---
_id: '12706'
abstract:
- lang: eng
text: Allometric settings of population dynamics models are appealing due to their
parsimonious nature and broad utility when studying system level effects. Here,
we parameterise the size-scaled Rosenzweig-MacArthur differential equations to
eliminate prey-mass dependency, facilitating an in depth analytic study of the
equations which incorporates scaling parameters’ contributions to coexistence.
We define the functional response term to match empirical findings, and examine
situations where metabolic theory derivations and observation diverge. The dynamical
properties of the Rosenzweig-MacArthur system, encompassing the distribution of
size-abundance equilibria, the scaling of period and amplitude of population cycling,
and relationships between predator and prey abundances, are consistent with empirical
observation. Our parameterisation is an accurate minimal model across 15+ orders
of mass magnitude.
acknowledgement: "This research was supported by an Australian Government Research
Training Program\r\n(RTP) Scholarship to JCM (https://www.dese.gov.au), and LB is
supported by the Centre de\r\nrecherche sur le vieillissement Fellowship Program.
The funders had no role in study design, data collection and analysis, decision
to publish, or preparation of the manuscript."
article_processing_charge: No
article_type: original
author:
- first_name: Jody C.
full_name: Mckerral, Jody C.
last_name: Mckerral
- first_name: Maria
full_name: Kleshnina, Maria
id: 4E21749C-F248-11E8-B48F-1D18A9856A87
last_name: Kleshnina
- first_name: Vladimir
full_name: Ejov, Vladimir
last_name: Ejov
- first_name: Louise
full_name: Bartle, Louise
last_name: Bartle
- first_name: James G.
full_name: Mitchell, James G.
last_name: Mitchell
- first_name: Jerzy A.
full_name: Filar, Jerzy A.
last_name: Filar
citation:
ama: Mckerral JC, Kleshnina M, Ejov V, Bartle L, Mitchell JG, Filar JA. Empirical
parameterisation and dynamical analysis of the allometric Rosenzweig-MacArthur
equations. PLoS One. 2023;18(2):e0279838. doi:10.1371/journal.pone.0279838
apa: Mckerral, J. C., Kleshnina, M., Ejov, V., Bartle, L., Mitchell, J. G., &
Filar, J. A. (2023). Empirical parameterisation and dynamical analysis of the
allometric Rosenzweig-MacArthur equations. PLoS One. Public Library of
Science. https://doi.org/10.1371/journal.pone.0279838
chicago: Mckerral, Jody C., Maria Kleshnina, Vladimir Ejov, Louise Bartle, James
G. Mitchell, and Jerzy A. Filar. “Empirical Parameterisation and Dynamical Analysis
of the Allometric Rosenzweig-MacArthur Equations.” PLoS One. Public Library
of Science, 2023. https://doi.org/10.1371/journal.pone.0279838.
ieee: J. C. Mckerral, M. Kleshnina, V. Ejov, L. Bartle, J. G. Mitchell, and J. A.
Filar, “Empirical parameterisation and dynamical analysis of the allometric Rosenzweig-MacArthur
equations,” PLoS One, vol. 18, no. 2. Public Library of Science, p. e0279838,
2023.
ista: Mckerral JC, Kleshnina M, Ejov V, Bartle L, Mitchell JG, Filar JA. 2023. Empirical
parameterisation and dynamical analysis of the allometric Rosenzweig-MacArthur
equations. PLoS One. 18(2), e0279838.
mla: Mckerral, Jody C., et al. “Empirical Parameterisation and Dynamical Analysis
of the Allometric Rosenzweig-MacArthur Equations.” PLoS One, vol. 18, no.
