Jeff Jones

1.1k total citations
46 papers, 520 citations indexed

About

Jeff Jones is a scholar working on Biomedical Engineering, Ecology, Evolution, Behavior and Systematics and Plant Science. According to data from OpenAlex, Jeff Jones has authored 46 papers receiving a total of 520 indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Biomedical Engineering, 23 papers in Ecology, Evolution, Behavior and Systematics and 19 papers in Plant Science. Recurrent topics in Jeff Jones's work include Slime Mold and Myxomycetes Research (29 papers), Biocrusts and Microbial Ecology (23 papers) and Plant and Biological Electrophysiology Studies (19 papers). Jeff Jones is often cited by papers focused on Slime Mold and Myxomycetes Research (29 papers), Biocrusts and Microbial Ecology (23 papers) and Plant and Biological Electrophysiology Studies (19 papers). Jeff Jones collaborates with scholars based in United Kingdom, United States and Australia. Jeff Jones's co-authors include Andrew Adamatzky, Yong Deng, Soichiro Tsuda, Richard Mayne, Rachel Armstrong, Larry Bull, Derek Filbey, Alexander Safonov, Eduardo Reck Miranda and Mohammed Saeed and has published in prestigious journals such as Scientific Reports, Journal of Inorganic Biochemistry and Vox Sanguinis.

In The Last Decade

Jeff Jones

44 papers receiving 495 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jeff Jones United Kingdom 13 336 245 214 84 36 46 520
Tomohiro Shirakawa Japan 10 321 1.0× 235 1.0× 216 1.0× 59 0.7× 13 0.4× 45 442
Michail‐Antisthenis Tsompanas United Kingdom 12 152 0.5× 63 0.3× 88 0.4× 73 0.9× 187 5.2× 56 441
Taoyang Wu United Kingdom 19 329 1.0× 76 0.3× 47 0.2× 49 0.6× 22 0.6× 69 1.0k
Takayuki Niizato Japan 11 95 0.3× 102 0.4× 62 0.3× 19 0.2× 8 0.2× 35 335
Mohammad Mahdi Dehshibi Spain 14 75 0.2× 19 0.1× 92 0.4× 14 0.2× 15 0.4× 50 485
Ricardo Ferreira Brazil 15 31 0.1× 29 0.1× 60 0.3× 189 2.3× 287 8.0× 106 716
Marco Seeland Germany 14 50 0.1× 115 0.5× 227 1.1× 4 0.0× 218 6.1× 30 856
Payam Zahadat Austria 11 67 0.2× 41 0.2× 55 0.3× 3 0.0× 11 0.3× 48 350
Hiroshi Tanaka Japan 8 21 0.1× 31 0.1× 15 0.1× 53 0.6× 12 0.3× 21 348
Bruno Augusto Nassif Travençolo Brazil 15 22 0.1× 53 0.2× 140 0.7× 10 0.1× 6 0.2× 52 672

Countries citing papers authored by Jeff Jones

Since Specialization
Citations

This map shows the geographic impact of Jeff Jones's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Jeff Jones with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jeff Jones more than expected).

Fields of papers citing papers by Jeff Jones

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeff Jones. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Jeff Jones. The network helps show where Jeff Jones may publish in the future.

