This repository contains the code for the paper:

  Prasse, B. and P. Van Mieghem, 2022, "Predicting network dynamics without requiring the knowledge of the interaction graph", 
  Proceedings of the National Academy of Sciences (PNAS), Vol. 119, No. 44, e2205517119. (DOI pnas.2205517119)

The main functionality of this code is to reproduce the figures in the paper. Hence, instead of a single main file, there are multiple
Fig_*.mat files which can be run directly to reproduce the corresponding figure(s) in the paper. Please see my comments in the code
for more information.

A good starting point could be to run and inspect the output of:

Fig_3_S5_S6_S7_S8( 1, 100, 200 )

The first argument is the random seed=1, the second argument specifies N=100 nodes, and the third arguments specifies n=200 observations.

Version 1.0, 1 October 2022

COPYRIGHT (c) 2022 Bastian Prasse

Permission to use, copy, modify, and distribute this software for any purpose without fee is hereby granted, provided that this entire
notice is included in all copies of any software which is or includes a copy or modification of this software and in all copies of the
supporting documentation for such software. This software is being provided "as is", without any express or implied warranty. In 
particular, the authors do not make any representation or warranty of any kind concerning the merchantability of this software or its 
fitness for any particular purpose.

Over and above the legal restrictions imposed by this license, if you use this software for an academic publication then you are obliged 
to provide proper attribution to the corresponding paper 

  Prasse, B. and P. Van Mieghem, 2022, "Predicting network dynamics without requiring the knowledge of the interaction graph", 
  Proceedings of the National Academy of Sciences (PNAS), Vol. 119, No. 44, e2205517119. (DOI pnas.2205517119)

and (ideally) also to this code directly,

  B. Prasse. Predicting network dynamics without the graph, v1.0 (2022). github.com/bprasse/Predicting-network-dynamics-without-the-graph/ 
 
Furthermore, if you make use of the empirical networks, then you are obliged to provide proper attribution by referring to the corresponding 
publications which are stated below. All of the networks were accessed via the Konect network collection:
 
@inproceedings{kunegis2013konect,
  title={Konect: the {K}oblenz network collection},
  author={Kunegis, J{\'e}r{\^o}me},
  booktitle={Proceedings of the 22nd International Conference on World Wide Web},
  pages={1343--1350},
  year={2013},
  organization={ACM}
}

For the Lotka-Volterra dynamics, we considered the Little Rock Lake network:

@article{martinez1991artifacts,
  title={Artifacts or attributes? {E}ffects of resolution on the {L}ittle {R}ock {L}ake food web},
  author={Martinez, Neo D},
  journal={Ecological monographs},
  volume={61},
  number={4},
  pages={367--392},
  year={1991},
  publisher={Wiley Online Library}
}

For the mutualistic population dynamics, we considered the insect-flower network:

@article{kato1990insect,
  title={Insect-flower relationship in the primary beech forest of Ashu, Kyoto: an overview of the flowering phenology and the seasonal pattern of insect visits},
  author={Kato, Makoto and Kakutani, Takehiko and Inoue, Tamiji and Itino, Takao},
  year={1990},
  publisher={Contributions from the Biological Laboratory, Kyoto University (1990), 27: 309-375}
}
@article{rezende2007non,
  title={Non-random coextinctions in phylogenetically structured mutualistic networks},
  author={Rezende, Enrico L and Lavabre, Jessica E and Guimar{\~a}es, Paulo R and Jordano, Pedro and Bascompte, Jordi},
  journal={Nature},
  volume={448},
  number={7156},
  pages={925},
  year={2007},
  publisher={Nature Publishing Group}
}

For the Michaelis-Menten dynamics, we considered the S. Cerevisiae yeast network:

@article{milo2002network,
  title={Network motifs: simple building blocks of complex networks},
  author={Milo, Ron and Shen-Orr, Shai and Itzkovitz, Shalev and Kashtan, Nadav and Chklovskii, Dmitri and Alon, Uri},
  journal={Science},
  volume={298},
  number={5594},
  pages={824--827},
  year={2002},
  publisher={American Association for the Advancement of Science}
}

For the SIS dynamics, we considered the 'Infectious: Stay Away' network:

@article{isella2011s,
  title={What's in a crowd? {A}nalysis of face-to-face behavioral networks},
  author={Isella, Lorenzo and Stehl{\'e}, Juliette and Barrat, Alain and Cattuto, Ciro and Pinton, Jean-Fran{\c{c}}ois and Van den Broeck, Wouter},
  journal={Journal of Theoretical Biology},
  volume={271},
  number={1},
  pages={166--180},
  year={2011},
  publisher={Elsevier}
}

For the Wilson-Cowan neural firing dynamics, we considered the C. Elegans network:
  
@article{white1986structure,
  title={The structure of the nervous system of the nematode {C}aenorhabditis elegans},
  author={White, John G and Southgate, Eileen and Thomson, J Nichol and Brenner, Sydney},
  journal={Philos Trans R Soc Lond B Biol Sci},
  volume={314},
  number={1165},
  pages={1--340},
  year={1986}
}
@article{chen2006wiring,
  title={Wiring optimization can relate neuronal structure and function},
  author={Chen, Beth L and Hall, David H and Chklovskii, Dmitri B},
  journal={Proceedings of the National Academy of Sciences},
  volume={103},
  number={12},
  pages={4723--4728},
  year={2006},
  publisher={National Acad Sciences}
}