2, Public Library of Science, 2023, p. e0279838, doi:10.1371/journal.pone.0279838.
short: J.C. Mckerral, M. Kleshnina, V. Ejov, L. Bartle, J.G. Mitchell, J.A. Filar,
PLoS One 18 (2023) e0279838.
date_created: 2023-03-05T23:01:05Z
date_published: 2023-02-27T00:00:00Z
date_updated: 2023-10-17T12:53:30Z
day: '27'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1371/journal.pone.0279838
external_id:
isi:
- '000996122900022'
pmid:
- '36848357'
file:
- access_level: open_access
checksum: 798ed5739a4117b03173e5d56e0534c9
content_type: application/pdf
creator: cchlebak
date_created: 2023-03-07T10:26:45Z
date_updated: 2023-03-07T10:26:45Z
file_id: '12712'
file_name: 2023_PLOSOne_Mckerral.pdf
file_size: 1257003
relation: main_file
success: 1
file_date_updated: 2023-03-07T10:26:45Z
has_accepted_license: '1'
intvolume: ' 18'
isi: 1
issue: '2'
language:
- iso: eng
month: '02'
oa: 1
oa_version: Published Version
page: e0279838
pmid: 1
publication: PLoS One
publication_identifier:
eissn:
- 1932-6203
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Empirical parameterisation and dynamical analysis of the allometric Rosenzweig-MacArthur
equations
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 18
year: '2023'
...
---
_id: '12758'
abstract:
- lang: eng
text: AlphaFold changed the field of structural biology by achieving three-dimensional
(3D) structure prediction from protein sequence at experimental quality. The astounding
success even led to claims that the protein folding problem is “solved”. However,
protein folding problem is more than just structure prediction from sequence.
Presently, it is unknown if the AlphaFold-triggered revolution could help to solve
other problems related to protein folding. Here we assay the ability of AlphaFold
to predict the impact of single mutations on protein stability (ΔΔG) and function.
To study the question we extracted the pLDDT and metrics from AlphaFold
predictions before and after single mutation in a protein and correlated the predicted
change with the experimentally known ΔΔG values. Additionally, we correlated the
same AlphaFold pLDDT metrics with the impact of a single mutation on structure
using a large scale dataset of single mutations in GFP with the experimentally
assayed levels of fluorescence. We found a very weak or no correlation between
AlphaFold output metrics and change of protein stability or fluorescence. Our
results imply that AlphaFold may not be immediately applied to other problems
or applications in protein folding.
acknowledgement: The authors acknowledge the use of Zhores supercomputer [28] for
obtaining the results presented in this paper.The authors thank Zimin Foundation
and Petrovax for support of the presented study at the School of Molecular and Theoretical
Biology 2021.
article_number: e0282689
article_processing_charge: No
article_type: original
author:
- first_name: Marina A.
full_name: Pak, Marina A.
last_name: Pak
- first_name: Karina A.
full_name: Markhieva, Karina A.
last_name: Markhieva
- first_name: Mariia S.
full_name: Novikova, Mariia S.
last_name: Novikova
- first_name: Dmitry S.
full_name: Petrov, Dmitry S.
last_name: Petrov
- first_name: Ilya S.
full_name: Vorobyev, Ilya S.
last_name: Vorobyev
- first_name: Ekaterina
full_name: Maksimova, Ekaterina
id: 2FBE0DE4-F248-11E8-B48F-1D18A9856A87
last_name: Maksimova
- first_name: Fyodor
full_name: Kondrashov, Fyodor
id: 44FDEF62-F248-11E8-B48F-1D18A9856A87
last_name: Kondrashov
orcid: 0000-0001-8243-4694
- first_name: Dmitry N.
full_name: Ivankov, Dmitry N.
last_name: Ivankov
citation:
ama: Pak MA, Markhieva KA, Novikova MS, et al. Using AlphaFold to predict the impact
of single mutations on protein stability and function. PLoS ONE. 2023;18(3).
doi:10.1371/journal.pone.0282689
apa: Pak, M. A., Markhieva, K. A., Novikova, M. S., Petrov, D. S., Vorobyev, I.
S., Maksimova, E., … Ivankov, D. N. (2023). Using AlphaFold to predict the impact
of single mutations on protein stability and function. PLoS ONE. Public
Library of Science. https://doi.org/10.1371/journal.pone.0282689
chicago: Pak, Marina A., Karina A. Markhieva, Mariia S. Novikova, Dmitry S. Petrov,
Ilya S. Vorobyev, Ekaterina Maksimova, Fyodor Kondrashov, and Dmitry N. Ivankov.
