---
_id: '13267'
abstract:
- lang: eng
text: Three-dimensional (3D) reconstruction of living brain tissue down to an individual
synapse level would create opportunities for decoding the dynamics and structure–function
relationships of the brain’s complex and dense information processing network;
however, this has been hindered by insufficient 3D resolution, inadequate signal-to-noise
ratio and prohibitive light burden in optical imaging, whereas electron microscopy
is inherently static. Here we solved these challenges by developing an integrated
optical/machine-learning technology, LIONESS (live information-optimized nanoscopy
enabling saturated segmentation). This leverages optical modifications to stimulated
emission depletion microscopy in comprehensively, extracellularly labeled tissue
and previous information on sample structure via machine learning to simultaneously
achieve isotropic super-resolution, high signal-to-noise ratio and compatibility
with living tissue. This allows dense deep-learning-based instance segmentation
and 3D reconstruction at a synapse level, incorporating molecular, activity and
morphodynamic information. LIONESS opens up avenues for studying the dynamic functional
(nano-)architecture of living brain tissue.
acknowledged_ssus:
- _id: ScienComp
- _id: Bio
- _id: PreCl
- _id: E-Lib
- _id: LifeSc
- _id: M-Shop
acknowledgement: "We thank J. Vorlaufer, N. Agudelo and A. Wartak for microscope maintenance
and troubleshooting, C. Kreuzinger and A. Freeman for technical assistance, M. Šuplata
for hardware control support and M. Cunha dos Santos for initial exploration of
software. We\r\nthank P. Henderson for advice on deep-learning training and M. Sixt,
S. Boyd and T. Weiss for discussions and critical reading of the manuscript. L.
Lavis (Janelia Research Campus) generously provided the JF585-HaloTag ligand. We
acknowledge expert support by IST\r\nAustria’s scientific computing, imaging and
optics, preclinical, library and laboratory support facilities and by the Miba machine
shop. We gratefully acknowledge funding by the following sources: Austrian Science
Fund (F.W.F.) grant no. I3600-B27 (J.G.D.), grant no. DK W1232\r\n(J.G.D. and J.M.M.)
and grant no. Z 312-B27, Wittgenstein award (P.J.); the Gesellschaft für Forschungsförderung
NÖ grant no. LSC18-022 (J.G.D.); an ISTA Interdisciplinary project grant (J.G.D.
and B.B.); the European Union’s Horizon 2020 research and innovation programme,\r\nMarie-Skłodowska
Curie grant 665385 (J.M.M. and J.L.); the European Union’s Horizon 2020 research
and innovation programme, European Research Council grant no. 715767, MATERIALIZABLE
(B.B.); grant no. 715508, REVERSEAUTISM (G.N.); grant no. 695568, SYNNOVATE (S.G.N.G.);
and grant no. 692692, GIANTSYN (P.J.); the Simons\r\nFoundation Autism Research
Initiative grant no. 529085 (S.G.N.G.); the Wellcome Trust Technology Development
grant no. 202932 (S.G.N.G.); the Marie Skłodowska-Curie Actions Individual Fellowship
no. 101026635 under the EU Horizon 2020 program (J.F.W.);\r\nthe Human Frontier
Science Program postdoctoral fellowship LT000557/2018 (W.J.); and the National Science
Foundation grant no. IIS-1835231 (H.P.) and NCS-FO-2124179 (H.P.)."
