---
_id: '14411'
abstract:
- lang: eng
text: "Partially specified Boolean networks (PSBNs) represent a promising framework
for the qualitative modelling of biological systems in which the logic of interactions
is not completely known. Phenotype control aims to stabilise the network in states
exhibiting specific traits.\r\nIn this paper, we define the phenotype control
problem in the context of asynchronous PSBNs and propose a novel semi-symbolic
algorithm for solving this problem with permanent variable perturbations."
acknowledgement: This work was supported by the Czech Foundation grant No. GA22-10845S,
Grant Agency of Masaryk University grant No. MUNI/G/1771/2020, and the European
Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie
Grant Agreement No. 101034413.
alternative_title:
- LNBI
article_processing_charge: No
author:
- first_name: Nikola
full_name: Beneš, Nikola
last_name: Beneš
- first_name: Luboš
full_name: Brim, Luboš
last_name: Brim
- first_name: Samuel
full_name: Pastva, Samuel
id: 07c5ea74-f61c-11ec-a664-aa7c5d957b2b
last_name: Pastva
orcid: 0000-0003-1993-0331
- first_name: David
full_name: Šafránek, David
last_name: Šafránek
- first_name: Eva
full_name: Šmijáková, Eva
last_name: Šmijáková
citation:
ama: 'Beneš N, Brim L, Pastva S, Šafránek D, Šmijáková E. Phenotype control of partially
specified boolean networks. In: 21st International Conference on Computational
Methods in Systems Biology. Vol 14137. Springer Nature; 2023:18-35. doi:10.1007/978-3-031-42697-1_2'
apa: 'Beneš, N., Brim, L., Pastva, S., Šafránek, D., & Šmijáková, E. (2023).
Phenotype control of partially specified boolean networks. In 21st International
Conference on Computational Methods in Systems Biology (Vol. 14137, pp. 18–35).
Luxembourg City, Luxembourg: Springer Nature. https://doi.org/10.1007/978-3-031-42697-1_2'
chicago: Beneš, Nikola, Luboš Brim, Samuel Pastva, David Šafránek, and Eva Šmijáková.
“Phenotype Control of Partially Specified Boolean Networks.” In 21st International
Conference on Computational Methods in Systems Biology, 14137:18–35. Springer
Nature, 2023. https://doi.org/10.1007/978-3-031-42697-1_2.
ieee: N. Beneš, L. Brim, S. Pastva, D. Šafránek, and E. Šmijáková, “Phenotype control
of partially specified boolean networks,” in 21st International Conference
on Computational Methods in Systems Biology, Luxembourg City, Luxembourg,
2023, vol. 14137, pp. 18–35.
ista: 'Beneš N, Brim L, Pastva S, Šafránek D, Šmijáková E. 2023. Phenotype control
of partially specified boolean networks. 21st International Conference on Computational
Methods in Systems Biology. CMSB: Computational Methods in Systems Biology, LNBI,
vol. 14137, 18–35.'
mla: Beneš, Nikola, et al. “Phenotype Control of Partially Specified Boolean Networks.”
21st International Conference on Computational Methods in Systems Biology,
vol. 14137, Springer Nature, 2023, pp. 18–35, doi:10.1007/978-3-031-42697-1_2.
short: N. Beneš, L. Brim, S. Pastva, D. Šafránek, E. Šmijáková, in:, 21st International
Conference on Computational Methods in Systems Biology, Springer Nature, 2023,
pp. 18–35.
