Patricia C. Babbitt

15.6k citations
134 papers · 8.1k indexed · 1 hit paper · h-index 52

Patricia C. Babbitt

133 papers receiving 8.0k citations

Hit Papers

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Peers

Patricia C. Babbitt
Comparison fields: 5 of 148
  • Biochemistry 770
  • Molecular Biology 6.3k
  • Materials Chemistry 2.1k
  • Biotechnology 395
  • Parasitology 204
Replace Debra Dunaway‐Mariano with:
Debra Dunaway‐Mariano United States
Rik K. Wierenga Finland
Peter Macheroux Austria
David L. Ollis Australia
Karen N. Allen United States
Seiki Kuramitsu Japan
J.A. Gerlt United States
Valérie de Crécy‐Lagard United States
Joseph D. Schrag Canada
Joseph M. Jez United States
Patricia C. Babbitt relative to Debra Dunaway‐Mariano United States Debra Dunaway‐Mariano's profile →
Citations per field
00.5×1.5×
Debra Dunaway‐Mariano · 1×
Citations per year

Countries citing papers authored by Patricia C. Babbitt

Since Specialization
Citations

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

Fields of papers citing papers by Patricia C. Babbitt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Patricia C. Babbitt. 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 Patricia C. Babbitt. The network helps show where Patricia C. Babbitt may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Patricia C. Babbitt, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Patricia C. Babbitt Line = papers co-authored together Patricia C. Babbitt links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 202167
2 201897
3 2017110
4 201524
5 201479
6 2013189
7 2013113
8 201374
9 201245
10 201138
11 201033
12 2009107
13 200786
14 2006183
15 200442
16 20030
17 200245
18 199928
19 199756
20 1992172

About Patricia C. Babbitt

Patricia C. Babbitt is a scholar working on Molecular Biology, Materials Chemistry and Biochemistry, having authored 134 papers that have together received 8.1k indexed citations. Recurring topics across this work include Enzyme Structure and Function (50 papers), Protein Structure and Dynamics (37 papers), Microbial Metabolic Engineering and Bioproduction (27 papers), Bioinformatics and Genomic Networks (14 papers), Machine Learning in Bioinformatics (13 papers), Biochemical and Molecular Research (13 papers), Genomics and Phylogenetic Studies (10 papers) and Computational Drug Discovery Methods (10 papers). The work is most often cited by research in Biochemistry (770 citations), Molecular Biology (6.3k citations) and Materials Chemistry (2.1k citations). Patricia C. Babbitt has collaborated with scholars based in United States, Canada and Italy. Frequent co-authors include J.A. Gerlt, Shoshana Brown, Holly J. Atkinson, George L. Kenyon, Alexandra M. Schnoes, Thomas E. Ferrin, John H. Morris, Igor Dodevski, Steven C. Almo and Debra Dunaway‐Mariano. Their work appears in journals such as Nature, Science and Proceedings of the National Academy of Sciences.

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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