[1]
B. Bach, E. Pietriga, and J. -D. Fekete. Graphdiaries: Animated transitions and temporal navigation for dynamic networks. IEEE Transactions on Visualization Computer Graphics, 20(5): 740- 754, (2014).
DOI: 10.1109/tvcg.2013.254
Google Scholar
[2]
L. Borisjuk, M. Hajirezaei, C. Klukas, H. Rolletschek, and F. Schreiber. Integrating data from biological experiments into metabolic networks with the DBE information system. In Silico Biology, 5(2): 93-102, (2004).
Google Scholar
[3]
I. Boyandin, E. Bertini, and D. Lalanne. A qualitative study on the exploration of temporal changes in flow maps with animation and small-multiples. Computer Graphics Forum, 31(3pt2): 1005-1014, (2012).
DOI: 10.1111/j.1467-8659.2012.03093.x
Google Scholar
[4]
U. Brandes and S. R. Corman. Visual unrolling of network evolution and the analysis of dynamic discourse. Information Visualization, 2(1): 40-50, (2003).
DOI: 10.1057/palgrave.ivs.9500037
Google Scholar
[5]
U. Brandes, S. Cornelsen, and D. Wagner. How to Draw the Minimum Cuts of a Planar Graph, pages 89-119. Springer Berlin Heidelberg, (2001).
DOI: 10.1007/3-540-44541-2_10
Google Scholar
[6]
N. Cesario, A. Pang, and L. Singh. Visualizing node attribute uncertainty in graphs. Proc. SPIE, 7868: 78680H-78680H-13, (2011).
DOI: 10.1117/12.872677
Google Scholar
[7]
J. Edmonds and R. M. Karp. Theoretical improvements in algorithmic efficiency for network flow problems. J. ACM, 19(2): 248-264, (1972).
DOI: 10.1145/321694.321699
Google Scholar
[8]
P. Elias, A. Feinstein, and C. Shannon. A note on the maximum flow through a network. Information Theory, IEEE Transactions on, 2(4): 117-119, (1956).
DOI: 10.1109/tit.1956.1056816
Google Scholar
[9]
L. R. Ford and D. R. Fulkerson. Maximal Flow through a Network. Canadian Journal of Mathematics, 8: 399-404, (1956).
DOI: 10.4153/cjm-1956-045-5
Google Scholar
[10]
S. Fortune. Voronoi diagrams and delaunay triangulations. In J. E. Goodman and J. O'Rourke, editors, Handbook of Discrete and Computational Geometry, pages 377-388. CRC Press, Inc., (1997).
DOI: 10.1201/9781420035315.ch23
Google Scholar
[11]
S. Hadlak, H. Schumann, and H. -J. Schulz. A Survey of Multi-faceted Graph Visualization. In R. Borgo, F. Ganovelli, and I. Viola, editors, Eurographics Conference on Visualization (EuroVis) - STARs. The Eurographics Association, (2015).
Google Scholar
[12]
S. Halim. https: /visualgo. net/maxflow. online, (2017).
Google Scholar
[13]
M. Itoh, D. Yokoyama, M. Toyoda, Y. Tomita, S. Kawamura, and M. Kitsuregawa. Visual exploration of changes in passenger flows and tweets on mega-city metro network. IEEE Transactions on Big Data, 2(1): 85-99, March (2016).
DOI: 10.1109/tbdata.2016.2546301
Google Scholar
[14]
J. Jaffe. Bottleneck flow control. IEEE Transactions on Communications, 29(7): 954-962, (1981).
DOI: 10.1109/tcom.1981.1095081
Google Scholar
[15]
M. Kikolski. Identification of production bottlenecks with the use of plant simulation software. Ekonomia i Zarzadzanie, 8(4): 103-112, (2017).
DOI: 10.1515/emj-2016-0038
Google Scholar
[16]
S. Klamt, J. Saez-Rodriguez, and E. D. Gilles. Structural and functional analysis of cellular networks with cellnetanalyzer. BMC Systems Biology, 1: open access, (2007).
DOI: 10.1186/1752-0509-1-2
Google Scholar
[17]
S. Klamt and A. von Kamp. An application programming interface for cellnetanalyzer. BioSystems, 105: 162-168, (2011).
DOI: 10.1016/j.biosystems.2011.02.002
Google Scholar
[18]
C. G. Lee and S. C. Park. Survey on the virtual commissioning of manufacturing systems. Journal of Computational Design and Engineering, 1(3): 213 - 222, (2014).
Google Scholar
[19]
C. Vehlow, F. Beck, and D. Weiskopf. Visualizing group structures in graphs: A survey. Computer Graphics Forum, pages n/a-n/a, (2016).
DOI: 10.1111/cgf.12872
Google Scholar
[20]
H. Yu, P. M. Kim, E. Sprecher, V. Trifonov, and M. Gerstein. The importance of bottlenecks in protein networks: Correlation with gene essentiality and expression dynamics. PLoS Computational Biology, 3(4), (2007).
DOI: 10.1371/journal.pcbi.0030059
Google Scholar