conference:
end_date: 2023-09-15
location: Luxembourg City, Luxembourg
name: 'CMSB: Computational Methods in Systems Biology'
start_date: 2023-09-13
date_created: 2023-10-08T22:01:18Z
date_published: 2023-09-09T00:00:00Z
date_updated: 2024-02-20T09:02:04Z
day: '09'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.1007/978-3-031-42697-1_2
ec_funded: 1
file:
- access_level: open_access
checksum: 6f71bdaedb770b52380222fd9f4d7937
content_type: application/pdf
creator: spastva
date_created: 2024-02-16T08:26:32Z
date_updated: 2024-02-16T08:26:32Z
file_id: '14997'
file_name: cmsb2023.pdf
file_size: 691582
relation: main_file
success: 1
file_date_updated: 2024-02-16T08:26:32Z
has_accepted_license: '1'
intvolume: ' 14137'
language:
- iso: eng
license: https://creativecommons.org/licenses/by/4.0/
month: '09'
oa: 1
oa_version: Submitted Version
page: 18-35
project:
- _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c
call_identifier: H2020
grant_number: '101034413'
name: 'IST-BRIDGE: International postdoctoral program'
publication: 21st International Conference on Computational Methods in Systems Biology
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031426964'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Phenotype control of partially specified boolean networks
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: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 14137
year: '2023'
...
---
_id: '14718'
abstract:
- lang: eng
text: 'Binary decision diagrams (BDDs) are one of the fundamental data structures
in formal methods and computer science in general. However, the performance of
BDD-based algorithms greatly depends on memory latency due to the reliance on
large hash tables and thus, by extension, on the speed of random memory access.
This hinders the full utilisation of resources available on modern CPUs, since
the absolute memory latency has not improved significantly for at least a decade.
In this paper, we explore several implementation techniques that improve the performance
of BDD manipulation either through enhanced memory locality or by partially eliminating
random memory access. On a benchmark suite of 600+ BDDs derived from real-world
applications, we demonstrate runtime that is comparable or better than parallelising
the same operations on eight CPU cores. '
acknowledgement: "This work was supported by the European Union’s Horizon 2020 research
and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 101034413
and the\r\n“VAMOS” grant ERC-2020-AdG 101020093."
article_processing_charge: No
author:
- first_name: Samuel
full_name: Pastva, Samuel
id: 07c5ea74-f61c-11ec-a664-aa7c5d957b2b
last_name: Pastva
orcid: 0000-0003-1993-0331
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: 'Pastva S, Henzinger TA. Binary decision diagrams on modern hardware. In: Proceedings
of the 23rd Conference on Formal Methods in Computer-Aided Design. TU Vienna
Academic Press; 2023:122-131. doi:10.34727/2023/isbn.978-3-85448-060-0_20'
apa: 'Pastva, S., & Henzinger, T. A. (2023). Binary decision diagrams on modern
hardware. In Proceedings of the 23rd Conference on Formal Methods in Computer-Aided
Design (pp. 122–131). Ames, IA, United States: TU Vienna Academic Press. https://doi.org/10.34727/2023/isbn.978-3-85448-060-0_20'
chicago: Pastva, Samuel, and Thomas A Henzinger. “Binary Decision Diagrams on Modern
Hardware.” In Proceedings of the 23rd Conference on Formal Methods in Computer-Aided
Design, 122–31. TU Vienna Academic Press, 2023. https://doi.org/10.34727/2023/isbn.978-3-85448-060-0_20.
ieee: S. Pastva and T. A. Henzinger, “Binary decision diagrams on modern hardware,”
in Proceedings of the 23rd Conference on Formal Methods in Computer-Aided Design,
Ames, IA, United States, 2023, pp. 122–131.
ista: 'Pastva S, Henzinger TA. 2023. Binary decision diagrams on modern hardware.
Proceedings of the 23rd Conference on Formal Methods in Computer-Aided Design.
