---
_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: '10927'
abstract:
- lang: eng
text: "Motivation\r\nHigh plasticity of bacterial genomes is provided by numerous
mechanisms including horizontal gene transfer and recombination via numerous flanking
repeats. Genome rearrangements such as inversions, deletions, insertions and duplications
may independently occur in different strains, providing parallel adaptation or
phenotypic diversity. Specifically, such rearrangements might be responsible for
virulence, antibiotic resistance and antigenic variation. However, identification
of such events requires laborious manual inspection and verification of phyletic
pattern consistency.\r\nResults\r\nHere, we define the term ‘parallel rearrangements’
as events that occur independently in phylogenetically distant bacterial strains
and present a formalization of the problem of parallel rearrangements calling.
We implement an algorithmic solution for the identification of parallel rearrangements
in bacterial populations as a tool PaReBrick. The tool takes a collection of strains
represented as a sequence of oriented synteny blocks and a phylogenetic tree as
input data. It identifies rearrangements, tests them for consistency with a tree,
and sorts the events by their parallelism score. The tool provides diagrams of
the neighbors for each block of interest, allowing the detection of horizontally
transferred blocks or their extra copies and the inversions in which copied blocks
are involved. We demonstrated PaReBrick’s efficiency and accuracy and showed its
potential to detect genome rearrangements responsible for pathogenicity and adaptation
in bacterial genomes."
acknowledgement: "The authors thank the 2020 student class of the Bioinformatics Institute,
who\r\nused the first versions of the tool and provided many valuable suggestions
to\r\nimprove usability. They also thank Louisa Gonzalez Somermeyer for manuscript
proofreading\r\nThis work was supported by the National Center for Cognitive Research
of\r\nITMO University and JetBrains Research [to A.Z and N.A.]; and the European\r\nUnion’s
Horizon 2020 Research and Innovation Programme under the Marie\r\nSkłodowska-Curie
[754411 to O.B.].\r\nPaReBrick is written in Python and is available on GitHub:
https://github.com/ctlab/parallel-rearrangements."
article_processing_charge: No
article_type: original
author:
- first_name: Alexey
full_name: Zabelkin, Alexey
last_name: Zabelkin
- first_name: Yulia
full_name: Yakovleva, Yulia
last_name: Yakovleva
- first_name: Olga
full_name: Bochkareva, Olga
id: C4558D3C-6102-11E9-A62E-F418E6697425
last_name: Bochkareva
orcid: 0000-0003-1006-6639
- first_name: Nikita
full_name: Alexeev, Nikita
last_name: Alexeev
citation:
ama: 'Zabelkin A, Yakovleva Y, Bochkareva O, Alexeev N. PaReBrick: PArallel REarrangements
and BReaks identification toolkit. Bioinformatics. 2022;38(2):357-363.
doi:10.1093/bioinformatics/btab691'
apa: 'Zabelkin, A., Yakovleva, Y., Bochkareva, O., & Alexeev, N. (2022). PaReBrick:
PArallel REarrangements and BReaks identification toolkit. Bioinformatics.
Oxford Academic. https://doi.org/10.1093/bioinformatics/btab691'
chicago: 'Zabelkin, Alexey, Yulia Yakovleva, Olga Bochkareva, and Nikita Alexeev.
“PaReBrick: PArallel REarrangements and BReaks Identification Toolkit.” Bioinformatics.
Oxford Academic, 2022. https://doi.org/10.1093/bioinformatics/btab691.'
ieee: 'A. Zabelkin, Y. Yakovleva, O. Bochkareva, and N. Alexeev, “PaReBrick: PArallel
REarrangements and BReaks identification toolkit,” Bioinformatics, vol.
