20.500.12556/RUL-139693 Review and assessment of Boolean approaches for inference of gene regulatory networks Boolean descriptions of gene regulatory networks can provide an insight into interactions between genes. Boolean networks hold predictive power, are easy to understand, and can be used to simulate the observed networks in different scenarios. We review fundamental and state-of-the-art methods for inference of Boolean networks. We introduce a methodology for a straightforward evaluation of Boolean inference approaches based on the generation of evaluation datasets, application of selected inference methods, and evaluation of performance measures to guide the selection of the best method for a given inference problem. We demonstrate this procedure on inference methods REVEAL (REVerse Engineering ALgorithm), Best-Fit Extension, MIBNI (Mutual Informationbased Boolean Network Inference), GABNI (Genetic Algorithm-based Boolean Network Inference) and ATEN (AND/OR Tree ENsemble algorithm), which infers Boolean descriptions of gene regulatory networks from discretised time series data. Boolean inference approaches tend to perform better in terms of dynamic accuracy, and slightly worse in terms of structural correctness. We believe that the proposed methodology and provided guidelines will help researchers to develop Boolean inference approaches with a good predictive capability while maintaining structural correctness and biological relevance. Boolean network inference gene regulatory networks static validation dynamic validation systems biology inferenca Boolovih mrež gensko regulatorna omrežja statična validacija dinamična validacija sistemska biologija true false true Angleški jezik Slovenski jezik Članek v reviji 2022-09-06 12:06:07 2022-09-06 12:06:07 2022-09-16 04:11:40 0000-00-00 00:00:00 2022 0 0 15 str. iss. 8, art. e10222 Vol. 8 2022 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 004:575.112 2405-8440 10.1016/j.heliyon.2022.e10222 117893635 1-s2.0-S2405844022015109-main.pdf 1-s2.0-S2405844022015109-main.pdf 1 67328B0F232C4EC04D534E7B6A1632DF d9899c0cee87e76b42427e5159010c6638c9dfb09a7975bfb0f0babf3b64465c d1c05074-2dcb-11ed-92af-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=160296 https://www.sciencedirect.com/science/article/pii/S2405844022015109 0 a0387379-2dcb-11ed-92af-00155dcfd717 https://repozitorij.uni-lj.si/Dokument.php?lang=slv&id=160295 Fakulteta za računalništvo in informatiko 0 0 0