Co-authorship network of co-authors of Jeff Jones

This figure shows the co-authorship network connecting the top 25 collaborators of Jeff Jones. A scholar is included among the top collaborators of Jeff Jones based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jeff Jones. Jeff Jones is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Morris, Meg E., Natasha K. Brusco, Jeff Jones, et al.. (2023). The Widening Gap between the Digital Capability of the Care Workforce and Technology-Enabled Healthcare Delivery: A Nursing and Allied Health Analysis. Healthcare. 11(7). 994–994. 17 indexed citations
2.
Ravanfar, Raheleh, Yuling Sheng, Mona Shahgholi, et al.. (2022). Surface cysteines could protect the SARS-CoV-2 main protease from oxidative damage. Journal of Inorganic Biochemistry. 234. 111886–111886. 7 indexed citations
3.
Jones, Jeff, et al.. (2017). Physarum machines imitating a Roman road network: the 3D approach. Scientific Reports. 7(1). 7010–7010. 11 indexed citations
4.
Deng, Yong, et al.. (2017). Network Division Method Based on Cellular Growth and Physarum-inspired Network Adaptation.. International journal of unconventional computing. 13. 477–491. 42 indexed citations
5.
Jones, Jeff, et al.. (2016). Towards a Physarum learning chip. Scientific Reports. 6(1). 19948–19948. 17 indexed citations
6.
Mayne, Richard, Jeff Jones, Ella Gale, & Andrew Adamatzky. (2016). On coupled oscillator dynamics and incident behaviour patterns in slime mouldPhysarum polycephalum: emergence of wave packets, global streaming clock frequencies and anticipation of periodic stimuli. International Journal of Parallel Emergent and Distributed Systems. 32(1). 95–118. 5 indexed citations
7.
Adamatzky, Andrew, et al.. (2016). Evaluation of French motorway network in relation to slime mould transport networks. Environment and Planning B Urban Analytics and City Science. 44(2). 364–383. 4 indexed citations
8.
Jones, Jeff & Andrew Adamatzky. (2015). Approximation of statistical analysis and estimation by morphological adaptation in a model of slime mould. International journal of unconventional computing. 11(1). 37–62. 2 indexed citations
9.
Jones, Jeff. (2015). From Pattern Formation to Material Computation: Multi-agent Modelling of Physarum Polycephalum. CERN Document Server (European Organization for Nuclear Research). 9 indexed citations
10.
Jones, Jeff & Andrew Adamatzky. (2014). Material approximation of data smoothing and spline curves inspired by slime mould. Bioinspiration & Biomimetics. 9(3). 36016–36016. 10 indexed citations
11.
Jones, Jeff & Andrew Adamatzky. (2012). Emergence of self-organized amoeboid movement in a multi-agent approximation of Physarum polycephalum. Bioinspiration & Biomimetics. 7(1). 16009–16009. 9 indexed citations
12.
Jones, Jeff. (2011). Towards programmable smart materials: Dynamical reconfiguration of emergent transport networks. International journal of unconventional computing. 7. 423–447. 9 indexed citations
13.
Tsuda, Soichiro & Jeff Jones. (2010). The Emergence of Complex Oscillatory Behaviour in Physarum polycephalum and its Particle Approximation. Artificial Life. 698–705. 3 indexed citations
14.
Jones, Jeff & Andrew Adamatzky. (2010). Towards Physarum binary adders. Biosystems. 101(1). 51–58. 24 indexed citations
15.
Jacobs, John, et al.. (2010). You Don't Need A Weatherman To Know Which Way The Wind Blows.
16.
Tsuda, Soichiro & Jeff Jones. (2010). The emergence of synchronization behavior in Physarum polycephalum and its particle approximation. Biosystems. 103(3). 331–341. 15 indexed citations
17.
Jones, Jeff. (2010). Influences on the formation and evolution of Physarum polycephalum inspired emergent transport networks. Natural Computing. 10(4). 1345–1369. 23 indexed citations
18.
Jones, Jeff. (2008). An Emergent Pattern Formation Approach to Dynamic Spatial Problems via Quantitative Front Propagation and Particle Chemotaxis.. International journal of unconventional computing. 4. 341–374. 2 indexed citations
19.
Jones, Jeff & Mohammed Saeed. (2007). Image enhancement – An emergent pattern formation approach via decentralised multi-agent systems. Multiagent and Grid Systems. 3(1). 105–140. 6 indexed citations
20.
Jones, Jeff & Derek Filbey. (1996). Selection of Monoclonal Antibodies for the Identification of D Variants: Ability to Detect Weak D and to Split epD2, epD5 and epD6/7. Vox Sanguinis. 70(3). 173–179. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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