38, no. 2. Oxford Academic, pp. 357–363, 2022.'
ista: 'Zabelkin A, Yakovleva Y, Bochkareva O, Alexeev N. 2022. PaReBrick: PArallel
REarrangements and BReaks identification toolkit. Bioinformatics. 38(2), 357–363.'
mla: 'Zabelkin, Alexey, et al. “PaReBrick: PArallel REarrangements and BReaks Identification
Toolkit.” Bioinformatics, vol. 38, no. 2, Oxford Academic, 2022, pp. 357–63,
doi:10.1093/bioinformatics/btab691.'
short: A. Zabelkin, Y. Yakovleva, O. Bochkareva, N. Alexeev, Bioinformatics 38 (2022)
357–363.
date_created: 2022-03-27T22:01:46Z
date_published: 2022-01-15T00:00:00Z
date_updated: 2023-08-03T06:21:46Z
day: '15'
ddc:
- '000'
department:
- _id: FyKo
doi: 10.1093/bioinformatics/btab691
ec_funded: 1
external_id:
isi:
- '000743380100008'
file:
- access_level: open_access
checksum: 4b5688ff9ac86180ccdf7f82fa33d926
content_type: application/pdf
creator: dernst
date_created: 2022-03-28T08:07:46Z
date_updated: 2022-03-28T08:07:46Z
file_id: '10930'
file_name: 2022_Bioinformatics_Zabelkin.pdf
file_size: 3425744
relation: main_file
success: 1
file_date_updated: 2022-03-28T08:07:46Z
has_accepted_license: '1'
intvolume: ' 38'
isi: 1
issue: '2'
language:
- iso: eng
month: '01'
oa: 1
oa_version: Published Version
page: 357-363
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Bioinformatics
publication_identifier:
eissn:
- 1460-2059
issn:
- 1367-4803
publication_status: published
publisher: Oxford Academic
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/ctlab/parallel-rearrangements
scopus_import: '1'
status: public
title: 'PaReBrick: PArallel REarrangements and BReaks identification toolkit'
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: 38
year: '2022'
...
---
_id: '8645'
abstract:
- lang: eng
text: 'Epistasis, the context-dependence of the contribution of an amino acid substitution
to fitness, is common in evolution. To detect epistasis, fitness must be measured
for at least four genotypes: the reference genotype, two different single mutants
and a double mutant with both of the single mutations. For higher-order epistasis
of the order n, fitness has to be measured for all 2n genotypes of an n-dimensional
hypercube in genotype space forming a ‘combinatorially complete dataset’. So far,
only a handful of such datasets have been produced by manual curation. Concurrently,
random mutagenesis experiments have produced measurements of fitness and other
phenotypes in a high-throughput manner, potentially containing a number of combinatorially
complete datasets. We present an effective recursive algorithm for finding all
hypercube structures in random mutagenesis experimental data. To test the algorithm,
we applied it to the data from a recent HIS3 protein dataset and found all 199
847 053 unique combinatorially complete genotype combinations of dimensionality
ranging from 2 to 12. The algorithm may be useful for researchers looking for
higher-order epistasis in their high-throughput experimental data.'
acknowledgement: 'This work was supported by the European Research Council under the
European Union’s Seventh Framework Programme (FP7/2007-2013, ERC grant agreement
335980_EinME) and Startup package to the Ivankov laboratory at Skolkovo Institute
of Science and Technology. The work was started at the School of Molecular and Theoretical
Biology 2017 supported by the Zimin Foundation. N.S.B. was supported by the Woman
Scientists Support Grant in Centre for Genomic Regulation (CRG). '
article_processing_charge: No
article_type: original
author:
- first_name: Laura A
full_name: Esteban, Laura A
last_name: Esteban
- first_name: Lyubov R
full_name: Lonishin, Lyubov R
last_name: Lonishin
- first_name: Daniil M
full_name: Bobrovskiy, Daniil M
last_name: Bobrovskiy
- first_name: Gregory
full_name: Leleytner, Gregory
last_name: Leleytner
- first_name: Natalya S
full_name: Bogatyreva, Natalya S
last_name: Bogatyreva
- 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: 'Esteban LA, Lonishin LR, Bobrovskiy DM, et al. HypercubeME: Two hundred million
combinatorially complete datasets from a single experiment. Bioinformatics.
2020;36(6):1960-1962. doi:10.1093/bioinformatics/btz841'
apa: 'Esteban, L. A., Lonishin, L. R., Bobrovskiy, D. M., Leleytner, G., Bogatyreva,
N. S., Kondrashov, F., & Ivankov, D. N. (2020). HypercubeME: Two hundred million
combinatorially complete datasets from a single experiment. Bioinformatics.