article_processing_charge: Yes
article_type: original
author:
- first_name: Philipp
full_name: Velicky, Philipp
id: 39BDC62C-F248-11E8-B48F-1D18A9856A87
last_name: Velicky
orcid: 0000-0002-2340-7431
- first_name: Eder
full_name: Miguel Villalba, Eder
id: 3FB91342-F248-11E8-B48F-1D18A9856A87
last_name: Miguel Villalba
orcid: 0000-0001-5665-0430
- first_name: Julia M
full_name: Michalska, Julia M
id: 443DB6DE-F248-11E8-B48F-1D18A9856A87
last_name: Michalska
orcid: 0000-0003-3862-1235
- first_name: Julia
full_name: Lyudchik, Julia
id: 46E28B80-F248-11E8-B48F-1D18A9856A87
last_name: Lyudchik
- first_name: Donglai
full_name: Wei, Donglai
last_name: Wei
- first_name: Zudi
full_name: Lin, Zudi
last_name: Lin
- first_name: Jake
full_name: Watson, Jake
id: 63836096-4690-11EA-BD4E-32803DDC885E
last_name: Watson
orcid: 0000-0002-8698-3823
- first_name: Jakob
full_name: Troidl, Jakob
last_name: Troidl
- first_name: Johanna
full_name: Beyer, Johanna
last_name: Beyer
- first_name: Yoav
full_name: Ben Simon, Yoav
id: 43DF3136-F248-11E8-B48F-1D18A9856A87
last_name: Ben Simon
- first_name: Christoph M
full_name: Sommer, Christoph M
id: 4DF26D8C-F248-11E8-B48F-1D18A9856A87
last_name: Sommer
orcid: 0000-0003-1216-9105
- first_name: Wiebke
full_name: Jahr, Wiebke
id: 425C1CE8-F248-11E8-B48F-1D18A9856A87
last_name: Jahr
- first_name: Alban
full_name: Cenameri, Alban
id: 9ac8f577-2357-11eb-997a-e566c5550886
last_name: Cenameri
- first_name: Johannes
full_name: Broichhagen, Johannes
last_name: Broichhagen
- first_name: Seth G.N.
full_name: Grant, Seth G.N.
last_name: Grant
- first_name: Peter M
full_name: Jonas, Peter M
id: 353C1B58-F248-11E8-B48F-1D18A9856A87
last_name: Jonas
orcid: 0000-0001-5001-4804
- first_name: Gaia
full_name: Novarino, Gaia
id: 3E57A680-F248-11E8-B48F-1D18A9856A87
last_name: Novarino
orcid: 0000-0002-7673-7178
- first_name: Hanspeter
full_name: Pfister, Hanspeter
last_name: Pfister
- first_name: Bernd
full_name: Bickel, Bernd
id: 49876194-F248-11E8-B48F-1D18A9856A87
last_name: Bickel
orcid: 0000-0001-6511-9385
- first_name: Johann G
full_name: Danzl, Johann G
id: 42EFD3B6-F248-11E8-B48F-1D18A9856A87
last_name: Danzl
orcid: 0000-0001-8559-3973
citation:
ama: Velicky P, Miguel Villalba E, Michalska JM, et al. Dense 4D nanoscale reconstruction
of living brain tissue. Nature Methods. 2023;20:1256-1265. doi:10.1038/s41592-023-01936-6
apa: Velicky, P., Miguel Villalba, E., Michalska, J. M., Lyudchik, J., Wei, D.,
Lin, Z., … Danzl, J. G. (2023). Dense 4D nanoscale reconstruction of living brain
tissue. Nature Methods. Springer Nature. https://doi.org/10.1038/s41592-023-01936-6
chicago: Velicky, Philipp, Eder Miguel Villalba, Julia M Michalska, Julia Lyudchik,
Donglai Wei, Zudi Lin, Jake Watson, et al. “Dense 4D Nanoscale Reconstruction
of Living Brain Tissue.” Nature Methods. Springer Nature, 2023. https://doi.org/10.1038/s41592-023-01936-6.
ieee: P. Velicky et al., “Dense 4D nanoscale reconstruction of living brain
tissue,” Nature Methods, vol. 20. Springer Nature, pp. 1256–1265, 2023.
ista: Velicky P, Miguel Villalba E, Michalska JM, Lyudchik J, Wei D, Lin Z, Watson
J, Troidl J, Beyer J, Ben Simon Y, Sommer CM, Jahr W, Cenameri A, Broichhagen
J, Grant SGN, Jonas PM, Novarino G, Pfister H, Bickel B, Danzl JG. 2023. Dense
4D nanoscale reconstruction of living brain tissue. Nature Methods. 20, 1256–1265.
