Year |
Citation |
Score |
2024 |
Molnár F, Horvát S, Ribeiro Gomes AR, Martinez Armas J, Molnár B, Ercsey-Ravasz M, Knoblauch K, Kennedy H, Toroczkai Z. Predictability of cortico-cortical connections in the mammalian brain. Network Neuroscience (Cambridge, Mass.). 8: 138-157. PMID 38562298 DOI: 10.1162/netn_a_00345 |
0.355 |
|
2024 |
Malik O, Varga M, Moussawi A, Hunt D, Szymanski BK, Toroczkai Z, Korniss G. Diffusive persistence on disordered lattices and random networks. Physical Review. E. 109: 024113. PMID 38491611 DOI: 10.1103/PhysRevE.109.024113 |
0.32 |
|
2023 |
Barabási DL, Bianconi G, Bullmore E, Burgess M, Chung S, Eliassi-Rad T, George D, Kovács IA, Makse H, Nichols TE, Papadimitriou C, Sporns O, Stachenfeld K, Toroczkai Z, Towlson EK, et al. Neuroscience Needs Network Science. The Journal of Neuroscience : the Official Journal of the Society For Neuroscience. 43: 5989-5995. PMID 37612141 DOI: 10.1523/JNEUROSCI.1014-23.2023 |
0.788 |
|
2023 |
Barabási DL, Bianconi G, Bullmore E, Burgess M, Chung S, Eliassi-Rad T, George D, Kovács IA, Makse H, Papadimitriou C, Nichols TE, Sporns O, Stachenfeld K, Toroczkai Z, Towlson EK, et al. Neuroscience needs Network Science. Arxiv. PMID 37214134 |
0.795 |
|
2018 |
Gămănuţ R, Kennedy H, Toroczkai Z, Ercsey-Ravasz M, Van Essen DC, Knoblauch K, Burkhalter A. The Mouse Cortical Connectome, Characterized by an Ultra-Dense Cortical Graph, Maintains Specificity by Distinct Connectivity Profiles. Neuron. 97: 698-715.e10. PMID 29420935 DOI: 10.1016/J.Neuron.2017.12.037 |
0.735 |
|
2018 |
Erdős PL, Miklós I, Toroczkai Z. New Classes of Degree Sequences with Fast Mixing Swap Markov Chain Sampling Combinatorics, Probability & Computing. 27: 186-207. DOI: 10.1017/S0963548317000499 |
0.361 |
|
2017 |
Noori HR, Schöttler J, Ercsey-Ravasz M, Cosa-Linan A, Varga M, Toroczkai Z, Spanagel R. A multiscale cerebral neurochemical connectome of the rat brain. Plos Biology. 15: e2002612. PMID 28671956 DOI: 10.1371/Journal.Pbio.2002612 |
0.338 |
|
2017 |
Toroczkai Z. Network ScienceNetwork Science, Albert-László Barabási, Cambridge U. Press, 2016, 456 p, $59.99, ISBN 978-1-107-07626-6 Physics Today. 70: 55-56. DOI: 10.1063/Pt.3.3526 |
0.387 |
|
2016 |
Horvát S, Gămănuț R, Ercsey-Ravasz M, Magrou L, Gămănuț B, Van Essen DC, Burkhalter A, Knoblauch K, Toroczkai Z, Kennedy H. Spatial Embedding and Wiring Cost Constrain the Functional Layout of the Cortical Network of Rodents and Primates. Plos Biology. 14: e1002512. PMID 27441598 DOI: 10.1371/Journal.Pbio.1002512 |
0.771 |
|
2015 |
Orsini C, Dankulov MM, Colomer-de-Simón P, Jamakovic A, Mahadevan P, Vahdat A, Bassler KE, Toroczkai Z, Boguñá M, Caldarelli G, Fortunato S, Krioukov D. Quantifying randomness in real networks. Nature Communications. 6: 8627. PMID 26482121 DOI: 10.1038/Ncomms9627 |
0.707 |
|
2015 |
Horvát S, Czabarka É, Toroczkai Z. Reducing degeneracy in maximum entropy models of networks. Physical Review Letters. 114: 158701. PMID 25933345 DOI: 10.1103/Physrevlett.114.158701 |
0.415 |
|
2015 |
Erdos PL, Miklós I, Toroczkai Z. A decomposition based proof for fast mixing of a Markov chain over balanced realizations of a joint degree matrix Siam Journal On Discrete Mathematics. 29: 481-499. DOI: 10.1137/130929874 |
0.322 |
|
2015 |
Bassler KE, Genio CID, Erds PL, Miklós I, Toroczkai Z. Exact sampling of graphs with prescribed degree correlations New Journal of Physics. 17. DOI: 10.1088/1367-2630/17/8/083052 |