Oxford Academic. https://doi.org/10.1093/bioinformatics/btz841'
chicago: 'Esteban, Laura A, Lyubov R Lonishin, Daniil M Bobrovskiy, Gregory Leleytner,
Natalya S Bogatyreva, Fyodor Kondrashov, and Dmitry N Ivankov. “HypercubeME:
Two Hundred Million Combinatorially Complete Datasets from a Single Experiment.”
Bioinformatics. Oxford Academic, 2020. https://doi.org/10.1093/bioinformatics/btz841.'
ieee: 'L. A. Esteban et al., “HypercubeME: Two hundred million combinatorially
complete datasets from a single experiment,” Bioinformatics, vol. 36, no.
6. Oxford Academic, pp. 1960–1962, 2020.'
ista: 'Esteban LA, Lonishin LR, Bobrovskiy DM, Leleytner G, Bogatyreva NS, Kondrashov
F, Ivankov DN. 2020. HypercubeME: Two hundred million combinatorially complete
datasets from a single experiment. Bioinformatics. 36(6), 1960–1962.'
mla: 'Esteban, Laura A., et al. “HypercubeME: Two Hundred Million Combinatorially
Complete Datasets from a Single Experiment.” Bioinformatics, vol. 36, no.
6, Oxford Academic, 2020, pp. 1960–62, doi:10.1093/bioinformatics/btz841.'
short: L.A. Esteban, L.R. Lonishin, D.M. Bobrovskiy, G. Leleytner, N.S. Bogatyreva,
F. Kondrashov, D.N. Ivankov, Bioinformatics 36 (2020) 1960–1962.
date_created: 2020-10-11T22:01:14Z
date_published: 2020-03-15T00:00:00Z
date_updated: 2023-08-22T09:57:29Z
day: '15'
ddc:
- '000'
- '570'
department:
- _id: FyKo
doi: 10.1093/bioinformatics/btz841
ec_funded: 1
external_id:
isi:
- '000538696800054'
pmid:
- '31742320'
file:
- access_level: open_access
checksum: 21d6f71839deb3b83e4a356193f72767
content_type: application/pdf
creator: dernst
date_created: 2020-10-12T12:02:09Z
date_updated: 2020-10-12T12:02:09Z
file_id: '8649'
file_name: 2020_Bioinformatics_Esteban.pdf
file_size: 308341
relation: main_file
success: 1
file_date_updated: 2020-10-12T12:02:09Z
has_accepted_license: '1'
intvolume: ' 36'
isi: 1
issue: '6'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc/4.0/
month: '03'
oa: 1
oa_version: Published Version
page: 1960-1962
pmid: 1
project:
- _id: 26120F5C-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '335980'
name: Systematic investigation of epistasis in molecular evolution
publication: Bioinformatics
publication_identifier:
eissn:
- 1460-2059
issn:
- 1367-4803
publication_status: published
publisher: Oxford Academic
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'HypercubeME: Two hundred million combinatorially complete datasets from a
single experiment'
tmp:
image: /images/cc_by_nc.png
legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode
name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
short: CC BY-NC (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 36
year: '2020'
...
---
_id: '5995'
abstract:
- lang: eng
text: "Motivation\r\nComputational prediction of the effect of mutations on protein
stability is used by researchers in many fields. The utility of the prediction
methods is affected by their accuracy and bias. Bias, a systematic shift of the
predicted change of stability, has been noted as an issue for several methods,
but has not been investigated systematically. Presence of the bias may lead to
misleading results especially when exploring the effects of combination of different
mutations.\r\n\r\nResults\r\nHere we use a protocol to measure the bias as a function
of the number of introduced mutations. It is based on a self-consistency test
of the reciprocity the effect of a mutation. An advantage of the used approach
is that it relies solely on crystal structures without experimentally measured
stability values. We applied the protocol to four popular algorithms predicting
change of protein stability upon mutation, FoldX, Eris, Rosetta and I-Mutant,
and found an inherent bias. For one program, FoldX, we manage to substantially
reduce the bias using additional relaxation by Modeller. Authors using algorithms
for predicting effects of mutations should be aware of the bias described here."