mla: Velicky, Philipp, et al. “Dense 4D Nanoscale Reconstruction of Living Brain
Tissue.” Nature Methods, vol. 20, Springer Nature, 2023, pp. 1256–65, doi:10.1038/s41592-023-01936-6.
short: P. Velicky, E. Miguel Villalba, J.M. Michalska, J. Lyudchik, D. Wei, Z. Lin,
J. Watson, J. Troidl, J. Beyer, Y. Ben Simon, C.M. Sommer, W. Jahr, A. Cenameri,
J. Broichhagen, S.G.N. Grant, P.M. Jonas, G. Novarino, H. Pfister, B. Bickel,
J.G. Danzl, Nature Methods 20 (2023) 1256–1265.
date_created: 2023-07-23T22:01:13Z
date_published: 2023-08-01T00:00:00Z
date_updated: 2024-01-10T08:37:48Z
day: '01'
department:
- _id: PeJo
- _id: GaNo
- _id: BeBi
- _id: JoDa
- _id: Bio
doi: 10.1038/s41592-023-01936-6
ec_funded: 1
external_id:
isi:
- '001025621500001'
pmid:
- '37429995'
intvolume: ' 20'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1038/s41592-023-01936-6
month: '08'
oa: 1
oa_version: Published Version
page: 1256-1265
pmid: 1
project:
- _id: 265CB4D0-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: I03600
name: Optical control of synaptic function via adhesion molecules
- _id: 2548AE96-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: W1232-B24
name: Molecular Drug Targets
- _id: 25C5A090-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z00312
name: The Wittgenstein Prize
- _id: 23889792-32DE-11EA-91FC-C7463DDC885E
name: High content imaging to decode human immune cell interactions in health and
allergic disease
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: 24F9549A-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '715767'
name: 'MATERIALIZABLE: Intelligent fabrication-oriented Computational Design and
Modeling'
- _id: 25444568-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '715508'
name: Probing the Reversibility of Autism Spectrum Disorders by Employing in vivo
and in vitro Models
- _id: 25B7EB9E-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '692692'
name: Biophysics and circuit function of a giant cortical glumatergic synapse
- _id: fc2be41b-9c52-11eb-aca3-faa90aa144e9
call_identifier: H2020
grant_number: '101026635'
name: Synaptic computations of the hippocampal CA3 circuitry
- _id: 2668BFA0-B435-11E9-9278-68D0E5697425
grant_number: LT00057
name: High-speed 3D-nanoscopy to study the role of adhesion during 3D cell migration
publication: Nature Methods
publication_identifier:
eissn:
- 1548-7105
issn:
- 1548-7091
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/danzllab/LIONESS
record:
- id: '12817'
relation: research_data
status: public
- id: '14770'
relation: shorter_version
status: public
scopus_import: '1'
status: public
title: Dense 4D nanoscale reconstruction of living brain tissue
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 20
year: '2023'
...
---
_id: '14770'
abstract:
- lang: eng
text: We developed LIONESS, a technology that leverages improvements to optical
super-resolution microscopy and prior information on sample structure via machine
learning to overcome the limitations (in 3D-resolution, signal-to-noise ratio
and light exposure) of optical microscopy of living biological specimens. LIONESS
enables dense reconstruction of living brain tissue and morphodynamics visualization
at the nanoscale.
article_processing_charge: No
article_type: letter_note
author:
- first_name: Johann G
full_name: Danzl, Johann G
id: 42EFD3B6-F248-11E8-B48F-1D18A9856A87
last_name: Danzl
orcid: 0000-0001-8559-3973
- first_name: Philipp
full_name: Velicky, Philipp
id: 39BDC62C-F248-11E8-B48F-1D18A9856A87
last_name: Velicky
orcid: 0000-0002-2340-7431
citation:
ama: Danzl JG, Velicky P. LIONESS enables 4D nanoscale reconstruction of living
brain tissue. Nature Methods. 2023;20(8):1141-1142. doi:10.1038/s41592-023-01937-5
apa: Danzl, J. G., & Velicky, P. (2023). LIONESS enables 4D nanoscale reconstruction
of living brain tissue. Nature Methods. Springer Nature. https://doi.org/10.1038/s41592-023-01937-5
chicago: Danzl, Johann G, and Philipp Velicky. “LIONESS Enables 4D Nanoscale Reconstruction
of Living Brain Tissue.” Nature Methods. Springer Nature, 2023. https://doi.org/10.1038/s41592-023-01937-5.
