dossier-complet/bib/sivanov-extra.bib

91 lines
5.2 KiB
BibTeX
Raw Permalink Blame History

This file contains ambiguous Unicode characters

This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.

@inbook{NushiPSMICP2022,
author = {Nushi, Elio and Popescu, Victor-Bogdan and Sanchez Martin, Jose-Angel and Ivanov, Sergiu and Czeizler, Eugen and Petre, Ion},
publisher = {John Wiley \& Sons, Ltd},
isbn = {9781119716600},
title = {Network Modelling Methods for Precision Medicine},
booktitle = {Systems Biology Modelling and Analysis},
chapter = {10},
pages = {363-423},
doi = {https://doi.org/10.1002/9781119716600.ch10},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/9781119716600.ch10},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/9781119716600.ch10},
year = {2022},
keywords = {network medicine, computational modelling, precision medicine, drug repurposing, centrality measures, systems controllability, graph theory.},
abstract = {Summary We discuss in this chapter several network modelling methods and their applicability to precision medicine. We review several network centrality methods (degree centrality, closeness centrality, eccentricity centrality, betweenness centrality, and eigenvector-based prestige) and two systems controllability methods (minimum dominating sets and network structural controllability). We demonstrate their applicability to precision medicine on three multiple myeloma patient disease networks. Each network consists of proteinprotein interactions (PPI) built around a specific patient's mutated genes, around the targets of the drugs used in the standard of care in multiple myeloma, and around multiple myeloma-specific essential genes. For each network, we demonstrate how the network methods we discuss can be used to identify personalized, targeted drug combinations uniquely suited to that patient.}
}
@techreport{AlhazovFI2016,
author={Artiom Alhazov and Rudolf Freund and Sergiu Ivanov},
title={Polymorphic P Systems: A Survey},
booktitle={Bulletin of the International Membrane Computing Society},
pages={79--101},
publisher={IMCS},
volume={Number 2},
year={December 2016}
}
@article {Segretain2020.10.02.323949,
author = {Segretain, R{\'e}mi and Ivanov, Sergiu and Trilling, Laurent and Glade, Nicolas},
title = {Implementation of a Computing Pipeline for Evaluating the Extensibility of Boolean Networks{\textquoteright} Structure and Function},
elocation-id = {2020.10.02.323949},
year = {2020},
doi = {10.1101/2020.10.02.323949},
publisher = {Cold Spring Harbor Laboratory},
abstract = {Formal interaction networks are well suited for representing complex biological systems and have been used to model signalling pathways, gene regulatory networks, interaction within ecosystems, etc. In this paper, we introduce Sign Boolean Networks (SBNs), which are a uniform variant of Threshold Boolean Networks (TBFs). We continue the study of the complexity of SBNs and build a new framework for evaluating their ability to extend, i.e. the potential to gain new functions by addition of nodes, while also maintaining the original functions. We describe our software implementation of this framework and show some first results. These results seem to confirm the conjecture that networks of moderate complexity are the most able to grow, because they are not too simple, but also not too constrained, like the highly complex ones. Biological Regulation, Biological Networks, Sign Boolean Networks, Complexity, Extensibility, Network GrowthCompeting Interest StatementThe authors have declared no competing interest.},
URL = {https://www.biorxiv.org/content/early/2020/10/05/2020.10.02.323949},
eprint = {https://www.biorxiv.org/content/early/2020/10/05/2020.10.02.323949.full.pdf},
journal = {bioRxiv}
}
@article{C:AB20,
author = {Urvan Christen and
Sergiu Ivanov and
Rémi Segretain and
Laurent Trilling and
Nicolas Glade},
title = {On Computing Structural and Behavioral Complexities of Threshold Boolean Networks},
journal = {Acta Biotheoretica},
volume = {68},
pages = {119--138},
year = {2020}
}
@techreport{AGIMPP2014,
title = {Complexity of Model Checking for Reaction Systems},
author = {Azimi, Sepinoud and Gratie, Cristian and Ivanov, Sergiu and Manzoni, Luca and Petre, Ion and Porreca, Antonio E.},
number = {1122},
series = {TUCS Technical Reports},
publisher = {TUCS},
year = {2014},
}
@techreport{AGIP2014,
title = {Dependency Graphs and Mass Conservation in Reaction Systems},
author = {Azimi, Sepinoud and Gratie, Cristian and Ivanov, Sergiu and Petre, Ion},
number = {1123},
series = {TUCS Technical Reports},
publisher = {TUCS},
year = {2014},
keywords = {Reaction system; model checking; mass conservation; conserved set; conservation dependency graph; simulator},
ISBN = {978-952-12-3123-0},
}
@article{IvanovMarcus2015,
Title = {On the Lower Bounds for Leftist Insertion-Deletion Languages},
Author = {Sergiu Ivanov and Sergey Verlan},
Journal = {Annals of the University of Bucharest (Informatics)},
Volume = {LXII(2)},
Pages = {77--88},
Year = {2015}
}
@article{AlhazovFIO2015,
title = {Observations on {P} Systems with States},
author = {Artiom Alhazov and Rudolf Freund and Sergiu Ivanov and Marion Oswald},
pages = {17--28},
journaltitle = {Multidisciplinary Creativity},
editors = {Marian Gheorghe and Ion Petre and Mario J. P\'erez-Jim\'enez and Grzegorz Rozenberg and Arto Salomaa},
year = {2015},
publisher = {Editura Spandugino}
}