FMCAD: Conference on Formal Methods in Computer-aided design, 122–131.'
mla: Pastva, Samuel, and Thomas A. Henzinger. “Binary Decision Diagrams on Modern
Hardware.” Proceedings of the 23rd Conference on Formal Methods in Computer-Aided
Design, TU Vienna Academic Press, 2023, pp. 122–31, doi:10.34727/2023/isbn.978-3-85448-060-0_20.
short: S. Pastva, T.A. Henzinger, in:, Proceedings of the 23rd Conference on Formal
Methods in Computer-Aided Design, TU Vienna Academic Press, 2023, pp. 122–131.
conference:
end_date: 2023-10-27
location: Ames, IA, United States
name: 'FMCAD: Conference on Formal Methods in Computer-aided design'
start_date: 2023-10-25
date_created: 2023-12-31T23:01:03Z
date_published: 2023-10-01T00:00:00Z
date_updated: 2024-01-02T08:16:28Z
day: '01'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.34727/2023/isbn.978-3-85448-060-0_20
ec_funded: 1
file:
- access_level: open_access
checksum: 818d6e13dd508f3a04f0941081022e5d
content_type: application/pdf
creator: dernst
date_created: 2024-01-02T08:14:23Z
date_updated: 2024-01-02T08:14:23Z
file_id: '14721'
file_name: 2023_FMCAD_Pastva.pdf
file_size: 524321
relation: main_file
success: 1
file_date_updated: 2024-01-02T08:14:23Z
has_accepted_license: '1'
language:
- iso: eng
month: '10'
oa: 1
oa_version: Published Version
page: 122-131
project:
- _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c
call_identifier: H2020
grant_number: '101034413'
name: 'IST-BRIDGE: International postdoctoral program'
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
publication: Proceedings of the 23rd Conference on Formal Methods in Computer-Aided
Design
publication_identifier:
isbn:
- '9783854480600'
publication_status: published
publisher: TU Vienna Academic Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Binary decision diagrams on modern hardware
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: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '13263'
abstract:
- lang: eng
text: "Motivation: Boolean networks are simple but efficient mathematical formalism
for modelling complex biological systems. However, having only two levels of activation
is sometimes not enough to fully capture the dynamics of real-world biological
systems. Hence, the need for multi-valued networks (MVNs), a generalization of
Boolean networks. Despite the importance of MVNs for modelling biological systems,
only limited progress has been made on developing theories, analysis methods,
and tools that can support them. In particular, the recent use of trap spaces
in Boolean networks made a great impact on the field of systems biology, but there
has been no similar concept defined and studied for MVNs to date.\r\n\r\nResults:
In this work, we generalize the concept of trap spaces in Boolean networks to
that in MVNs. We then develop the theory and the analysis methods for trap spaces
in MVNs. In particular, we implement all proposed methods in a Python package
called trapmvn. Not only showing the applicability of our approach via a realistic
case study, we also evaluate the time efficiency of the method on a large collection
of real-world models. The experimental results confirm the time efficiency, which
we believe enables more accurate analysis on larger and more complex multi-valued
models."
acknowledgement: This work was supported by L’Institut Carnot STAR, Marseille, France,
and by the European Union’s Horizon 2020 research and innovation programme under
the Marie Skłodowska-Curie Grant Agreement No. [101034413].
article_processing_charge: Yes
article_type: original
author:
- first_name: Van Giang
full_name: Trinh, Van Giang
last_name: Trinh
- first_name: Belaid
full_name: Benhamou, Belaid
last_name: Benhamou
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Samuel
full_name: Pastva, Samuel
id: 07c5ea74-f61c-11ec-a664-aa7c5d957b2b
last_name: Pastva
orcid: 0000-0003-1993-0331
citation:
ama: 'Trinh VG, Benhamou B, Henzinger TA, Pastva S. Trap spaces of multi-valued
networks: Definition, computation, and applications. Bioinformatics. 2023;39(Supplement_1):i513-i522.
doi:10.1093/bioinformatics/btad262'
apa: 'Trinh, V. G., Benhamou, B., Henzinger, T. A., & Pastva, S. (2023). Trap
spaces of multi-valued networks: Definition, computation, and applications. Bioinformatics.
Oxford Academic. https://doi.org/10.1093/bioinformatics/btad262'
chicago: 'Trinh, Van Giang, Belaid Benhamou, Thomas A Henzinger, and Samuel Pastva.