ieee: J. G. Danzl and P. Velicky, “LIONESS enables 4D nanoscale reconstruction of
living brain tissue,” Nature Methods, vol. 20, no. 8. Springer Nature,
pp. 1141–1142, 2023.
ista: Danzl JG, Velicky P. 2023. LIONESS enables 4D nanoscale reconstruction of
living brain tissue. Nature Methods. 20(8), 1141–1142.
mla: Danzl, Johann G., and Philipp Velicky. “LIONESS Enables 4D Nanoscale Reconstruction
of Living Brain Tissue.” Nature Methods, vol. 20, no. 8, Springer Nature,
2023, pp. 1141–42, doi:10.1038/s41592-023-01937-5.
short: J.G. Danzl, P. Velicky, Nature Methods 20 (2023) 1141–1142.
date_created: 2024-01-10T08:07:15Z
date_published: 2023-08-01T00:00:00Z
date_updated: 2024-01-10T08:37:48Z
day: '01'
department:
- _id: JoDa
doi: 10.1038/s41592-023-01937-5
external_id:
isi:
- '001025621500002'
intvolume: ' 20'
isi: 1
issue: '8'
keyword:
- Cell Biology
- Molecular Biology
- Biochemistry
- Biotechnology
language:
- iso: eng
month: '08'
oa_version: None
page: 1141-1142
publication: Nature Methods
publication_identifier:
eissn:
- 1548-7105
issn:
- 1548-7091
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '13267'
relation: extended_version
status: public
scopus_import: '1'
status: public
title: LIONESS enables 4D nanoscale reconstruction of living brain tissue
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 20
year: '2023'
...
---
_id: '11187'
abstract:
- lang: eng
text: During the COVID-19 pandemic, genomics and bioinformatics have emerged as
essential public health tools. The genomic data acquired using these methods have
supported the global health response, facilitated the development of testing methods
and allowed the timely tracking of novel SARS-CoV-2 variants. Yet the virtually
unlimited potential for rapid generation and analysis of genomic data is also
coupled with unique technical, scientific and organizational challenges. Here,
we discuss the application of genomic and computational methods for efficient
data-driven COVID-19 response, the advantages of the democratization of viral
sequencing around the world and the challenges associated with viral genome data
collection and processing.
acknowledgement: 'Our paper is dedicated to all freedom-loving people around the world,
and to the people of Ukraine who fight for our freedom. We thank William M. Switzer
and Ellsworth M. Campbell from the Division of HIV/AIDS Prevention, Centers for
Disease Control and Prevention (CDC), Atlanta, GA, USA, for discussions and suggestions.
We thank Jason Ladner from the Pathogen and Microbiome Institute, Northern Arizona
University, Flagstaff, AZ, for providing suggestions and feedback. S.M. was partially
supported by National Science Foundation grants 2041984. T.L. is supported by the
NSFC Excellent Young Scientists Fund (Hong Kong and Macau; 31922087), Research Grants
Council (RGC) Collaborative Research Fund (C7144-20GF), RGC Research Impact Fund
(R7021-20), Innovation and Technology Commission’s InnoHK funding (D24H) and Health
and Medical Research Fund (COVID190223). P.S. was supported by US National Institutes
of Health (NIH) grant 1R01EB025022 and National Science Foundation (NSF) grant 2047828.
