Fred P. Davis

4.5k total citations · 1 hit paper
37 papers, 2.8k citations indexed

About

Fred P. Davis is a scholar working on Molecular Biology, Immunology and Materials Chemistry. According to data from OpenAlex, Fred P. Davis has authored 37 papers receiving a total of 2.8k indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Molecular Biology, 9 papers in Immunology and 7 papers in Materials Chemistry. Recurrent topics in Fred P. Davis's work include Protein Structure and Dynamics (10 papers), Immune Cell Function and Interaction (9 papers) and Enzyme Structure and Function (7 papers). Fred P. Davis is often cited by papers focused on Protein Structure and Dynamics (10 papers), Immune Cell Function and Interaction (9 papers) and Enzyme Structure and Function (7 papers). Fred P. Davis collaborates with scholars based in United States, United Kingdom and Spain. Fred P. Davis's co-authors include Andrej Săli, Sean R. Eddy, Gilbert L. Henry, Serge Picard, Yuka Kanno, John J. O’Shea, Han‐Yu Shih, Yohei Mikami, Joseph R. Nery and Eran A. Mukamel and has published in prestigious journals such as Cell, Nucleic Acids Research and Nature Medicine.

In The Last Decade

Fred P. Davis

36 papers receiving 2.7k citations

Hit Papers

Epigenomic Signatures of Neuronal Diversity in the Mammal... 2015 2026 2018 2022 2015 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fred P. Davis United States 27 1.6k 699 376 322 250 37 2.8k
Brian Freeman United States 32 2.7k 1.7× 400 0.6× 242 0.6× 273 0.8× 312 1.2× 72 3.5k
Wolfgang Jagla Germany 20 908 0.6× 696 1.0× 240 0.6× 220 0.7× 60 0.2× 30 2.6k
Julie Dam France 22 1.1k 0.7× 257 0.4× 316 0.8× 183 0.6× 155 0.6× 48 2.4k
Henry F. Vischer Netherlands 32 1.7k 1.1× 773 1.1× 703 1.9× 341 1.1× 232 0.9× 111 3.1k
Martin Ebeling Switzerland 29 1.5k 0.9× 425 0.6× 273 0.7× 162 0.5× 32 0.1× 77 2.6k
Dan Garza United States 28 2.8k 1.8× 326 0.5× 681 1.8× 419 1.3× 71 0.3× 47 4.2k
Lois E. Greene United States 48 4.5k 2.9× 389 0.6× 424 1.1× 160 0.5× 216 0.9× 116 6.4k
Mikko Taipale Canada 29 5.7k 3.6× 585 0.8× 165 0.4× 847 2.6× 298 1.2× 47 6.9k
Clemens Broger Switzerland 26 1.7k 1.1× 680 1.0× 572 1.5× 217 0.7× 103 0.4× 42 2.9k
Alexander Gragerov United States 17 1.8k 1.1× 460 0.7× 222 0.6× 288 0.9× 273 1.1× 20 2.4k

Countries citing papers authored by Fred P. Davis

Since Specialization
Citations

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

Fields of papers citing papers by Fred P. Davis

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fred P. Davis. 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 Fred P. Davis. The network helps show where Fred P. Davis may publish in the future.