“Trap Spaces of Multi-Valued Networks: Definition, Computation, and Applications.”
Bioinformatics. Oxford Academic, 2023. https://doi.org/10.1093/bioinformatics/btad262.'
ieee: 'V. G. Trinh, B. Benhamou, T. A. Henzinger, and S. Pastva, “Trap spaces of
multi-valued networks: Definition, computation, and applications,” Bioinformatics,
vol. 39, no. Supplement_1. Oxford Academic, pp. i513–i522, 2023.'
ista: 'Trinh VG, Benhamou B, Henzinger TA, Pastva S. 2023. Trap spaces of multi-valued
networks: Definition, computation, and applications. Bioinformatics. 39(Supplement_1),
i513–i522.'
mla: 'Trinh, Van Giang, et al. “Trap Spaces of Multi-Valued Networks: Definition,
Computation, and Applications.” Bioinformatics, vol. 39, no. Supplement_1,
Oxford Academic, 2023, pp. i513–22, doi:10.1093/bioinformatics/btad262.'
short: V.G. Trinh, B. Benhamou, T.A. Henzinger, S. Pastva, Bioinformatics 39 (2023)
i513–i522.
date_created: 2023-07-23T22:01:12Z
date_published: 2023-06-30T00:00:00Z
date_updated: 2023-12-13T11:41:52Z
day: '30'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.1093/bioinformatics/btad262
ec_funded: 1
external_id:
isi:
- '001027457000060'
pmid:
- '37387165'
file:
- access_level: open_access
checksum: ba3abe1171df1958413b7c7f957f5486
content_type: application/pdf
creator: dernst
date_created: 2023-07-31T11:09:05Z
date_updated: 2023-07-31T11:09:05Z
file_id: '13335'
file_name: 2023_Bioinformatics_Trinh.pdf
file_size: 641736
relation: main_file
success: 1
file_date_updated: 2023-07-31T11:09:05Z
has_accepted_license: '1'
intvolume: ' 39'
isi: 1
issue: Supplement_1
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
page: i513-i522
pmid: 1
project:
- _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c
call_identifier: H2020
grant_number: '101034413'
name: 'IST-BRIDGE: International postdoctoral program'
publication: Bioinformatics
publication_identifier:
eissn:
- 1367-4811
issn:
- 1367-4803
publication_status: published
publisher: Oxford Academic
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/giang-trinh/trap-mvn
scopus_import: '1'
status: public
title: 'Trap spaces of multi-valued networks: Definition, computation, and applications'
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: 39
year: '2023'
...
---
_id: '12876'
abstract:
- lang: eng
text: "Motivation: The problem of model inference is of fundamental importance to
systems biology. Logical models (e.g. Boolean networks; BNs) represent a computationally
attractive approach capable of handling large biological networks. The models
are typically inferred from experimental data. However, even with a substantial
amount of experimental data supported by some prior knowledge, existing inference
methods often focus on a small sample of admissible candidate models only.\r\n\r\nResults:
We propose Boolean network sketches as a new formal instrument for the inference
of Boolean networks. A sketch integrates (typically partial) knowledge about the
network’s topology and the update logic (obtained through, e.g. a biological knowledge
base or a literature search), as well as further assumptions about the properties
of the network’s transitions (e.g. the form of its attractor landscape), and additional
restrictions on the model dynamics given by the measured experimental data. Our
new BNs inference algorithm starts with an ‘initial’ sketch, which is extended
by adding restrictions representing experimental data to a ‘data-informed’ sketch
and subsequently computes all BNs consistent with the data-informed sketch. Our
algorithm is based on a symbolic representation and coloured model-checking. Our
approach is unique in its ability to cover a broad spectrum of knowledge and efficiently
produce a compact representation of all inferred BNs. We evaluate the method on
a non-trivial collection of real-world and simulated data."