M.A. acknowledges King Abdulaziz City for Science and Technology and the Saudi Human
Genome Project for technical and financial support (https://shgp.kacst.edu.sa) N.W.
was supported by US NIH grants R00 AI139445, DP2 AT011966 and R01 AI167910. A.S.
acknowledge funding from NSF grant no. 2029025. A.Z. has been partially supported
by NIH grants 1R01EB025022-01 and 1R21CA241044-01A1. S. Knyazev has been partly
supported by Molecular Basis of Disease at Georgia State University and NIH awards
R01 HG009120, R01 MH115676, R01 AI153827 and U01 HG011715. A.W. has been supported
by the CAMS Innovation Fund for Medical Sciences (2021-I2M-1-061). R.K. was supported
by NSF project 2038509, RAPID: Improving QIIME 2 and UniFrac for Viruses to Respond
to COVID-19, CDC project 30055281 with Scripps led by Kristian Andersen, Genomic
sequencing of SARS-CoV-2 to investigate local and cross-border emergence and spread.
J.O.W. was supported by NIH–National Institute of Allergy and Infectious Diseases
(NIAID) R01 AI135992 and receives funding from the CDC unrelated to this work. T.I.V.
is supported by the Branco Weiss Fellowship. Y.P. was supported by the Ministry
of Science and Higher Education of the Russian Federation within the framework of
state support for the creation and development of World-Class Research Centers “Digital
biodesign and personalized healthcare” N◦075-15-2020-926. E.B. was supported by
a US National Institute of General Medical Sciences IDeA Alaska INBRE (P20GM103395)
and NIAID CEIRR (75N93019R00028). C.E.M. thanks Testing for America (501c3), OpenCovidScreen
Foundation, Igor Tulchinsky and the WorldQuant Foundation, Bill Ackman and Olivia
Flatto and the Pershing Square Foundation, Ken Griffin and Citadel, the US National
Institutes of Health (R01AI125416, R01AI151059, R21AI129851, U01DA053941), and the
Alfred P. Sloan Foundation (G-2015-13964). C.Y.C. is supported by US CDC Epidemiology
and Laboratory Capacity (ELC) for Infectious Diseases grant 6NU50CK000539 to the
California Department of Public Health, the Innovative Genomics Institute (IGI)
at the University of California, Berkeley, and University of California, San Francisco,
NIH grant R33AI12945 and US CDC contract 75D30121C10991. A.K. was partly supported
by RFBR grant 20-515-80017. P.L. acknowledges support from the European Research
Council (ERC) under the European Union’s Horizon 2020 research and innovation program
(grant agreement no. ~725422 - ReservoirDOCS), the Wellcome Trust through project
206298/Z/17/Z (Artic Network) and NIH grants R01 AI153044 and U19 AI135995. K.C.
acknowledges support from the US NSF award EEID-IOS-2109688. F.K.’s work was supported
by an ERC Consolidator grant to F.K. (771209–CharFL).'
article_processing_charge: No
article_type: letter_note
author:
- first_name: Sergey
full_name: Knyazev, Sergey
last_name: Knyazev
- first_name: Karishma
full_name: Chhugani, Karishma
last_name: Chhugani
- first_name: Varuni
full_name: Sarwal, Varuni
last_name: Sarwal
- first_name: Ram
full_name: Ayyala, Ram
last_name: Ayyala
- first_name: Harman
full_name: Singh, Harman
last_name: Singh
- first_name: Smruthi
full_name: Karthikeyan, Smruthi
last_name: Karthikeyan
- first_name: Dhrithi
full_name: Deshpande, Dhrithi
last_name: Deshpande
- first_name: Pelin Icer
full_name: Baykal, Pelin Icer
last_name: Baykal
- first_name: Zoia
full_name: Comarova, Zoia
last_name: Comarova
- first_name: Angela
full_name: Lu, Angela
last_name: Lu
- first_name: Yuri
full_name: Porozov, Yuri
last_name: Porozov
- first_name: Tetyana I.
full_name: Vasylyeva, Tetyana I.
last_name: Vasylyeva
- first_name: Joel O.
full_name: Wertheim, Joel O.