“Using AlphaFold to Predict the Impact of Single Mutations on Protein Stability
and Function.” PLoS ONE. Public Library of Science, 2023. https://doi.org/10.1371/journal.pone.0282689.
ieee: M. A. Pak et al., “Using AlphaFold to predict the impact of single
mutations on protein stability and function,” PLoS ONE, vol. 18, no. 3.
Public Library of Science, 2023.
ista: Pak MA, Markhieva KA, Novikova MS, Petrov DS, Vorobyev IS, Maksimova E, Kondrashov
F, Ivankov DN. 2023. Using AlphaFold to predict the impact of single mutations
on protein stability and function. PLoS ONE. 18(3), e0282689.
mla: Pak, Marina A., et al. “Using AlphaFold to Predict the Impact of Single Mutations
on Protein Stability and Function.” PLoS ONE, vol. 18, no. 3, e0282689,
Public Library of Science, 2023, doi:10.1371/journal.pone.0282689.
short: M.A. Pak, K.A. Markhieva, M.S. Novikova, D.S. Petrov, I.S. Vorobyev, E. Maksimova,
F. Kondrashov, D.N. Ivankov, PLoS ONE 18 (2023).
date_created: 2023-03-26T22:01:07Z
date_published: 2023-03-16T00:00:00Z
date_updated: 2023-08-01T13:47:14Z
day: '16'
ddc:
- '570'
department:
- _id: FyKo
- _id: MaRo
doi: 10.1371/journal.pone.0282689
external_id:
isi:
- '000985134400106'
file:
- access_level: open_access
checksum: 0281bdfccf8d76c4e08dd011c603f6b6
content_type: application/pdf
creator: dernst
date_created: 2023-03-27T07:09:08Z
date_updated: 2023-03-27T07:09:08Z
file_id: '12771'
file_name: 2023_PLoSOne_Pak.pdf
file_size: 856625
relation: main_file
success: 1
file_date_updated: 2023-03-27T07:09:08Z
has_accepted_license: '1'
intvolume: ' 18'
isi: 1
issue: '3'
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
publication: PLoS ONE
publication_identifier:
eissn:
- 1932-6203
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Using AlphaFold to predict the impact of single mutations on protein stability
and function
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 18
year: '2023'
...
---
_id: '12759'
abstract:
- lang: eng
text: Stereological methods for estimating the 3D particle size and density from
2D projections are essential to many research fields. These methods are, however,
prone to errors arising from undetected particle profiles due to sectioning and
limited resolution, known as ‘lost caps’. A potential solution developed by Keiding,
Jensen, and Ranek in 1972, which we refer to as the Keiding model, accounts for
lost caps by quantifying the smallest detectable profile in terms of its limiting
‘cap angle’ (ϕ), a size-independent measure of a particle’s distance from the
section surface. However, this simple solution has not been widely adopted nor
tested. Rather, model-independent design-based stereological methods, which do
not explicitly account for lost caps, have come to the fore. Here, we provide
the first experimental validation of the Keiding model by comparing the size and
density of particles estimated from 2D projections with direct measurement from
3D EM reconstructions of the same tissue. We applied the Keiding model to estimate
the size and density of somata, nuclei and vesicles in the cerebellum of mice
and rats, where high packing density can be problematic for design-based methods.
Our analysis reveals a Gaussian distribution for ϕ rather than a single value.
Nevertheless, curve fits of the Keiding model to the 2D diameter distribution
accurately estimate the mean ϕ and 3D diameter distribution. While systematic
testing using simulations revealed an upper limit to determining ϕ, our analysis
shows that estimated ϕ can be used to determine the 3D particle density from the
2D density under a wide range of conditions, and this method is potentially more
accurate than minimum-size-based lost-cap corrections and disector methods. Our
results show the Keiding model provides an efficient means of accurately estimating
the size and density of particles from 2D projections even under conditions of
a high density.
acknowledged_ssus:
- _id: EM-Fac
acknowledgement: "We thank the IST Austria Electron Microscopy Facility for technical
support, and Diccon Coyle, Andrea Lőrincz and Zoltan Nusser for their helpful comments
and discussions.\r\nFunding for JSR and RAS was from the Wellcome Trust (203048;
224499; https://\r\nwellcome.org/). RAS is in receipt of a Wellcome Trust Principal
Research Fellowship (224499).\r\nFunding for CBM and PJ was from Fond zur Förderung
der Wissenschaftlichen Forschung (V\r\n739-B27 Elise-Richter Programme to CBM, Z
312-B27 Wittgenstein Award to PJ; \r\nhttps://www.fwf.ac.at). PJ received funding
from the European Research Council (ERC; https://erc.europa.eu) under the European
Union’s Horizon 2020 research and innovation programme (grant agreement no. 692692).
