Controlling gene regulatory networks with FQI-SARSA

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dc.contributor.advisorOrcidhttps://orcid.org/0000-0001-9097-827X
dc.contributor.authorNISHIDA, C. E. H.
dc.contributor.authorCOSTA, A. H. R.
dc.contributor.authorReinaldo Bianchi
dc.date.accessioned2023-06-01T06:26:10Z
dc.date.available2023-06-01T06:26:10Z
dc.date.issued2017-06-28
dc.description.abstract© 2017 IEEE.External control of a gene regulatory network model can help accelerate the design of treatments to make it avoid diseased states. However, inferring this model and then controlling it has a exponential complexity of time and space, making large networks inviable for model dependent approaches. This is visible in the literature as only models with at most dozens of genes could be used in control problems. We propose to apply a batch reinforcement learning method Fitted Q-Iteration Sarsa for controlling partially observable gene regulatory networks directly from data, with a new reward function and a way to create experience tuples from gene expression samples. Our framework produces approximate stochastic policies without restricting it to time series samples, allowing it to freely manage the experience tuples. Results demonstrate that our method is more effective than previous studies, with a higher shifting between undesirable to desirable states and higher expected reward.
dc.description.firstpage216
dc.description.lastpage221
dc.description.volume2018-January
dc.identifier.citationNISHIDA, C. E. H.; COSTA, A. H. R. Controlling gene regulatory networks with FQI-SARSA. Proceedings - 2017 Brazilian Conference on Intelligent Systems, BRACIS 2017, v. 2018-January, p. 216-221, 2017.
dc.identifier.doi10.1109/BRACIS.2017.81
dc.identifier.urihttps://repositorio.fei.edu.br/handle/FEI/4835
dc.relation.ispartofProceedings - 2017 Brazilian Conference on Intelligent Systems, BRACIS 2017
dc.rightsAcesso Restrito
dc.subject.otherlanguageGene Network control
dc.subject.otherlanguageMarkov Decision Process
dc.subject.otherlanguageReinforcement Learning
dc.titleControlling gene regulatory networks with FQI-SARSA
dc.typeArtigo de evento
fei.scopus.citations3
fei.scopus.eid2-s2.0-85049516747
fei.scopus.subjectBatch reinforcement learning
fei.scopus.subjectExponential complexity
fei.scopus.subjectExternal control
fei.scopus.subjectGene networks
fei.scopus.subjectGene regulatory network model
fei.scopus.subjectGene regulatory networks
fei.scopus.subjectMarkov Decision Processes
fei.scopus.subjectStochastic policy
fei.scopus.updated2024-07-01
fei.scopus.urlhttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85049516747&origin=inward
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