last_name: Wertheim
- first_name: Braden T.
full_name: Tierney, Braden T.
last_name: Tierney
- first_name: Charles Y.
full_name: Chiu, Charles Y.
last_name: Chiu
- first_name: Ren
full_name: Sun, Ren
last_name: Sun
- first_name: Aiping
full_name: Wu, Aiping
last_name: Wu
- first_name: Malak S.
full_name: Abedalthagafi, Malak S.
last_name: Abedalthagafi
- first_name: Victoria M.
full_name: Pak, Victoria M.
last_name: Pak
- first_name: Shivashankar H.
full_name: Nagaraj, Shivashankar H.
last_name: Nagaraj
- first_name: Adam L.
full_name: Smith, Adam L.
last_name: Smith
- first_name: Pavel
full_name: Skums, Pavel
last_name: Skums
- first_name: Bogdan
full_name: Pasaniuc, Bogdan
last_name: Pasaniuc
- first_name: Andrey
full_name: Komissarov, Andrey
last_name: Komissarov
- first_name: Christopher E.
full_name: Mason, Christopher E.
last_name: Mason
- first_name: Eric
full_name: Bortz, Eric
last_name: Bortz
- first_name: Philippe
full_name: Lemey, Philippe
last_name: Lemey
- first_name: Fyodor
full_name: Kondrashov, Fyodor
id: 44FDEF62-F248-11E8-B48F-1D18A9856A87
last_name: Kondrashov
orcid: 0000-0001-8243-4694
- first_name: Niko
full_name: Beerenwinkel, Niko
last_name: Beerenwinkel
- first_name: Tommy Tsan Yuk
full_name: Lam, Tommy Tsan Yuk
last_name: Lam
- first_name: Nicholas C.
full_name: Wu, Nicholas C.
last_name: Wu
- first_name: Alex
full_name: Zelikovsky, Alex
last_name: Zelikovsky
- first_name: Rob
full_name: Knight, Rob
last_name: Knight
- first_name: Keith A.
full_name: Crandall, Keith A.
last_name: Crandall
- first_name: Serghei
full_name: Mangul, Serghei
last_name: Mangul
citation:
ama: Knyazev S, Chhugani K, Sarwal V, et al. Unlocking capacities of genomics for
the COVID-19 response and future pandemics. Nature Methods. 2022;19(4):374-380.
doi:10.1038/s41592-022-01444-z
apa: Knyazev, S., Chhugani, K., Sarwal, V., Ayyala, R., Singh, H., Karthikeyan,
S., … Mangul, S. (2022). Unlocking capacities of genomics for the COVID-19 response
and future pandemics. Nature Methods. Springer Nature. https://doi.org/10.1038/s41592-022-01444-z
chicago: Knyazev, Sergey, Karishma Chhugani, Varuni Sarwal, Ram Ayyala, Harman Singh,
Smruthi Karthikeyan, Dhrithi Deshpande, et al. “Unlocking Capacities of Genomics
for the COVID-19 Response and Future Pandemics.” Nature Methods. Springer
Nature, 2022. https://doi.org/10.1038/s41592-022-01444-z.
ieee: S. Knyazev et al., “Unlocking capacities of genomics for the COVID-19
response and future pandemics,” Nature Methods, vol. 19, no. 4. Springer
Nature, pp. 374–380, 2022.
ista: Knyazev S, Chhugani K, Sarwal V, Ayyala R, Singh H, Karthikeyan S, Deshpande
D, Baykal PI, Comarova Z, Lu A, Porozov Y, Vasylyeva TI, Wertheim JO, Tierney
BT, Chiu CY, Sun R, Wu A, Abedalthagafi MS, Pak VM, Nagaraj SH, Smith AL, Skums
P, Pasaniuc B, Komissarov A, Mason CE, Bortz E, Lemey P, Kondrashov F, Beerenwinkel
N, Lam TTY, Wu NC, Zelikovsky A, Knight R, Crandall KA, Mangul S. 2022. Unlocking
capacities of genomics for the COVID-19 response and future pandemics. Nature
Methods. 19(4), 374–380.