NH was supported by a European\r\nResearch Council Advanced Grant (ERC-AG787157)."
article_number: e0277148
article_processing_charge: No
article_type: original
author:
- first_name: Jason Seth
full_name: Rothman, Jason Seth
last_name: Rothman
- first_name: Carolina
full_name: Borges Merjane, Carolina
id: 4305C450-F248-11E8-B48F-1D18A9856A87
last_name: Borges Merjane
orcid: 0000-0003-0005-401X
- first_name: Noemi
full_name: Holderith, Noemi
last_name: Holderith
- 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: R.
full_name: Angus Silver, R.
last_name: Angus Silver
citation:
ama: Rothman JS, Borges Merjane C, Holderith N, Jonas PM, Angus Silver R. Validation
of a stereological method for estimating particle size and density from 2D projections
with high accuracy. PLoS ONE. 2023;18(3 March). doi:10.1371/journal.pone.0277148
apa: Rothman, J. S., Borges Merjane, C., Holderith, N., Jonas, P. M., & Angus
Silver, R. (2023). Validation of a stereological method for estimating particle
size and density from 2D projections with high accuracy. PLoS ONE. Public
Library of Science. https://doi.org/10.1371/journal.pone.0277148
chicago: Rothman, Jason Seth, Carolina Borges Merjane, Noemi Holderith, Peter M
Jonas, and R. Angus Silver. “Validation of a Stereological Method for Estimating
Particle Size and Density from 2D Projections with High Accuracy.” PLoS ONE.
Public Library of Science, 2023. https://doi.org/10.1371/journal.pone.0277148.
ieee: J. S. Rothman, C. Borges Merjane, N. Holderith, P. M. Jonas, and R. Angus
Silver, “Validation of a stereological method for estimating particle size and
density from 2D projections with high accuracy,” PLoS ONE, vol. 18, no.
3 March. Public Library of Science, 2023.
ista: Rothman JS, Borges Merjane C, Holderith N, Jonas PM, Angus Silver R. 2023.
Validation of a stereological method for estimating particle size and density
from 2D projections with high accuracy. PLoS ONE. 18(3 March), e0277148.
mla: Rothman, Jason Seth, et al. “Validation of a Stereological Method for Estimating
Particle Size and Density from 2D Projections with High Accuracy.” PLoS ONE,
vol. 18, no. 3 March, e0277148, Public Library of Science, 2023, doi:10.1371/journal.pone.0277148.
short: J.S. Rothman, C. Borges Merjane, N. Holderith, P.M. Jonas, R. Angus Silver,
PLoS ONE 18 (2023).
date_created: 2023-03-26T22:01:07Z
date_published: 2023-03-17T00:00:00Z
date_updated: 2023-08-01T13:46:39Z
day: '17'
ddc:
- '570'
department:
- _id: PeJo
doi: 10.1371/journal.pone.0277148
ec_funded: 1
external_id:
isi:
- '001024737400001'
file:
- access_level: open_access
checksum: 2380331ec27cc87808826fc64419ac1c
content_type: application/pdf
creator: dernst
date_created: 2023-03-27T06:51:09Z
date_updated: 2023-03-27T06:51:09Z
file_id: '12770'
file_name: 2023_PLoSOne_Rothman.pdf
file_size: 7290413
relation: main_file
success: 1
file_date_updated: 2023-03-27T06:51:09Z
has_accepted_license: '1'
intvolume: ' 18'
isi: 1
issue: 3 March
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
project:
- _id: 25B7EB9E-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '692692'
name: Biophysics and circuit function of a giant cortical glumatergic synapse
- _id: 25C5A090-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z00312
name: The Wittgenstein Prize
- _id: 2696E7FE-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: V00739
name: Structural plasticity at mossy fiber-CA3 synapses
publication: PLoS ONE
publication_identifier:
eissn:
- 1932-6203
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Validation of a stereological method for estimating particle size and density
from 2D projections with high accuracy
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 18
year: '2023'
...