article_processing_charge: No
author:
- first_name: Dinara R
full_name: Usmanova, Dinara R
last_name: Usmanova
- first_name: Natalya S
full_name: Bogatyreva, Natalya S
last_name: Bogatyreva
- first_name: Joan
full_name: Ariño Bernad, Joan
last_name: Ariño Bernad
- first_name: Aleksandra A
full_name: Eremina, Aleksandra A
last_name: Eremina
- first_name: Anastasiya A
full_name: Gorshkova, Anastasiya A
last_name: Gorshkova
- first_name: German M
full_name: Kanevskiy, German M
last_name: Kanevskiy
- first_name: Lyubov R
full_name: Lonishin, Lyubov R
last_name: Lonishin
- first_name: Alexander V
full_name: Meister, Alexander V
last_name: Meister
- first_name: Alisa G
full_name: Yakupova, Alisa G
last_name: Yakupova
- first_name: Fyodor
full_name: Kondrashov, Fyodor
id: 44FDEF62-F248-11E8-B48F-1D18A9856A87
last_name: Kondrashov
orcid: 0000-0001-8243-4694
- first_name: Dmitry
full_name: Ivankov, Dmitry
id: 49FF1036-F248-11E8-B48F-1D18A9856A87
last_name: Ivankov
citation:
ama: Usmanova DR, Bogatyreva NS, Ariño Bernad J, et al. Self-consistency test reveals
systematic bias in programs for prediction change of stability upon mutation.
Bioinformatics. 2018;34(21):3653-3658. doi:10.1093/bioinformatics/bty340
apa: Usmanova, D. R., Bogatyreva, N. S., Ariño Bernad, J., Eremina, A. A., Gorshkova,
A. A., Kanevskiy, G. M., … Ivankov, D. (2018). Self-consistency test reveals systematic
bias in programs for prediction change of stability upon mutation. Bioinformatics.
Oxford University Press . https://doi.org/10.1093/bioinformatics/bty340
chicago: Usmanova, Dinara R, Natalya S Bogatyreva, Joan Ariño Bernad, Aleksandra
A Eremina, Anastasiya A Gorshkova, German M Kanevskiy, Lyubov R Lonishin, et al.
“Self-Consistency Test Reveals Systematic Bias in Programs for Prediction Change
of Stability upon Mutation.” Bioinformatics. Oxford University Press ,
2018. https://doi.org/10.1093/bioinformatics/bty340.
ieee: D. R. Usmanova et al., “Self-consistency test reveals systematic bias
in programs for prediction change of stability upon mutation,” Bioinformatics,
vol. 34, no. 21. Oxford University Press , pp. 3653–3658, 2018.
ista: Usmanova DR, Bogatyreva NS, Ariño Bernad J, Eremina AA, Gorshkova AA, Kanevskiy
GM, Lonishin LR, Meister AV, Yakupova AG, Kondrashov F, Ivankov D. 2018. Self-consistency
test reveals systematic bias in programs for prediction change of stability upon
mutation. Bioinformatics. 34(21), 3653–3658.
mla: Usmanova, Dinara R., et al. “Self-Consistency Test Reveals Systematic Bias
in Programs for Prediction Change of Stability upon Mutation.” Bioinformatics,
vol. 34, no. 21, Oxford University Press , 2018, pp. 3653–58, doi:10.1093/bioinformatics/bty340.
short: D.R. Usmanova, N.S. Bogatyreva, J. Ariño Bernad, A.A. Eremina, A.A. Gorshkova,
G.M. Kanevskiy, L.R. Lonishin, A.V. Meister, A.G. Yakupova, F. Kondrashov, D.
