Hay Dvir

3.2k citations
33 papers · 2.6k indexed · 2 hit papers · h-index 19
Topics
Computational Drug Discovery Methods (7 papers)Cholinesterase and Neurodegenerative Diseases (7 papers)Bacterial Genetics and Biotechnology (4 papers)

In The Last Decade

Hay Dvir

33 papers receiving 2.5k citations

Hit Papers

Acetylcholinesterase: From 3D structure to function200420262011201820102004200400600

Peers

Hay Dvir
Comparison fields: 5 of 116
  • Pharmacology 1.2k
  • Molecular Biology 913
  • Computational Theory and Mathematics 746
  • Organic Chemistry 605
  • Plant Science 503
Replace Lilly Toker with:
Lilly Toker Israel
Christian Bergamini Italy
Clarence A. Broomfield United States
Ashima Saxena United States
Mankil Jung South Korea
Francisco Orallo Spain
Zhili Zuo China
David E. Lenz United States
Babu L. Tekwani United States
Soliman Khatib Israel
Hay Dvir relative to Lilly Toker Israel Lilly Toker's profile →
Citations per field
00.5×1.5×
Lilly Toker · 1×
Citations per year

Countries citing papers authored by Hay Dvir

Since Specialization
Citations

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

Fields of papers citing papers by Hay Dvir

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hay Dvir

This figure shows the co-authorship network connecting the top 25 collaborators of Hay Dvir. A scholar is included among the top collaborators of Hay Dvir 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 Hay Dvir. Hay Dvir 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 1
2 21
3 1
4 28
5 9
6 15
7 13
8 8
9 21
10 61
11 10
12 3
13 23
14 12
15
Acetylcholinesterase: From 3D structure to functionbreakdown →
606
16 23
17 128
18
Structure and evolution of the serum paraoxonase family of detoxifying and anti-atherosclerotic enzymesbreakdown →
501
19 97
20 217

About Hay Dvir

Hay Dvir is a scholar working on Computational Theory and Mathematics, Pharmacology and Biotechnology, having authored 33 papers that have together received 2.6k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (7 papers), Cholinesterase and Neurodegenerative Diseases (7 papers) and Bacterial Genetics and Biotechnology (4 papers). The work is most often cited by research in Pharmacology (1.2k citations), Clinical Biochemistry (398 citations) and Computational Theory and Mathematics (746 citations). Hay Dvir has collaborated with scholars based in Israel, United States and France. Frequent co-authors include Joel L. Sussman, Israel Silman, Michal Harel, Terrone L. Rosenberry, Andrew A. McCarthy, Lilly Toker, Senyon Choe, Ran Meged, Raimond B. G. Ravelli and Boris Brumshtein. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and The EMBO Journal.

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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