acknowledgement: This work was partially supported by GACR [grant No. GA22-10845S];
and Grant Agency of Masaryk University [grant No. MUNI/G/1771/2020]. This work was
partially supported by European Union’s Horizon 2020 research and innovation programme
under the Marie Skłodowska-Curie [Grant Agreement No. 101034413 to S.P.].
article_number: btad158
article_processing_charge: No
article_type: original
author:
- first_name: Nikola
full_name: Beneš, Nikola
last_name: Beneš
- first_name: Luboš
full_name: Brim, Luboš
last_name: Brim
- first_name: Ondřej
full_name: Huvar, Ondřej
last_name: Huvar
- first_name: Samuel
full_name: Pastva, Samuel
id: 07c5ea74-f61c-11ec-a664-aa7c5d957b2b
last_name: Pastva
- first_name: David
full_name: Šafránek, David
last_name: Šafránek
citation:
ama: 'Beneš N, Brim L, Huvar O, Pastva S, Šafránek D. Boolean network sketches:
A unifying framework for logical model inference. Bioinformatics. 2023;39(4).
doi:10.1093/bioinformatics/btad158'
apa: 'Beneš, N., Brim, L., Huvar, O., Pastva, S., & Šafránek, D. (2023). Boolean
network sketches: A unifying framework for logical model inference. Bioinformatics.
Oxford Academic. https://doi.org/10.1093/bioinformatics/btad158'
chicago: 'Beneš, Nikola, Luboš Brim, Ondřej Huvar, Samuel Pastva, and David Šafránek.
“Boolean Network Sketches: A Unifying Framework for Logical Model Inference.”
Bioinformatics. Oxford Academic, 2023. https://doi.org/10.1093/bioinformatics/btad158.'
ieee: 'N. Beneš, L. Brim, O. Huvar, S. Pastva, and D. Šafránek, “Boolean network
sketches: A unifying framework for logical model inference,” Bioinformatics,
vol. 39, no. 4. Oxford Academic, 2023.'
ista: 'Beneš N, Brim L, Huvar O, Pastva S, Šafránek D. 2023. Boolean network sketches:
A unifying framework for logical model inference. Bioinformatics. 39(4), btad158.'
mla: 'Beneš, Nikola, et al. “Boolean Network Sketches: A Unifying Framework for
Logical Model Inference.” Bioinformatics, vol. 39, no. 4, btad158, Oxford
Academic, 2023, doi:10.1093/bioinformatics/btad158.'
short: N. Beneš, L. Brim, O. Huvar, S. Pastva, D. Šafránek, Bioinformatics 39 (2023).
date_created: 2023-04-30T22:01:05Z
date_published: 2023-04-03T00:00:00Z
date_updated: 2023-08-01T14:27:28Z
day: '03'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.1093/bioinformatics/btad158
ec_funded: 1
external_id:
isi:
- '000976610800001'
pmid:
- '37004199'
file:
- access_level: open_access
checksum: 2cb90ddf781baefddf47eac4b54e2a03
content_type: application/pdf
creator: dernst
date_created: 2023-05-02T07:39:04Z
date_updated: 2023-05-02T07:39:04Z
file_id: '12886'
file_name: 2023_Bioinformatics_Benes.pdf
file_size: 478740
relation: main_file
success: 1
file_date_updated: 2023-05-02T07:39:04Z
has_accepted_license: '1'
intvolume: ' 39'
isi: 1
issue: '4'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c
call_identifier: H2020
grant_number: '101034413'
name: 'IST-BRIDGE: International postdoctoral program'
publication: Bioinformatics
publication_identifier:
eissn:
- 1367-4811
publication_status: published
publisher: Oxford Academic
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://doi.org/10.5281/zenodo.7688740
scopus_import: '1'
status: public
title: 'Boolean network sketches: A unifying framework for logical model inference'
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: 39
year: '2023'
...