Ivankov, Bioinformatics 34 (2018) 3653–3658.
date_created: 2019-02-14T12:48:00Z
date_published: 2018-11-01T00:00:00Z
date_updated: 2023-09-19T14:31:13Z
day: '01'
ddc:
- '570'
department:
- _id: FyKo
doi: 10.1093/bioinformatics/bty340
ec_funded: 1
external_id:
isi:
- '000450038900008'
pmid:
- '29722803'
file:
- access_level: open_access
checksum: 7e0495153f44211479674601d7f6ee03
content_type: application/pdf
creator: kschuh
date_created: 2019-02-14T13:00:55Z
date_updated: 2020-07-14T12:47:15Z
file_id: '5997'
file_name: 2018_Oxford_Usmanova.pdf
file_size: 291969
relation: main_file
file_date_updated: 2020-07-14T12:47:15Z
has_accepted_license: '1'
intvolume: ' 34'
isi: 1
issue: '21'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
page: 3653-3658
pmid: 1
project:
- _id: 26120F5C-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '335980'
name: Systematic investigation of epistasis in molecular evolution
publication: Bioinformatics
publication_identifier:
issn:
- 1367-4803
- 1460-2059
publication_status: published
publisher: 'Oxford University Press '
quality_controlled: '1'
scopus_import: '1'
status: public
title: Self-consistency test reveals systematic bias in programs for prediction change
of stability upon mutation
tmp:
image: /images/cc_by_nc.png
legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode
name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
short: CC BY-NC (4.0)
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 34
year: '2018'
...
---
_id: '8459'
abstract:
- lang: eng
text: Nuclear magnetic resonance (NMR) is a powerful tool for observing the motion
of biomolecules at the atomic level. One technique, the analysis of relaxation
dispersion phenomenon, is highly suited for studying the kinetics and thermodynamics
of biological processes. Built on top of the relax computational environment for
NMR dynamics is a new dispersion analysis designed to be comprehensive, accurate
and easy-to-use. The software supports more models, both numeric and analytic,
than current solutions. An automated protocol, available for scripting and driving
the graphical user interface (GUI), is designed to simplify the analysis of dispersion
data for NMR spectroscopists. Decreases in optimization time are granted by parallelization
for running on computer clusters and by skipping an initial grid search by using
parameters from one solution as the starting point for another —using analytic
model results for the numeric models, taking advantage of model nesting, and using
averaged non-clustered results for the clustered analysis.
article_processing_charge: No
article_type: original
author:
- first_name: Sébastien
full_name: Morin, Sébastien
last_name: Morin
- first_name: Troels E
full_name: Linnet, Troels E
last_name: Linnet
- first_name: Mathilde
full_name: Lescanne, Mathilde
last_name: Lescanne
- first_name: Paul
full_name: Schanda, Paul
id: 7B541462-FAF6-11E9-A490-E8DFE5697425
last_name: Schanda
orcid: 0000-0002-9350-7606
- first_name: Gary S
full_name: Thompson, Gary S
last_name: Thompson
- first_name: Martin
full_name: Tollinger, Martin
last_name: Tollinger
- first_name: Kaare
full_name: Teilum, Kaare
last_name: Teilum
- first_name: Stéphane
full_name: Gagné, Stéphane
last_name: Gagné
- first_name: Dominique
full_name: Marion, Dominique
last_name: Marion
- first_name: Christian
full_name: Griesinger, Christian
last_name: Griesinger
- first_name: Martin
full_name: Blackledge, Martin
last_name: Blackledge
- first_name: Edward J
full_name: d’Auvergne, Edward J
last_name: d’Auvergne
citation:
ama: 'Morin S, Linnet TE, Lescanne M, et al. Relax: The analysis of biomolecular
kinetics and thermodynamics using NMR relaxation dispersion data. Bioinformatics.
2014;30(15):2219-2220. doi:10.1093/bioinformatics/btu166'
apa: 'Morin, S., Linnet, T. E., Lescanne, M., Schanda, P., Thompson, G. S., Tollinger,
M., … d’Auvergne, E. J. (2014). Relax: The analysis of biomolecular kinetics and
thermodynamics using NMR relaxation dispersion data. Bioinformatics. Oxford
University Press. https://doi.org/10.1093/bioinformatics/btu166'
chicago: 'Morin, Sébastien, Troels E Linnet, Mathilde Lescanne, Paul Schanda, Gary
S Thompson, Martin Tollinger, Kaare Teilum, et al. “Relax: The Analysis of Biomolecular
Kinetics and Thermodynamics Using NMR Relaxation Dispersion Data.” Bioinformatics.