0.649 |
|
2014 |
Ren Y, Ercsey-Ravasz M, Wang P, González MC, Toroczkai Z. Predicting commuter flows in spatial networks using a radiation model based on temporal ranges. Nature Communications. 5: 5347. PMID 25373437 DOI: 10.1038/Ncomms6347 |
0.436 |
|
2014 |
Markov NT, Ercsey-Ravasz MM, Ribeiro Gomes AR, Lamy C, Magrou L, Vezoli J, Misery P, Falchier A, Quilodran R, Gariel MA, Sallet J, Gamanut R, Huissoud C, Clavagnier S, Giroud P, ... ... Toroczkai Z, et al. A weighted and directed interareal connectivity matrix for macaque cerebral cortex. Cerebral Cortex (New York, N.Y. : 1991). 24: 17-36. PMID 23010748 DOI: 10.1093/Cercor/Bhs270 |
0.37 |
|
2013 |
Markov NT, Ercsey-Ravasz M, Van Essen DC, Knoblauch K, Toroczkai Z, Kennedy H. Cortical high-density counterstream architectures. Science (New York, N.Y.). 342: 1238406. PMID 24179228 DOI: 10.1126/Science.1238406 |
0.427 |
|
2013 |
Ercsey-Ravasz M, Markov NT, Lamy C, Van Essen DC, Knoblauch K, Toroczkai Z, Kennedy H. A predictive network model of cerebral cortical connectivity based on a distance rule. Neuron. 80: 184-97. PMID 24094111 DOI: 10.1016/J.Neuron.2013.07.036 |
0.541 |
|
2013 |
Kennedy H, Knoblauch K, Toroczkai Z. Why data coherence and quality is critical for understanding interareal cortical networks. Neuroimage. 80: 37-45. PMID 23603347 DOI: 10.1016/J.Neuroimage.2013.04.031 |
0.441 |
|
2013 |
Markov NT, Ercsey-Ravasz M, Lamy C, Ribeiro Gomes AR, Magrou L, Misery P, Giroud P, Barone P, Dehay C, Toroczkai Z, Knoblauch K, Van Essen DC, Kennedy H. The role of long-range connections on the specificity of the macaque interareal cortical network. Proceedings of the National Academy of Sciences of the United States of America. 110: 5187-92. PMID 23479610 DOI: 10.1073/Pnas.1218972110 |
0.422 |
|
2013 |
WANG C, LIZARDO O, HACHEN D, STRATHMAN A, TOROCZKAI Z, CHAWLA NV. A dyadic reciprocity index for repeated interaction networks Network Science. 1: 31-48. DOI: 10.1017/Nws.2012.5 |
0.651 |
|
2012 |
Ercsey-Ravasz M, Lichtenwalter RN, Chawla NV, Toroczkai Z. Range-limited centrality measures in complex networks. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 85: 066103. PMID 23005158 DOI: 10.1103/Physreve.85.066103 |
0.483 |
|
2012 |
Ercsey-Ravasz M, Toroczkai Z, Lakner Z, Baranyi J. Complexity of the international agro-food trade network and its impact on food safety. Plos One. 7: e37810. PMID 22701535 DOI: 10.1371/Journal.Pone.0037810 |
0.337 |
|
2012 |
Kim H, Del Genio CI, Bassler KE, Toroczkai Z. Constructing and sampling directed graphs with given degree sequences New Journal of Physics. 14. DOI: 10.1088/1367-2630/14/2/023012 |
0.693 |
|
2011 |
Markov NT, Misery P, Falchier A, Lamy C, Vezoli J, Quilodran R, Gariel MA, Giroud P, Ercsey-Ravasz M, Pilaz LJ, Huissoud C, Barone P, Dehay C, Toroczkai Z, Van Essen DC, et al. Weight consistency specifies regularities of macaque cortical networks. Cerebral Cortex (New York, N.Y. : 1991). 21: 1254-72. PMID 21045004 DOI: 10.1093/Cercor/Bhq201 |
0.408 |
|
2010 |
Ercsey-Ravasz M, Toroczkai Z. Centrality scaling in large networks. Physical Review Letters. 105: 038701. PMID 20867816 DOI: 10.1103/Physrevlett.105.038701 |
0.474 |
|
2010 |
Del Genio CI, Kim H, Toroczkai Z, Bassler KE. Efficient and exact sampling of simple graphs with given arbitrary degree sequence. Plos One. 5: e10012. PMID 20386694 DOI: 10.1371/Journal.Pone.0010012 |
0.701 |
|
2010 |
