Mark D. Humphries

Statistical and Nonlinear Physics · 2006–2008

A researcher in the Science corpus: 2 papers; trusts 19 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Statistical and Nonlinear Physics — 25 citations into it; #2,743 of 10,127 by trust here, #3,979 by citations
• Computer Networks and Communications — 8 citations into it
• Molecular Biology — 8 citations into it
• Cognitive Neuroscience — 7 citations into it; #3,533 of 10,852 by trust here, #4,616 by citations
• Experimental and Cognitive Psychology — 6 citations into it; #2,951 of 9,731 by trust here, #3,491 by citations
• Geometry and Topology — 5 citations into it

Whom Mark D. Humphries trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Steven H. Strogatz
2. Mark Newman
3. Jie Wu
4. Mauricio Barahona
5. M. Keeling
6. Marco A. Janssen
7. Sophie Achard
8. Duncan J. Watts
9. Takashi Nishikawa
10. D. Bassett

Who trusts Mark D. Humphries overall

1. Yoed N. Kenett
2. D. Bassett
3. E. Bullmore
4. Marcus Kaiser
5. Cornelis J. Stam
6. B. van Wijk
7. Qawi K. Telesford
8. Olaf Sporns
9. Jaap C. Reijneveld
10. David Anaki

Papers from Mark D. Humphries's perspective

Ordered by how strongly the researchers Mark D. Humphries trusts endorse each paper. Same corpus, a different order for every researcher.

1. Collective dynamics of ‘small-world’ networks
2. Exploring complex networks (Nature)
3. Statistical mechanics of complex networks
4. Emergence of Scaling in Random Networks
5. Small world patterns in food webs. (Journal of Theoretical Biology)
6. Small worlds: the dynamics of networks between order and randomness
7. Classes of small-world networks. (Proceedings of the National Academy of Sciences of the United States of America)
8. Anatomical connectivity defines the organization of clusters of cortical areas in the macaque monkey and the cat. (Philosophical transactions of the Royal Society of London. Series B, Biological sciences)
9. Efficient behavior of small-world networks. (Physical Review Letters)
10. The small world inside large metabolic networks (Proceedings of the Royal Society of London. Series B: Biological Sciences)

Their papers

• Network ‘Small-World-Ness’: A Quantitative Method for Determining Canonical Network Equivalence (2008) — 1,397 citations
• The brainstem reticular formation is a small-world, not scale-free, network (2006) — 625 citations