---
_id: '11704'
abstract:
- lang: eng
text: In Fall 2020, several European countries reported rapid increases in COVID-19
cases along with growing estimates of the effective reproduction rates. Such an
acceleration in epidemic spread is usually attributed to time-dependent effects,
e.g. human travel, seasonal behavioral changes, mutations of the pathogen etc.
In this case however the acceleration occurred when counter measures such as testing
and contact tracing exceeded their capacity limit. Considering Austria as an example,
here we show that this dynamics can be captured by a time-independent, i.e. autonomous,
compartmental model that incorporates these capacity limits. In this model, the
epidemic acceleration coincides with the exhaustion of mitigation efforts, resulting
in an increasing fraction of undetected cases that drive the effective reproduction
rate progressively higher. We demonstrate that standard models which does not
include this effect necessarily result in a systematic underestimation of the
effective reproduction rate.
article_number: e0269975
article_processing_charge: No
article_type: original
author:
- first_name: Nazmi B
full_name: Budanur, Nazmi B
id: 3EA1010E-F248-11E8-B48F-1D18A9856A87
last_name: Budanur
orcid: 0000-0003-0423-5010
- first_name: Björn
full_name: Hof, Björn
id: 3A374330-F248-11E8-B48F-1D18A9856A87
last_name: Hof
orcid: 0000-0003-2057-2754
citation:
ama: Budanur NB, Hof B. An autonomous compartmental model for accelerating epidemics.
PLoS ONE. 2022;17(7). doi:10.1371/journal.pone.0269975
apa: Budanur, N. B., & Hof, B. (2022). An autonomous compartmental model for
accelerating epidemics. PLoS ONE. Public Library of Science. https://doi.org/10.1371/journal.pone.0269975
chicago: Budanur, Nazmi B, and Björn Hof. “An Autonomous Compartmental Model for
Accelerating Epidemics.” PLoS ONE. Public Library of Science, 2022. https://doi.org/10.1371/journal.pone.0269975.
ieee: N. B. Budanur and B. Hof, “An autonomous compartmental model for accelerating
epidemics,” PLoS ONE, vol. 17, no. 7. Public Library of Science, 2022.
ista: Budanur NB, Hof B. 2022. An autonomous compartmental model for accelerating
epidemics. PLoS ONE. 17(7), e0269975.
mla: Budanur, Nazmi B., and Björn Hof. “An Autonomous Compartmental Model for Accelerating
Epidemics.” PLoS ONE, vol. 17, no. 7, e0269975, Public Library of Science,
2022, doi:10.1371/journal.pone.0269975.
short: N.B. Budanur, B. Hof, PLoS ONE 17 (2022).
date_created: 2022-07-31T22:01:48Z
date_published: 2022-07-18T00:00:00Z
date_updated: 2023-08-03T12:24:22Z
day: '18'
ddc:
- '510'
department:
- _id: BjHo
doi: 10.1371/journal.pone.0269975
external_id:
isi:
- '000911392100055'
file:
- access_level: open_access
checksum: 1ddd9b91e6dec31ab0e7a8433ca2d452
content_type: application/pdf
creator: dernst
date_created: 2022-08-01T08:02:38Z
date_updated: 2022-08-01T08:02:38Z
file_id: '11712'
file_name: 2022_PLoSONE_Budanur.pdf
file_size: 1421256
relation: main_file
success: 1
file_date_updated: 2022-08-01T08:02:38Z
has_accepted_license: '1'
intvolume: ' 17'
isi: 1
issue: '7'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
publication: PLoS ONE
publication_identifier:
eissn:
- 1932-6203
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
related_material:
record:
- id: '11711'
relation: research_data
status: public
scopus_import: '1'
status: public
title: An autonomous compartmental model for accelerating epidemics
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 17
year: '2022'
...
