Natalie L. Dawson

3.6k citations
30 papers · 2.0k indexed · 1 hit paper · h-index 21
Topics
Genomics and Phylogenetic Studies (12 papers)Machine Learning in Bioinformatics (11 papers)Protein Structure and Dynamics (8 papers)

In The Last Decade

Natalie L. Dawson

30 papers receiving 2.0k citations

Hit Papers

CATH: increased structural coverage of functional space2020202620222024202050100150200250

Peers

Natalie L. Dawson
Comparison fields: 5 of 117
  • Molecular Biology 1.7k
  • Materials Chemistry 385
  • Computational Theory and Mathematics 171
  • Genetics 147
  • Infectious Diseases 117
Replace Keehyoung Joo with:
Keehyoung Joo South Korea
Shuchismita Dutta United States
Raymond Hui Canada
Ian Sillitoe United Kingdom
Karim M. ElSawy United Kingdom
Paul Ashford United Kingdom
Lukáš Pravda Czechia
David T. Barkan United States
Carl Schmitz Australia
Sayoni Das United Kingdom
Natalie L. Dawson relative to Keehyoung Joo South Korea Keehyoung Joo's profile →
Citations per field
00.5×1.6×
Keehyoung Joo · 1×
Citations per year

Countries citing papers authored by Natalie L. Dawson

Since Specialization
Citations

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

Fields of papers citing papers by Natalie L. Dawson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Natalie L. Dawson. 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 Natalie L. Dawson. The network helps show where Natalie L. Dawson may publish in the future.

Co-authorship network of co-authors of Natalie L. Dawson

This figure shows the co-authorship network connecting the top 25 collaborators of Natalie L. Dawson. A scholar is included among the top collaborators of Natalie L. Dawson 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 Natalie L. Dawson. Natalie L. Dawson 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
#WorkIndexed citations
1 2
2 80
3 93
4 124
5 29
6 14
7 18
8 19
9 253
10 45
11 28
12 54
13 16
14 41
15 328
16 1
17 43
18 23
19 171
20
Is postmenopausal estrogen use risky results from a methodologic review and information synthesis
2

About Natalie L. Dawson

Natalie L. Dawson is a scholar working on Biophysics, Molecular Biology and Pharmacology, having authored 30 papers that have together received 2.0k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (12 papers), Machine Learning in Bioinformatics (11 papers) and Protein Structure and Dynamics (8 papers). The work is most often cited by research in Molecular Biology (1.7k citations), Computational Theory and Mathematics (171 citations) and Materials Chemistry (385 citations). Natalie L. Dawson has collaborated with scholars based in United Kingdom, Malaysia and India. Frequent co-authors include Christine Orengo, Ian Sillitoe, Jonathan Lees, Sayoni Das, David Lee, Tony E. Lewis, Paul Ashford, Janet M. Thornton, Su Datt Lam and Nicholas Furnham. Their work appears in journals such as Nucleic Acids Research, Bioinformatics and Journal of Molecular Biology.

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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