Oxford University Press, 2014. https://doi.org/10.1093/bioinformatics/btu166.'
ieee: 'S. Morin et al., “Relax: The analysis of biomolecular kinetics and
thermodynamics using NMR relaxation dispersion data,” Bioinformatics, vol.
30, no. 15. Oxford University Press, pp. 2219–2220, 2014.'
ista: 'Morin S, Linnet TE, Lescanne M, Schanda P, Thompson GS, Tollinger M, Teilum
K, Gagné S, Marion D, Griesinger C, Blackledge M, d’Auvergne EJ. 2014. Relax:
The analysis of biomolecular kinetics and thermodynamics using NMR relaxation
dispersion data. Bioinformatics. 30(15), 2219–2220.'
mla: 'Morin, Sébastien, et al. “Relax: The Analysis of Biomolecular Kinetics and
Thermodynamics Using NMR Relaxation Dispersion Data.” Bioinformatics, vol.
30, no. 15, Oxford University Press, 2014, pp. 2219–20, doi:10.1093/bioinformatics/btu166.'
short: S. Morin, T.E. Linnet, M. Lescanne, P. Schanda, G.S. Thompson, M. Tollinger,
K. Teilum, S. Gagné, D. Marion, C. Griesinger, M. Blackledge, E.J. d’Auvergne,
Bioinformatics 30 (2014) 2219–2220.
date_created: 2020-09-18T10:08:07Z
date_published: 2014-08-01T00:00:00Z
date_updated: 2021-01-12T08:19:25Z
day: '01'
doi: 10.1093/bioinformatics/btu166
extern: '1'
intvolume: ' 30'
issue: '15'
keyword:
- Statistics and Probability
- Computational Theory and Mathematics
- Biochemistry
- Molecular Biology
- Computational Mathematics
- Computer Science Applications
language:
- iso: eng
month: '08'
oa_version: None
page: 2219-2220
publication: Bioinformatics
publication_identifier:
issn:
- 1367-4803
- 1460-2059
publication_status: published
publisher: Oxford University Press
quality_controlled: '1'
related_material:
link:
- relation: erratum
url: https://doi.org/10.1093/bioinformatics/btz397
status: public
title: 'Relax: The analysis of biomolecular kinetics and thermodynamics using NMR
relaxation dispersion data'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 30
year: '2014'
...
---
_id: '855'
abstract:
- lang: eng
text: 'Motivation: The context of the start codon (typically, AUG) and the features
of the 5′ Untranslated Regions (5′ UTRs) are important for understanding translation
regulation in eukaryotic mRNAs and for accurate prediction of the coding region
in genomic and cDNA sequences. The presence of AUG triplets in 5′ UTRs (upstream
AUGs) might effect the initiation rate and, in the context of gene prediction,
could reduce the accuracy of the identification of the authentic start. To reveal
potential connections between the presence of upstream AUGs and other features
of 5′ UTRs, such as their length and the start codon context, we undertook a systematic
analysis of the available eukaryotic 5′ UTR sequences. Results: We show that a
large fraction of 5′ UTRs in the available cDNA sequences, 15-53% depending on
the organism, contain upstream ATGs. A negative correlation was observed between
the information content of the translation start signal and the length of the
5′ UTR. Similarly, a negative correlation exists between the ''strength'' of the
start context and the number of upstream ATGs. Typically, cDNAs containing long
5′ UTRs with multiple upstream ATGs have a ''weak'' start context, and in contrast,
cDNAs containing short 5′ UTRs without ATGs have ''strong'' starts. These counter-intuitive
results may be interpreted in terms of upstream AUGs having an important role
in the regulation of translation efficiency by ensuring low basal translation
level via double negative control and creating the potential for additional regulatory
mechanisms. One of such mechanisms, supported by experimental studies of some
mRNAs, includes removal of the AUG-containing portion of the 5′ UTR by alternative
splicing.'
