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#COVIDisAirborne: AI-Enabled Multiscale Computational Microscopy of Delta SARS-CoV-2 in a Respiratory Aerosol.
Dommer, Abigail; Casalino, Lorenzo; Kearns, Fiona; Rosenfeld, Mia; Wauer, Nicholas; Ahn, Surl-Hee; Russo, John; Oliveira, Sofia; Morris, Clare; Bogetti, Anthony; Trifan, Anda; Brace, Alexander; Sztain, Terra; Clyde, Austin; Ma, Heng; Chennubhotla, Chakra; Lee, Hyungro; Turilli, Matteo; Khalid, Syma; Tamayo-Mendoza, Teresa; Welborn, Matthew; Christensen, Anders; Smith, Daniel G A; Qiao, Zhuoran; Sirumalla, Sai Krishna; O'Connor, Michael; Manby, Frederick; Anandkumar, Anima; Hardy, David; Phillips, James; Stern, Abraham; Romero, Josh; Clark, David; Dorrell, Mitchell; Maiden, Tom; Huang, Lei; McCalpin, John; Woods, Christopher; Gray, Alan; Williams, Matt; Barker, Bryan; Rajapaksha, Harinda; Pitts, Richard; Gibbs, Tom; Stone, John; Zuckerman, Daniel; Mulholland, Adrian; Miller, Thomas; Jha, Shantenu; Ramanathan, Arvind.
Afiliación
  • Dommer A; UC San Diego.
  • Casalino L; UC San Diego.
  • Kearns F; UC San Diego.
  • Rosenfeld M; UC San Diego.
  • Wauer N; UC San Diego.
  • Ahn SH; UC San Diego.
  • Russo J; Oregon Health & Science University.
  • Oliveira S; University of Bristol.
  • Morris C; UC San Diego.
  • Bogetti A; University of Pittsburgh.
  • Trifan A; Argonne National Laboratory.
  • Brace A; University of Illinois at Urbana-Champaign.
  • Sztain T; Argonne National Laboratory.
  • Clyde A; University of Chicago.
  • Ma H; UC San Diego.
  • Chennubhotla C; Freie Universität Berlin.
  • Lee H; Argonne National Laboratory.
  • Turilli M; University of Chicago.
  • Khalid S; Argonne National Laboratory.
  • Tamayo-Mendoza T; University of Pittsburgh.
  • Welborn M; Brookhaven National Lab & Rutgers University.
  • Christensen A; Brookhaven National Lab & Rutgers University.
  • Smith DGA; University of Oxford.
  • Qiao Z; Entos, Inc.
  • Sirumalla SK; Entos, Inc.
  • O'Connor M; Entos, Inc.
  • Manby F; Entos, Inc.
  • Anandkumar A; California Institute of Technology.
  • Hardy D; Entos, Inc.
  • Phillips J; Entos, Inc.
  • Stern A; Entos, Inc.
  • Romero J; California Institute of Technology.
  • Clark D; NVIDIA Corporation.
  • Dorrell M; University of Illinois at Urbana-Champaign.
  • Maiden T; University of Illinois at Urbana-Champaign.
  • Huang L; NVIDIA Corporation.
  • McCalpin J; NVIDIA Corporation.
  • Woods C; NVIDIA Corporation.
  • Gray A; Pittsburgh Supercomputing Center.
  • Williams M; Pittsburgh Supercomputing Center.
  • Barker B; Texas Advanced Computing Center.
  • Rajapaksha H; Texas Advanced Computing Center.
  • Pitts R; University of Bristol.
  • Gibbs T; NVIDIA Corporation.
  • Stone J; University of Bristol.
  • Zuckerman D; Oracle for Research.
  • Mulholland A; Oracle for Research.
  • Miller T; Oracle for Research.
  • Jha S; NVIDIA Corporation.
  • Ramanathan A; University of Illinois at Urbana-Champaign.
bioRxiv ; 2021 Nov 15.
Article en En | MEDLINE | ID: mdl-34816263
ABSTRACT
We seek to completely revise current models of airborne transmission of respiratory viruses by providing never-before-seen atomic-level views of the SARS-CoV-2 virus within a respiratory aerosol. Our work dramatically extends the capabilities of multiscale computational microscopy to address the significant gaps that exist in current experimental methods, which are limited in their ability to interrogate aerosols at the atomic/molecular level and thus ob-scure our understanding of airborne transmission. We demonstrate how our integrated data-driven platform provides a new way of exploring the composition, structure, and dynamics of aerosols and aerosolized viruses, while driving simulation method development along several important axes. We present a series of initial scientific discoveries for the SARS-CoV-2 Delta variant, noting that the full scientific impact of this work has yet to be realized. ACM REFERENCE FORMAT Abigail Dommer 1† , Lorenzo Casalino 1† , Fiona Kearns 1† , Mia Rosenfeld 1 , Nicholas Wauer 1 , Surl-Hee Ahn 1 , John Russo, 2 Sofia Oliveira 3 , Clare Morris 1 , AnthonyBogetti 4 , AndaTrifan 5,6 , Alexander Brace 5,7 , TerraSztain 1,8 , Austin Clyde 5,7 , Heng Ma 5 , Chakra Chennubhotla 4 , Hyungro Lee 9 , Matteo Turilli 9 , Syma Khalid 10 , Teresa Tamayo-Mendoza 11 , Matthew Welborn 11 , Anders Christensen 11 , Daniel G. A. Smith 11 , Zhuoran Qiao 12 , Sai Krishna Sirumalla 11 , Michael O'Connor 11 , Frederick Manby 11 , Anima Anandkumar 12,13 , David Hardy 6 , James Phillips 6 , Abraham Stern 13 , Josh Romero 13 , David Clark 13 , Mitchell Dorrell 14 , Tom Maiden 14 , Lei Huang 15 , John McCalpin 15 , Christo- pherWoods 3 , Alan Gray 13 , MattWilliams 3 , Bryan Barker 16 , HarindaRajapaksha 16 , Richard Pitts 16 , Tom Gibbs 13 , John Stone 6 , Daniel Zuckerman 2 *, Adrian Mulholland 3 *, Thomas MillerIII 11,12 *, ShantenuJha 9 *, Arvind Ramanathan 5 *, Lillian Chong 4 *, Rommie Amaro 1 *. 2021. #COVIDisAirborne AI-Enabled Multiscale Computational Microscopy ofDeltaSARS-CoV-2 in a Respiratory Aerosol. In Supercomputing '21 International Conference for High Perfor-mance Computing, Networking, Storage, and Analysis . ACM, New York, NY, USA, 14 pages. https//doi.org/finalDOI.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: BioRxiv Año: 2021 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: BioRxiv Año: 2021 Tipo del documento: Article
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