BROWSE

ITEM VIEW & DOWNLOAD

A general model-based causal inference method overcomes the curse of synchrony and indirect effect

DC Field Value Language
dc.contributor.authorSe Ho Park-
dc.contributor.authorSeokmin Ha-
dc.contributor.authorJae Kyoung Kim-
dc.date.accessioned2023-09-04T22:01:02Z-
dc.date.available2023-09-04T22:01:02Z-
dc.date.created2023-08-02-
dc.date.issued2023-07-
dc.identifier.issn2041-1723-
dc.identifier.urihttps://pr.ibs.re.kr/handle/8788114/13874-
dc.description.abstractTo identify causation, model-free inference methods, such as Granger Causality, have been widely used due to their flexibility. However, they have difficulty distinguishing synchrony and indirect effects from direct causation, leading to false predictions. To overcome this, model-based inference methods that test the reproducibility of data with a specific mechanistic model to infer causality were developed. However, they can only be applied to systems described by a specific model, greatly limiting their applicability. Here, we address this limitation by deriving an easily testable condition for a general monotonic ODE model to reproduce time-series data. We built a user-friendly computational package, General ODE-Based Inference (GOBI), which is applicable to nearly any monotonic system with positive and negative regulations described by ODE. GOBI successfully inferred positive and negative regulations in various networks at both the molecular and population levels, unlike existing model-free methods. Thus, this accurate and broadly applicable inference method is a powerful tool for understanding complex dynamical systems. © 2023, The Author(s).-
dc.language영어-
dc.publisherNature Research-
dc.titleA general model-based causal inference method overcomes the curse of synchrony and indirect effect-
dc.typeArticle-
dc.type.rimsART-
dc.identifier.wosid001036000300007-
dc.identifier.scopusid2-s2.0-85165538783-
dc.identifier.rimsid81360-
dc.contributor.affiliatedAuthorSe Ho Park-
dc.contributor.affiliatedAuthorSeokmin Ha-
dc.contributor.affiliatedAuthorJae Kyoung Kim-
dc.identifier.doi10.1038/s41467-023-39983-4-
dc.identifier.bibliographicCitationNature Communications, v.14, no.1-
dc.relation.isPartOfNature Communications-
dc.citation.titleNature Communications-
dc.citation.volume14-
dc.citation.number1-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.journalClass1-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaScience & Technology - Other Topics-
dc.relation.journalWebOfScienceCategoryMultidisciplinary Sciences-
dc.subject.keywordPlusHOSPITAL ADMISSIONS-
dc.subject.keywordPlusGRANGER CAUSALITY-
dc.subject.keywordPlusAIR-POLLUTION-
dc.subject.keywordPlusOSCILLATIONS-
dc.subject.keywordPlusSYSTEMS-
Appears in Collections:
Pioneer Research Center for Mathematical and Computational Sciences(수리 및 계산과학 연구단) > Biomedical Mathematics Group(의생명 수학 그룹) > 1. Journal Papers (저널논문)
Pioneer Research Center for Mathematical and Computational Sciences(수리 및 계산과학 연구단) > 1. Journal Papers (저널논문)
Files in This Item:
There are no files associated with this item.

qrcode

  • facebook

    twitter

  • Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.
해당 아이템을 이메일로 공유하기 원하시면 인증을 거치시기 바랍니다.

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.

Browse