Perturbations and their effects within networks.
<p><b>(A)</b> Overview of gene expression model and its parameters. Here, <i>σ</i> is the logistic sigmoid . <b>(B)</b> Example forward simulation of the dynamical systems model. Trace lines show genes, whose expression values are initialized at zero. The sy...
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2025
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| _version_ | 1852017061630312448 |
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| author | Matthew Aguirre (9558032) |
| author2 | Jeffrey P. Spence (15317543) Guy Sella (230321) Jonathan K. Pritchard (8027465) |
| author2_role | author author author |
| author_facet | Matthew Aguirre (9558032) Jeffrey P. Spence (15317543) Guy Sella (230321) Jonathan K. Pritchard (8027465) |
| author_role | author |
| dc.creator.none.fl_str_mv | Matthew Aguirre (9558032) Jeffrey P. Spence (15317543) Guy Sella (230321) Jonathan K. Pritchard (8027465) |
| dc.date.none.fl_str_mv | 2025-09-02T18:03:15Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pcbi.1013387.g003 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Perturbations_and_their_effects_within_networks_/30037032 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Genetics Molecular Biology Developmental Biology Infectious Diseases Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified world network theory consider future avenues interpret gene coexpression gene knockouts within better understand properties scale perturbation study like hierarchical structure unperturbed cells may gene regulation unperturbed states scale efforts key properties systematically describe remains challenging recent genome recapitulate features perturbation data new approach molecular perturbations modular organization efficient manner deeper analysis |
| dc.title.none.fl_str_mv | Perturbations and their effects within networks. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p><b>(A)</b> Overview of gene expression model and its parameters. Here, <i>σ</i> is the logistic sigmoid . <b>(B)</b> Example forward simulation of the dynamical systems model. Trace lines show genes, whose expression values are initialized at zero. The system eventually reaches a steady-state, and is then subject to perturbation (knockout of gene <i>j</i>, i.e. holding <i>x</i><sub><i>j</i></sub> = 0). Further forward simulation leads to a new steady-state, from which we can compute perturbation effects ( for other genes <i>i</i>). <b>(C)</b> Distribution of knockout (KO) effects (i.e., fold-changes in expression <i>x</i><sub><i>i</i></sub> of a focal gene <i>i</i>) in 50 example GRNs, along with the median distribution (black line). <b>(D)</b> KO effects as a function of network distance between two genes, and <b>(E)</b> within and across modules given by the generating algorithm. Note that the solid lines in <b>(D)</b> and <b>(E)</b> are the median distributions over the 50 example GRNs, split respectively by distances and modules.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_065174ff831773fcf8e46ba63e0fc270 |
| identifier_str_mv | 10.1371/journal.pcbi.1013387.g003 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/30037032 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Perturbations and their effects within networks.Matthew Aguirre (9558032)Jeffrey P. Spence (15317543)Guy Sella (230321)Jonathan K. Pritchard (8027465)GeneticsMolecular BiologyDevelopmental BiologyInfectious DiseasesComputational BiologyBiological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedworld network theoryconsider future avenuesinterpret gene coexpressiongene knockouts withinbetter understand propertiesscale perturbation studylike hierarchical structureunperturbed cells maygene regulationunperturbed statesscale effortskey propertiessystematically describeremains challengingrecent genomerecapitulate featuresperturbation datanew approachmolecular perturbationsmodular organizationefficient mannerdeeper analysis<p><b>(A)</b> Overview of gene expression model and its parameters. Here, <i>σ</i> is the logistic sigmoid . <b>(B)</b> Example forward simulation of the dynamical systems model. Trace lines show genes, whose expression values are initialized at zero. The system eventually reaches a steady-state, and is then subject to perturbation (knockout of gene <i>j</i>, i.e. holding <i>x</i><sub><i>j</i></sub> = 0). Further forward simulation leads to a new steady-state, from which we can compute perturbation effects ( for other genes <i>i</i>). <b>(C)</b> Distribution of knockout (KO) effects (i.e., fold-changes in expression <i>x</i><sub><i>i</i></sub> of a focal gene <i>i</i>) in 50 example GRNs, along with the median distribution (black line). <b>(D)</b> KO effects as a function of network distance between two genes, and <b>(E)</b> within and across modules given by the generating algorithm. Note that the solid lines in <b>(D)</b> and <b>(E)</b> are the median distributions over the 50 example GRNs, split respectively by distances and modules.</p>2025-09-02T18:03:15ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pcbi.1013387.g003https://figshare.com/articles/figure/Perturbations_and_their_effects_within_networks_/30037032CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/300370322025-09-02T18:03:15Z |
| spellingShingle | Perturbations and their effects within networks. Matthew Aguirre (9558032) Genetics Molecular Biology Developmental Biology Infectious Diseases Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified world network theory consider future avenues interpret gene coexpression gene knockouts within better understand properties scale perturbation study like hierarchical structure unperturbed cells may gene regulation unperturbed states scale efforts key properties systematically describe remains challenging recent genome recapitulate features perturbation data new approach molecular perturbations modular organization efficient manner deeper analysis |
| status_str | publishedVersion |
| title | Perturbations and their effects within networks. |
| title_full | Perturbations and their effects within networks. |
| title_fullStr | Perturbations and their effects within networks. |
| title_full_unstemmed | Perturbations and their effects within networks. |
| title_short | Perturbations and their effects within networks. |
| title_sort | Perturbations and their effects within networks. |
| topic | Genetics Molecular Biology Developmental Biology Infectious Diseases Computational Biology Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified world network theory consider future avenues interpret gene coexpression gene knockouts within better understand properties scale perturbation study like hierarchical structure unperturbed cells may gene regulation unperturbed states scale efforts key properties systematically describe remains challenging recent genome recapitulate features perturbation data new approach molecular perturbations modular organization efficient manner deeper analysis |