CELLoGeNe - An energy landscape framework for logical networks controlling cell decisions

Experimental and computational efforts are constantly made to elucidate mechanisms controlling cell fate decisions during development and reprogramming. One powerful computational method is to consider cell commitment and reprogramming as movements in an energy landscape. Here, we develop Computatio...

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Bibliographic Details
Published in:iScience 2022-08, Vol.25 (8), p.104743-104743, Article 104743
Main Authors: Andersson, Emil, Sjö, Mattias, Kaji, Keisuke, Olariu, Victor
Format: Article
Language:English
Subjects:
Bioinformatics
Bioinformatics (Computational Biology)
Bioinformatik (beräkningsbiologi)
Biologi
Biological Sciences
Cell Biology
Cellbiologi
Computer and Information Science
Data- och informationsvetenskap (Datateknik)
Mathematical biosciences
Natural Sciences
Naturvetenskap
Stem cells research
Systems biology
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Summary:Experimental and computational efforts are constantly made to elucidate mechanisms controlling cell fate decisions during development and reprogramming. One powerful computational method is to consider cell commitment and reprogramming as movements in an energy landscape. Here, we develop Computation of Energy Landscapes of Logical Gene Networks (CELLoGeNe), which maps Boolean implementation of gene regulatory networks (GRNs) into energy landscapes. CELLoGeNe removes inadvertent symmetries in the energy landscapes normally arising from standard Boolean operators. Furthermore, CELLoGeNe provides tools to visualize and stochastically analyze the shapes of multi-dimensional energy landscapes corresponding to epigenetic landscapes for development and reprogramming. We demonstrate CELLoGeNe on two GRNs governing different aspects of induced pluripotent stem cells, identifying experimentally validated attractors and revealing potential reprogramming roadblocks. CELLoGeNe is a general framework that can be applied to various biological systems offering a broad picture of intracellular dynamics otherwise inaccessible with existing methods. [Display omitted] •CELLoGeNe – Computation of Energy Landscapes of Logical Gene Networks•Cell states as landscape attractors•Maintenance and acquisition of cell pluripotency applications•Single cell stochastic landscape navigation and visualization tool Cell biology; Stem cells research; Bioinformatics; Mathematical biosciences; Systems biology
ISSN:2589-0042
2589-0042
DOI:10.1016/j.isci.2022.104743