Paul Ashford

4.7k citations
15 papers · 1.3k indexed · 1 hit paper · h-index 12
Topics
Genomics and Phylogenetic Studies (5 papers)Machine Learning in Bioinformatics (3 papers)Fibroblast Growth Factor Research (3 papers)

In The Last Decade

Paul Ashford

15 papers receiving 1.3k citations

Hit Papers

CATH: increased structural coverage of functional space2020202620222024202050100150200250

Peers

Paul Ashford
Comparison fields: 5 of 102
  • Molecular Biology 1.1k
  • Materials Chemistry 272
  • Computational Theory and Mathematics 126
  • Infectious Diseases 108
  • Genetics 98
Replace Natalie L. Dawson with:
Natalie L. Dawson United Kingdom
Panagiotis I. Koukos Netherlands
John Badger United States
Tony E. Lewis United Kingdom
David T. Barkan United States
Damien Farrell Ireland
Jason W. Labonte United States
Carles Pons Spain
John P. Priestle Switzerland
Brian Jiménez‐García Spain
Paul Ashford relative to Natalie L. Dawson United Kingdom Natalie L. Dawson's profile →
Citations per field
00.5×1.5×
Natalie L. Dawson · 1×
Citations per year

Countries citing papers authored by Paul Ashford

Since Specialization
Citations

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

Fields of papers citing papers by Paul Ashford

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul Ashford. 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 Paul Ashford. The network helps show where Paul Ashford may publish in the future.

Co-authorship network of co-authors of Paul Ashford

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

All Works

15 of 15 papers shown
#WorkIndexed citations
1 1
2 8
3 80
4
CATH: increased structural coverage of functional spacebreakdown →
280
5 15
6 93
7 11
8 16
9 253
10 91
11 45
12 59
13 328
14 30
15 14

About Paul Ashford

Paul Ashford is a scholar working on Biophysics, Infectious Diseases and Molecular Biology, having authored 15 papers that have together received 1.3k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (5 papers), Machine Learning in Bioinformatics (3 papers) and Fibroblast Growth Factor Research (3 papers). The work is most often cited by research in Molecular Biology (1.1k citations), Computational Theory and Mathematics (126 citations) and Materials Chemistry (272 citations). Paul Ashford has collaborated with scholars based in United Kingdom, Malaysia and Spain. Frequent co-authors include Christine Orengo, Natalie L. Dawson, Ian Sillitoe, Jonathan Lees, Sayoni Das, Tony E. Lewis, David Lee, Janet M. Thornton, Camilla Pang and Sonja Lehtinen. Their work appears in journals such as Nucleic Acids Research, PLoS ONE and Scientific Reports.

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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