Eric de Silva

1.5k total citations · 1 hit paper
16 papers, 1.0k citations indexed

About

Eric de Silva is a scholar working on Molecular Biology, Genetics and Epidemiology. According to data from OpenAlex, Eric de Silva has authored 16 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 5 papers in Genetics and 3 papers in Epidemiology. Recurrent topics in Eric de Silva's work include Bioinformatics and Genomic Networks (5 papers), RNA and protein synthesis mechanisms (4 papers) and Genetic Associations and Epidemiology (3 papers). Eric de Silva is often cited by papers focused on Bioinformatics and Genomic Networks (5 papers), RNA and protein synthesis mechanisms (4 papers) and Genetic Associations and Epidemiology (3 papers). Eric de Silva collaborates with scholars based in United Kingdom, United States and Denmark. Eric de Silva's co-authors include Michael P. H. Stumpf, Thomas Thorne, Carsten Wiuf, Michael Lappé, R. J. C. Stewart, Neil M. Ferguson, Christophe Fraser, Ian Stansfield, Russell Betney and Simon Cauchemez and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Astrophysical Journal and Philosophical Transactions of the Royal Society B Biological Sciences.

In The Last Decade

Eric de Silva

16 papers receiving 976 citations

Hit Papers

Estimating the size of the human interactome 2008 2026 2014 2020 2008 100 200 300 400 500
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Estimating the size of the human interactome
    2008 563 citations Michael P. H. Stumpf, Thomas Thorne et al. Proceedings of the National Academy of Sciences profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Eric de Silva United Kingdom 10 681 154 121 84 80 16 1.0k
Timothy R. Lezon United States 13 1.3k 1.9× 203 1.3× 93 0.8× 46 0.5× 35 0.4× 24 1.6k
Fabian Paul Germany 14 1.6k 2.4× 285 1.9× 72 0.6× 116 1.4× 27 0.3× 17 2.0k
David R. Lorenz United States 18 1.1k 1.6× 75 0.5× 101 0.8× 56 0.7× 128 1.6× 38 1.7k
Chakra Chennubhotla United States 15 1.2k 1.7× 227 1.5× 67 0.6× 27 0.3× 34 0.4× 32 1.4k
Faruck Morcos United States 24 2.3k 3.4× 186 1.2× 412 3.4× 56 0.7× 38 0.5× 66 2.7k
Wolfgang Rieping France 17 1.4k 2.0× 95 0.6× 140 1.2× 19 0.2× 32 0.4× 23 1.6k
Georg Casari Germany 20 1.4k 2.1× 147 1.0× 151 1.2× 13 0.2× 53 0.7× 24 1.9k
Anurag Sethi United States 20 1.3k 1.9× 189 1.2× 158 1.3× 11 0.1× 50 0.6× 35 1.7k
Robin Palotai Hungary 8 993 1.5× 253 1.6× 76 0.6× 86 1.0× 39 0.5× 11 1.4k
Pranab K. Chanda United States 23 535 0.8× 44 0.3× 227 1.9× 54 0.6× 226 2.8× 53 1.4k

Countries citing papers authored by Eric de Silva

Since Specialization
Citations

This map shows the geographic impact of Eric de Silva'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 Eric de Silva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eric de Silva more than expected).

Fields of papers citing papers by Eric de Silva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Eric de Silva. 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 Eric de Silva. The network helps show where Eric de Silva may publish in the future.

Co-authorship network of co-authors of Eric de Silva

This figure shows the co-authorship network connecting the top 25 collaborators of Eric de Silva. A scholar is included among the top collaborators of Eric de Silva 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 Eric de Silva. Eric de Silva is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Silva, Eric de, et al.. (2022). Polygenic coronary artery disease association with brain atrophy in the cognitively impaired. Brain Communications. 4(6). fcac314–fcac314. 4 indexed citations
2.
Chen, Hanyi, Eric de Silva, Carole H. Sudre, et al.. (2021). What do data‐driven Alzheimer’s disease subtypes tell us about white matter pathology and clinical progression?. Alzheimer s & Dementia. 17(S1). 1 indexed citations
3.
Altmann, André, Marzia A. Scelsi, Maryam Shoai, et al.. (2019). A comprehensive analysis of methods for assessing polygenic burden on Alzheimer’s disease pathology and risk beyond APOE. Brain Communications. 2(1). fcz047–fcz047. 35 indexed citations
4.
Silva, Eric de, Neil M. Ferguson, & Christophe Fraser. (2012). Inferring pandemic growth rates from sequence data. Journal of The Royal Society Interface. 9(73). 1797–1808. 34 indexed citations
5.
Betney, Russell, et al.. (2012). Regulation of release factor expression using a translational negative feedback loop: A systems analysis. RNA. 18(12). 2320–2334. 9 indexed citations
6.
Opatowski, Lulla, Christophe Fraser, Jamie T. Griffin, et al.. (2011). Transmission Characteristics of the 2009 H1N1 Influenza Pandemic: Comparison of 8 Southern Hemisphere Countries. PLoS Pathogens. 7(9). e1002225–e1002225. 54 indexed citations
7.
Betney, Russell, et al.. (2010). Autoregulatory systems controlling translation factor expression: Thermostat-like control of translational accuracy. RNA. 16(4). 655–663. 23 indexed citations
8.
Silva, Eric de, J. Krishnan, Russell Betney, & Ian Stansfield. (2010). A mathematical modelling framework for elucidating the role of feedback control in translation termination. Journal of Theoretical Biology. 264(3). 808–821. 9 indexed citations
9.
Stumpf, Michael P. H., Thomas Thorne, Eric de Silva, et al.. (2008). Estimating the size of the human interactome. Proceedings of the National Academy of Sciences. 105(19). 6959–6964. 563 indexed citations breakdown →
10.
Silva, Eric de, Thomas Thorne, Piers J. Ingram, et al.. (2006). The effects of incomplete protein interaction data on structural and evolutionary inferences. BMC Biology. 4(1). 39–39. 52 indexed citations
11.
Chakraborty, Rana, Milan Reiniš, Tim Rostron, et al.. (2006). nef gene sequence variation among HIV‐1‐infected African children*. HIV Medicine. 7(2). 75–84. 8 indexed citations
12.
Silva, Eric de & Michael P. H. Stumpf. (2005). Complex networks and simple models in biology. Journal of The Royal Society Interface. 2(5). 419–430. 90 indexed citations
13.
Iorio, Maria De, Eric de Silva, & Michael P. H. Stumpf. (2005). Recombination hotspots as a point process. Philosophical Transactions of the Royal Society B Biological Sciences. 360(1460). 1597–1603. 5 indexed citations
14.
Silva, Eric de, Lawrence A. Kelley, & Michael P. H. Stumpf. (2004). The extent and importance of intragenic recombination. Human Genomics. 1(6). 410–410. 9 indexed citations
15.
Silva, Eric de & Michael P. H. Stumpf. (2004). HIV and the CCR5-Î32 resistance allele. FEMS Microbiology Letters. 241(1). 1–12. 71 indexed citations
16.
Baker, Joanne C., R. W. Hunstead, R. Athreya, et al.. (2002). Associated Absorption in Radio Quasars. I. CivAbsorption and the Growth of Radio Sources. The Astrophysical Journal. 568(2). 592–609. 35 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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