---
_id: '9816'
abstract:
- lang: eng
text: "Aims: Mass antigen testing programs have been challenged because of an alleged
insufficient specificity, leading to a large number of false positives. The objective
of this study is to derive a lower bound of the specificity of the SD Biosensor
Standard Q Ag-Test in large scale practical use.\r\nMethods: Based on county data
from the nationwide tests for SARS-CoV-2 in Slovakia between 31.10.–1.11. 2020
we calculate a lower confidence bound for the specificity. As positive test results
were not systematically verified by PCR tests, we base the lower bound on a worst
case assumption, assuming all positives to be false positives.\r\nResults: 3,625,332
persons from 79 counties were tested. The lowest positivity rate was observed
in the county of Rožňava where 100 out of 34307 (0.29%) tests were positive. This
implies a test specificity of at least 99.6% (97.5% one-sided lower confidence
bound, adjusted for multiplicity).\r\nConclusion: The obtained lower bound suggests
a higher specificity compared to earlier studies in spite of the underlying worst
case assumption and the application in a mass testing setting. The actual specificity
is expected to exceed 99.6% if the prevalence in the respective regions was non-negligible
at the time of testing. To our knowledge, this estimate constitutes the first
bound obtained from large scale practical use of an antigen test."
acknowledgement: We would like to thank Alfred Uhl, Richard Kollár and Katarína Bod’ová
for very helpful comments. We also thank Matej Mišík for discussion and information
regarding the Slovak testing data and Ag-Test used.
article_number: e0255267
article_processing_charge: Yes
article_type: original
author:
- first_name: Michal
full_name: Hledik, Michal
id: 4171253A-F248-11E8-B48F-1D18A9856A87
last_name: Hledik
- first_name: Jitka
full_name: Polechova, Jitka
id: 3BBFB084-F248-11E8-B48F-1D18A9856A87
last_name: Polechova
orcid: 0000-0003-0951-3112
- first_name: Mathias
full_name: Beiglböck, Mathias
last_name: Beiglböck
- first_name: Anna Nele
full_name: Herdina, Anna Nele
last_name: Herdina
- first_name: Robert
full_name: Strassl, Robert
last_name: Strassl
- first_name: Martin
full_name: Posch, Martin
last_name: Posch
citation:
ama: Hledik M, Polechova J, Beiglböck M, Herdina AN, Strassl R, Posch M. Analysis
of the specificity of a COVID-19 antigen test in the Slovak mass testing program.
PLoS ONE. 2021;16(7). doi:10.1371/journal.pone.0255267
apa: Hledik, M., Polechova, J., Beiglböck, M., Herdina, A. N., Strassl, R., &
Posch, M. (2021). Analysis of the specificity of a COVID-19 antigen test in the
Slovak mass testing program. PLoS ONE. Public Library of Science. https://doi.org/10.1371/journal.pone.0255267
chicago: Hledik, Michal, Jitka Polechova, Mathias Beiglböck, Anna Nele Herdina,
Robert Strassl, and Martin Posch. “Analysis of the Specificity of a COVID-19 Antigen
Test in the Slovak Mass Testing Program.” PLoS ONE. Public Library of Science,
2021. https://doi.org/10.1371/journal.pone.0255267.
ieee: M. Hledik, J. Polechova, M. Beiglböck, A. N. Herdina, R. Strassl, and M. Posch,
“Analysis of the specificity of a COVID-19 antigen test in the Slovak mass testing
program,” PLoS ONE, vol. 16, no. 7. Public Library of Science, 2021.
ista: Hledik M, Polechova J, Beiglböck M, Herdina AN, Strassl R, Posch M. 2021.
Analysis of the specificity of a COVID-19 antigen test in the Slovak mass testing
program. PLoS ONE. 16(7), e0255267.
mla: Hledik, Michal, et al. “Analysis of the Specificity of a COVID-19 Antigen Test
in the Slovak Mass Testing Program.” PLoS ONE, vol. 16, no. 7, e0255267,
Public Library of Science, 2021, doi:10.1371/journal.pone.0255267.
short: M. Hledik, J. Polechova, M. Beiglböck, A.N. Herdina, R. Strassl, M. Posch,
PLoS ONE 16 (2021).
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