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SAILoR : structure-aware inference of logic rules
ID Pušnik, Žiga (Avtor), ID Mraz, Miha (Avtor), ID Zimic, Nikolaj (Avtor), ID Moškon, Miha (Avtor)

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Izvleček
Boolean networks provide an effective mechanism for describing interactions and dynamics of gene regulatory networks (GRNs). Deriving accurate Boolean descriptions of GRNs is a challenging task. The number of experiments is usually much smaller than the number of genes. In addition, binarization leads to a loss of information and inconsistencies arise in binarized time-series data. The inference of Boolean networks from binarized time-series data alone often leads to complex and overfitted models. To obtain relevant Boolean models of gene regulatory networks, inference methods could incorporate data from multiple sources and prior knowledge in terms of general network structure and/or exact interactions. We propose the Boolean network inference method SAILoR (Structure-Aware Inference of Logic Rules). SAILoR incorporates time-series gene expression data in combination with provided reference networks to infer accurate Boolean models. SAILoR automatically extracts topological properties from reference networks. These can describe a more general structure of the GRN or can be more precise and describe specific interactions. SAILoR infers a Boolean network by learning from both continuous and binarized time-series data. It navigates between two main objectives, topological similarity to reference networks and correspondence with gene expression data. By incorporating the NSGA-II multi-objective genetic algorithm, SAILoR relies on the wisdom of crowds. Our results indicate that SAILoR can infer accurate and biologically relevant Boolean descriptions of GRNs from both a static and a dynamic perspective. We show that SAILoR improves the static accuracy of the inferred network compared to the network inference method dynGENIE3. Furthermore, we compared the performance of SAILoR with other Boolean network inference approaches including Best-Fit, REVEAL, MIBNI, GABNI, ATEN, and LogBTF. We have shown that by incorporating prior knowledge about the overall network structure, SAILoR can improve the structural correctness of the inferred Boolean networks while maintaining dynamic accuracy. To demonstrate the applicability of SAILoR, we inferred context-specific Boolean subnetworks of female Drosophila melanogaster before and after mating.

Jezik:Angleški jezik
Ključne besede:Boolean network inference, context-specific gene regulatory networks, prior knowledge integration, multi-objective optimization
Vrsta gradiva:Članek v reviji
Tipologija:1.01 - Izvirni znanstveni članek
Organizacija:FRI - Fakulteta za računalništvo in informatiko
Status publikacije:Objavljeno
Različica publikacije:Objavljena publikacija
Leto izida:2024
Št. strani:29 str.
Številčenje:Vol. 19, iss. 6, art. e0304102
PID:20.500.12556/RUL-158454 Povezava se odpre v novem oknu
UDK:004:575.112
ISSN pri članku:1932-6203
DOI:10.1371/journal.pone.0304102 Povezava se odpre v novem oknu
COBISS.SI-ID:198615043 Povezava se odpre v novem oknu
Datum objave v RUL:13.06.2024
Število ogledov:76
Število prenosov:18
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Gradivo je del revije

Naslov:PloS one
Založnik:Public Library of Science
ISSN:1932-6203
COBISS.SI-ID:2005896 Povezava se odpre v novem oknu

Licence

Licenca:CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
Povezava:http://creativecommons.org/licenses/by/4.0/deed.sl
Opis:To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

Jezik:Slovenski jezik
Ključne besede:inferenca Boolovih omrežij, kontekstno specifična gensko regulatorna omrežja, integracija predhodnega znanja, večkriterijska optimizacija

Projekti

Financer:ARIS - Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije
Številka projekta:P2-0359
Naslov:Vseprisotno računalništvo

Financer:ARIS - Javna agencija za znanstvenoraziskovalno in inovacijsko dejavnost Republike Slovenije
Številka projekta:J1-50024
Naslov:Povezava med hipoksijo in sintezo holesterola v cirkadianem času

Financer:Drugi - Drug financer ali več financerjev
Program financ.:ELIXIR-SI RI-SI-2

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