnicas
instacron:CONICET
r-FISABIO. Repositorio Institucional de Producción Científica
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
Nature Communications, 10(1):2674. Nature Publishing Group
Recercat. Dipósit de la Recerca de Catalunya
Nature Communications
Nature Communications, 10, 2674
r-IGTP. Repositorio Institucional de Producción Científica del Instituto de Investigación Germans Trias i Pujol
instname
Nature Communications, 10, pp. 1-17
Nature Communications 10, 2674 (2019). doi:10.1038/s41467-019-09799-2
Dipòsit Digital de la UB
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
CONICET Digital (CONICET)
Consejo Nacional de Investigaciones Científicas y Técnicas
instacron:CONICET
r-FISABIO. Repositorio Institucional de Producción Científica
Repositório Científico de Acesso Aberto de Portugal
Repositório Científico de Acesso Aberto de Portugal (RCAAP)
instacron:RCAAP
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
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
Publikováno v:
Journal of Applied Ecology. 58:777-788
Publikováno v:
PLoS ONE, Vol 11, Iss 1, p e0146113 (2016)
In social networks, individuals constantly drop ties and replace them by new ones in a highly unpredictable fashion. This highly dynamical nature of social ties has important implications for processes such as the spread of information or of epidemic
Externí odkaz:
https://doaj.org/article/b95c4cb3fb5a47d29af8a7e3d9c461e4