mla: Knyazev, Sergey, et al. “Unlocking Capacities of Genomics for the COVID-19
Response and Future Pandemics.” Nature Methods, vol. 19, no. 4, Springer
Nature, 2022, pp. 374–80, doi:10.1038/s41592-022-01444-z.
short: S. Knyazev, K. Chhugani, V. Sarwal, R. Ayyala, H. Singh, S. Karthikeyan,
D. Deshpande, P.I. Baykal, Z. Comarova, A. Lu, Y. Porozov, T.I. Vasylyeva, J.O.
Wertheim, B.T. Tierney, C.Y. Chiu, R. Sun, A. Wu, M.S. Abedalthagafi, V.M. Pak,
S.H. Nagaraj, A.L. Smith, P. Skums, B. Pasaniuc, A. Komissarov, C.E. Mason, E.
Bortz, P. Lemey, F. Kondrashov, N. Beerenwinkel, T.T.Y. Lam, N.C. Wu, A. Zelikovsky,
R. Knight, K.A. Crandall, S. Mangul, Nature Methods 19 (2022) 374–380.
date_created: 2022-04-17T22:01:48Z
date_published: 2022-04-08T00:00:00Z
date_updated: 2023-08-03T06:46:09Z
day: '08'
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doi: 10.1038/s41592-022-01444-z
ec_funded: 1
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url: https://doi.org/10.1038/s41592-022-01444-z
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page: 374-380
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call_identifier: H2020
grant_number: '771209'
name: Characterizing the fitness landscape on population and global scales
publication: Nature Methods
publication_identifier:
eissn:
- 1548-7105
issn:
- 1548-7091
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Unlocking capacities of genomics for the COVID-19 response and future pandemics
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 19
year: '2022'
...
---
_id: '9258'
acknowledgement: 'We thank S. van der Walt and K. Marchuk for discussion during development.
This project was funded by Packard Fellowship and Chan Zuckerberg Biohub Investigator
Awards to L.W.; STROBE: A NSF Science and Technology Center; an NSF Graduate Research
Fellowship awarded to H.P.; a Berkeley Institute for Data Science/UCSF Bakar Computational
Health Sciences Institute Fellowship awarded to H.P. with support from the Koret
Foundation, the Gordon and Betty Moore Foundation, and the Alfred P. Sloan Foundation
to the University of California, Berkeley. K.W.E., B.L. and M.T. were funded by
the Chan Zuckerberg Initiative and NIH grant P41GM135019.'
article_processing_charge: No
article_type: letter_note
author:
- first_name: Henry
full_name: Pinkard, Henry
last_name: Pinkard
- first_name: Nico
full_name: Stuurman, Nico
last_name: Stuurman
- first_name: Ivan E.
full_name: Ivanov, Ivan E.
last_name: Ivanov
- first_name: Nicholas M.
full_name: Anthony, Nicholas M.
last_name: Anthony
- first_name: Wei
full_name: Ouyang, Wei
last_name: Ouyang
- first_name: Bin
full_name: Li, Bin
last_name: Li
- first_name: Bin
full_name: Yang, Bin
last_name: Yang
- first_name: Mark A.
full_name: Tsuchida, Mark A.
last_name: Tsuchida
- first_name: Bryant
full_name: Chhun, Bryant
last_name: Chhun
- first_name: Grace
full_name: Zhang, Grace
last_name: Zhang
- first_name: Ryan
full_name: Mei, Ryan
last_name: Mei
- first_name: Michael
full_name: Anderson, Michael
last_name: Anderson
- first_name: Douglas P.
full_name: Shepherd, Douglas P.
last_name: Shepherd
- first_name: Ian
full_name: Hunt-Isaak, Ian
last_name: Hunt-Isaak
- first_name: Raymond L.
full_name: Dunn, Raymond L.