Co-authorship network of co-authors of Fred P. Davis

This figure shows the co-authorship network connecting the top 25 collaborators of Fred P. Davis. A scholar is included among the top collaborators of Fred P. Davis 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 Fred P. Davis. Fred P. Davis 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
1.
Girard, F, et al.. (2022). The PV2 cluster of parvalbumin neurons in the murine periaqueductal gray: connections and gene expression. Brain Structure and Function. 227(6). 2049–2072.
2.
Davis, Fred P., René Riedl‬, Jan vom Brocke, et al.. (2021). Information Systems and Neuroscience: NeuroIS Retreat 2020. CERN Document Server (European Organization for Nuclear Research). 10 indexed citations
3.
Mikami, Yohei, Rachael L. Philips, Giuseppe Sciumè, et al.. (2021). MicroRNA-221 and -222 modulate intestinal inflammatory Th17 cell response as negative feedback regulators downstream of interleukin-23. Immunity. 54(3). 514–525.e6. 38 indexed citations
4.
Davis, Fred P., Aljoscha Nern, Serge Picard, et al.. (2020). A genetic, genomic, and computational resource for exploring neural circuit function. eLife. 9. 131 indexed citations
5.
‍Kim, Do Young, Tetsuro Kobayashi, Benjamin Voisin, et al.. (2020). Targeted therapy guided by single-cell transcriptomic analysis in drug-induced hypersensitivity syndrome: a case report. Nature Medicine. 26(2). 236–243. 118 indexed citations
6.
Schwartz, Daniella M., Taylor K. Farley, Nathan Richoz, et al.. (2019). Retinoic Acid Receptor Alpha Represses a Th9 Transcriptional and Epigenomic Program to Reduce Allergic Pathology. Immunity. 50(1). 106–120.e10. 58 indexed citations
7.
Nagashima, Hiroyuki, Tanel Mahlakõiv, Han‐Yu Shih, et al.. (2019). Neuropeptide CGRP Limits Group 2 Innate Lymphoid Cell Responses and Constrains Type 2 Inflammation. Immunity. 51(4). 682–695.e6. 225 indexed citations
8.
Shih, Meng-Fu Maxwell, Fred P. Davis, Gilbert L. Henry, & Josh Dubnau. (2018). Nuclear Transcriptomes of the Seven Neuronal Cell Types That Constitute the Drosophila Mushroom Bodies. G3 Genes Genomes Genetics. 9(1). 81–94. 37 indexed citations
9.
Shmueli, Anat, et al.. (2018). Odorant binding protein 69a connects social interaction to modulation of social responsiveness in Drosophila. PLoS Genetics. 14(4). e1007328–e1007328. 42 indexed citations
10.
Villarino, Alejandro V., Giuseppe Sciumè, Fred P. Davis, et al.. (2017). Subset- and tissue-defined STAT5 thresholds control homeostasis and function of innate lymphoid cells. The Journal of Experimental Medicine. 214(10). 2999–3014. 72 indexed citations
11.
Xie, Liangqi, Sharon E. Torigoe, Jerry Xiao, et al.. (2017). A dynamic interplay of enhancer elements regulates Klf4 expression in naïve pluripotency. Genes & Development. 31(17). 1795–1808. 44 indexed citations
12.
Noon, Ella Preger‐Ben, Fred P. Davis, & David L. Stern. (2016). Evolved Repression Overcomes Enhancer Robustness. Developmental Cell. 39(5). 572–584. 26 indexed citations
13.
Mo, Alisa, Eran A. Mukamel, Fred P. Davis, et al.. (2015). Epigenomic Signatures of Neuronal Diversity in the Mammalian Brain. Neuron. 86(6). 1369–1384. 475 indexed citations breakdown →
14.
Davis, Fred P.. (2010). Proteome-wide prediction of overlapping small molecule and protein binding sites using structure. Molecular BioSystems. 7(2). 545–557. 9 indexed citations
15.
Pieper, Ursula, Narayanan Eswar, Benjamin Webb, et al.. (2008). MODBASE, a database of annotated comparative protein structure models and associated resources. Nucleic Acids Research. 37(Database). D347–D354. 126 indexed citations
16.
Martı́-Renom, Marc A., Ursula Pieper, M. S. Madhusudhan, et al.. (2007). DBAli tools: mining the protein structure space. Nucleic Acids Research. 35(Web Server). W393–W397. 22 indexed citations
17.
Davis, Fred P., David T. Barkan, Narayanan Eswar, James H. McKerrow, & Andrej Săli. (2007). Host–pathogen protein interactions predicted by comparative modeling. Protein Science. 16(12). 2585–2596. 93 indexed citations
18.
Davis, Fred P.. (2006). Protein complex compositions predicted by structural similarity. Nucleic Acids Research. 34(10). 2943–2952. 46 indexed citations
19.
Korkin, Dmitry, Fred P. Davis, & Andrej Săli. (2005). Localization of protein‐binding sites within families of proteins. Protein Science. 14(9). 2350–2360. 35 indexed citations
20.
Davis, Fred P. & Andrej Săli. (2005). PIBASE: a comprehensive database of structurally defined protein interfaces. Computer applications in the biosciences. 21(9). 1901–1907. 134 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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