Erdős PL, Miklós I, Toroczkai Z. A simple Havel-Hakimi type algorithm to realize graphical degree sequences of directed graphs ∗ Electronic Journal of Combinatorics. 17: 66. DOI: 10.37236/338 |
0.305 |
|
2010 |
Asztalos A, Toroczkai Z. Network discovery by generalized random walks Epl (Europhysics Letters). 92: 50008. DOI: 10.1209/0295-5075/92/50008 |
0.459 |
|
2009 |
Kim H, Toroczkai Z, Erdős PL, Miklós I, Székely LA. Degree-based graph construction Journal of Physics a: Mathematical and Theoretical. 42: 392001. DOI: 10.1088/1751-8113/42/39/392001 |
0.581 |
|
2008 |
Piontti ALPy, Rocca CEL, Toroczkai Z, Braunstein LA, Macri PA, López E. Using relaxational dynamics to reduce network congestion New Journal of Physics. 10: 93007. DOI: 10.1088/1367-2630/10/9/093007 |
0.452 |
|
2007 |
Motter AE, Toroczkai Z. Introduction: optimization in networks. Chaos (Woodbury, N.Y.). 17: 026101. PMID 17614688 DOI: 10.1063/1.2751266 |
0.415 |
|
2007 |
Sreenivasan S, Cohen R, López E, Toroczkai Z, Stanley HE. Structural bottlenecks for communication in networks. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 75: 036105. PMID 17500757 DOI: 10.1103/Physreve.75.036105 |
0.471 |
|
2007 |
Guclu H, Korniss G, Toroczkai Z. Extreme fluctuations in noisy task-completion landscapes on scale-free networks Chaos. 17. DOI: 10.1063/1.2735446 |
0.483 |
|
2007 |
Toroczkai Z, Guclu H. Proximity networks and epidemics Physica a: Statistical Mechanics and Its Applications. 378: 68-75. DOI: 10.1016/J.Physa.2006.11.088 |
0.387 |
|
2006 |
Danila B, Yu Y, Earl S, Marsh JA, Toroczkai Z, Bassler KE. Congestion-gradient driven transport on complex networks. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 74: 046114. PMID 17155140 DOI: 10.1103/Physreve.74.046114 |
0.648 |
|
2006 |
Guclu H, Korniss G, Novotny MA, Toroczkai Z, Rácz Z. Synchronization landscapes in small-world-connected computer networks Physical Review E - Statistical, Nonlinear, and Soft Matter Physics. 73. DOI: 10.1103/Physreve.73.066115 |
0.518 |
|
2004 |
Eubank S, Guclu H, Kumar VS, Marathe MV, Srinivasan A, Toroczkai Z, Wang N. Modelling disease outbreaks in realistic urban social networks. Nature. 429: 180-4. PMID 15141212 DOI: 10.1038/Nature02541 |
0.437 |
|
2004 |
Toroczkai Z, Bassler KE. Network dynamics: jamming is limited in scale-free systems. Nature. 428: 716. PMID 15085122 DOI: 10.1038/428716A |
0.68 |
|
2004 |
Anghel M, Toroczkai Z, Bassler KE, Korniss G. Competition-driven network dynamics: emergence of a scale-free leadership structure and collective efficiency. Physical Review Letters. 92: 058701. PMID 14995348 DOI: 10.1103/Physrevlett.92.058701 |
0.697 |
|
2004 |
Guclu H, Korniss G, Toroczkai Z, Novotny MA. Small-World Synchronized Computing Networks for Scalable Parallel Discrete-Event Simulations Lecture Notes in Physics. 650: 255-275. DOI: 10.1007/978-3-540-44485-5_12 |
0.384 |
|
2002 |
Toroczkai Z. Topological classification of binary trees using the Horton-Strahler index. Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics. 65: 016130. PMID 11800759 DOI: 10.1103/Physreve.65.016130 |
0.332 |
|
2000 |
Toroczkai Z, Korniss G, Das Sarma S, Zia RK. Extremal-point densities of interface fluctuations Physical Review. E, Statistical Physics, Plasmas, Fluids, and Related Interdisciplinary Topics. 62: 276-94. PMID 11088461 DOI: 10.1103/Physreve.62.276 |
0.697 |
|
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