last_name: Dunn
- first_name: Wiebke
full_name: Jahr, Wiebke
id: 425C1CE8-F248-11E8-B48F-1D18A9856A87
last_name: Jahr
- first_name: Saul
full_name: Kato, Saul
last_name: Kato
- first_name: Loïc A.
full_name: Royer, Loïc A.
last_name: Royer
- first_name: Jay R.
full_name: Thiagarajah, Jay R.
last_name: Thiagarajah
- first_name: Kevin W.
full_name: Eliceiri, Kevin W.
last_name: Eliceiri
- first_name: Emma
full_name: Lundberg, Emma
last_name: Lundberg
- first_name: Shalin B.
full_name: Mehta, Shalin B.
last_name: Mehta
- first_name: Laura
full_name: Waller, Laura
last_name: Waller
citation:
ama: 'Pinkard H, Stuurman N, Ivanov IE, et al. Pycro-Manager: Open-source software
for customized and reproducible microscope control. Nature Methods. 2021;18(3):226-228.
doi:10.1038/s41592-021-01087-6'
apa: 'Pinkard, H., Stuurman, N., Ivanov, I. E., Anthony, N. M., Ouyang, W., Li,
B., … Waller, L. (2021). Pycro-Manager: Open-source software for customized and
reproducible microscope control. Nature Methods. Springer Nature. https://doi.org/10.1038/s41592-021-01087-6'
chicago: 'Pinkard, Henry, Nico Stuurman, Ivan E. Ivanov, Nicholas M. Anthony, Wei
Ouyang, Bin Li, Bin Yang, et al. “Pycro-Manager: Open-Source Software for Customized
and Reproducible Microscope Control.” Nature Methods. Springer Nature,
2021. https://doi.org/10.1038/s41592-021-01087-6.'
ieee: 'H. Pinkard et al., “Pycro-Manager: Open-source software for customized
and reproducible microscope control,” Nature Methods, vol. 18, no. 3. Springer
Nature, pp. 226–228, 2021.'
ista: 'Pinkard H, Stuurman N, Ivanov IE, Anthony NM, Ouyang W, Li B, Yang B, Tsuchida
MA, Chhun B, Zhang G, Mei R, Anderson M, Shepherd DP, Hunt-Isaak I, Dunn RL, Jahr
W, Kato S, Royer LA, Thiagarajah JR, Eliceiri KW, Lundberg E, Mehta SB, Waller
L. 2021. Pycro-Manager: Open-source software for customized and reproducible microscope
control. Nature Methods. 18(3), 226–228.'
mla: 'Pinkard, Henry, et al. “Pycro-Manager: Open-Source Software for Customized
and Reproducible Microscope Control.” Nature Methods, vol. 18, no. 3, Springer
Nature, 2021, pp. 226–28, doi:10.1038/s41592-021-01087-6.'
short: H. Pinkard, N. Stuurman, I.E. Ivanov, N.M. Anthony, W. Ouyang, B. Li, B.
Yang, M.A. Tsuchida, B. Chhun, G. Zhang, R. Mei, M. Anderson, D.P. Shepherd, I.
Hunt-Isaak, R.L. Dunn, W. Jahr, S. Kato, L.A. Royer, J.R. Thiagarajah, K.W. Eliceiri,
E. Lundberg, S.B. Mehta, L. Waller, Nature Methods 18 (2021) 226–228.
date_created: 2021-03-21T23:01:20Z
date_published: 2021-03-01T00:00:00Z
date_updated: 2023-08-07T14:19:08Z
day: '01'
department:
- _id: JoDa
doi: 10.1038/s41592-021-01087-6
external_id:
isi:
- '000625600600007'
pmid:
- '33674797'
intvolume: ' 18'
isi: 1
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1038/s41592-021-01087-6
month: '03'
oa: 1
oa_version: Published Version
page: 226-228
pmid: 1
publication: Nature Methods
publication_identifier:
eissn:
- 1548-7105
issn:
- 1548-7091
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Pycro-Manager: Open-source software for customized and reproducible microscope
control'
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 18
year: '2021'
...