acknowledgement: This work has been partially supported by EU 'TRADAT' project and
by CNR Genetic Engineering (Italy), the RFBR grant for support of scientific schools
(00-15-97968) and SD RAS grant for young scientists (AVK). The authors wish to thank
J.Lyons-Weiler for helpful comments and A. Sorokin for help with the ATG_EVALUATOR
program.
article_processing_charge: No
article_type: original
author:
- first_name: Igor
full_name: Rogozin, Igor
last_name: Rogozin
- first_name: Alex
full_name: Kochetov, Alex
last_name: Kochetov
- first_name: Fyodor
full_name: Kondrashov, Fyodor
id: 44FDEF62-F248-11E8-B48F-1D18A9856A87
last_name: Kondrashov
orcid: 0000-0001-8243-4694
- first_name: Eugene
full_name: Koonin, Eugene
last_name: Koonin
- first_name: Luciano
full_name: Milanesi, Luciano
last_name: Milanesi
citation:
ama: Rogozin I, Kochetov A, Kondrashov F, Koonin E, Milanesi L. Presence of ATG
triplets in 5′ untranslated regions of eukaryotic cDNAs correlates with a ’weak’context
of the start codon. Bioinformatics. 2001;17(10):890-900. doi:10.1093/bioinformatics/17.10.890
apa: Rogozin, I., Kochetov, A., Kondrashov, F., Koonin, E., & Milanesi, L. (2001).
Presence of ATG triplets in 5′ untranslated regions of eukaryotic cDNAs correlates
with a ’weak’context of the start codon. Bioinformatics. Oxford University
Press. https://doi.org/10.1093/bioinformatics/17.10.890
chicago: Rogozin, Igor, Alex Kochetov, Fyodor Kondrashov, Eugene Koonin, and Luciano
Milanesi. “Presence of ATG Triplets in 5′ Untranslated Regions of Eukaryotic CDNAs
Correlates with a ’weak’context of the Start Codon.” Bioinformatics. Oxford
University Press, 2001. https://doi.org/10.1093/bioinformatics/17.10.890.
ieee: I. Rogozin, A. Kochetov, F. Kondrashov, E. Koonin, and L. Milanesi, “Presence
of ATG triplets in 5′ untranslated regions of eukaryotic cDNAs correlates with
a ’weak’context of the start codon,” Bioinformatics, vol. 17, no. 10. Oxford
University Press, pp. 890–900, 2001.
ista: Rogozin I, Kochetov A, Kondrashov F, Koonin E, Milanesi L. 2001. Presence
of ATG triplets in 5′ untranslated regions of eukaryotic cDNAs correlates with
a ’weak’context of the start codon. Bioinformatics. 17(10), 890–900.
mla: Rogozin, Igor, et al. “Presence of ATG Triplets in 5′ Untranslated Regions
of Eukaryotic CDNAs Correlates with a ’weak’context of the Start Codon.” Bioinformatics,
vol. 17, no. 10, Oxford University Press, 2001, pp. 890–900, doi:10.1093/bioinformatics/17.10.890.
short: I. Rogozin, A. Kochetov, F. Kondrashov, E. Koonin, L. Milanesi, Bioinformatics
17 (2001) 890–900.
date_created: 2018-12-11T11:48:52Z
date_published: 2001-10-01T00:00:00Z
date_updated: 2023-06-02T09:08:25Z
day: '01'
doi: 10.1093/bioinformatics/17.10.890
extern: '1'
external_id:
pmid:
- '11673233'
intvolume: ' 17'
issue: '10'
language:
- iso: eng
month: '10'
oa_version: None
page: 890 - 900
pmid: 1
publication: Bioinformatics
publication_identifier:
issn:
- 1367-4803
publication_status: published
publisher: Oxford University Press
publist_id: '6795'
quality_controlled: '1'
scopus_import: '1'
status: public
title: Presence of ATG triplets in 5′ untranslated regions of eukaryotic cDNAs correlates
with a 'weak'context of the start codon
type: journal_article
user_id: ea97e931-d5af-11eb-85d4-e6957dddbf17
volume: 17
year: '2001'
...