Barbara Gilmore

951 total citations
20 papers, 506 citations indexed

About

Barbara Gilmore is a scholar working on Plant Science, Cell Biology and Molecular Biology. According to data from OpenAlex, Barbara Gilmore has authored 20 papers receiving a total of 506 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Plant Science, 5 papers in Cell Biology and 4 papers in Molecular Biology. Recurrent topics in Barbara Gilmore's work include Plant pathogens and resistance mechanisms (7 papers), Plant Pathogens and Fungal Diseases (5 papers) and Horticultural and Viticultural Research (5 papers). Barbara Gilmore is often cited by papers focused on Plant pathogens and resistance mechanisms (7 papers), Plant Pathogens and Fungal Diseases (5 papers) and Horticultural and Viticultural Research (5 papers). Barbara Gilmore collaborates with scholars based in United States, New Zealand and Canada. Barbara Gilmore's co-authors include Nahla Bassil, Todd C. Mockler, Cindy Lawley, Dorrie Main, Larry Wilhelm, James R. Myers, D. Jasper G. Rees, Ross Crowhurst, Stijn Vanderzande and Susan E. Gardiner and has published in prestigious journals such as PLoS ONE, Theoretical and Applied Genetics and Phytopathology.

In The Last Decade

Barbara Gilmore

20 papers receiving 470 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Barbara Gilmore United States 8 450 186 92 82 40 20 506
Ladislav Kučera Czechia 14 444 1.0× 160 0.9× 115 1.3× 57 0.7× 48 1.2× 44 509
T. Gopalakrishna India 12 594 1.3× 99 0.5× 49 0.5× 80 1.0× 70 1.8× 30 666
Yolanda Loarce Spain 14 627 1.4× 171 0.9× 50 0.5× 207 2.5× 75 1.9× 34 692
F. G. Felsenstein Germany 16 526 1.2× 147 0.8× 104 1.1× 22 0.3× 175 4.4× 30 566
Sundeep Kumar India 10 377 0.8× 79 0.4× 32 0.3× 194 2.4× 24 0.6× 21 456
M. S. Saharan India 13 498 1.1× 108 0.6× 141 1.5× 38 0.5× 23 0.6× 103 542
Ebrahiem Babiker United States 16 528 1.2× 142 0.8× 85 0.9× 137 1.7× 16 0.4× 42 564
Catherine Macadré France 17 514 1.1× 323 1.7× 141 1.5× 28 0.3× 30 0.8× 23 740
Leona Leišová‐Svobodová Czechia 11 269 0.6× 60 0.3× 67 0.7× 34 0.4× 41 1.0× 48 308
Vincent Thareau France 18 840 1.9× 354 1.9× 75 0.8× 34 0.4× 42 1.1× 24 921

Countries citing papers authored by Barbara Gilmore

Since Specialization
Citations

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

Fields of papers citing papers by Barbara Gilmore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Barbara Gilmore

This figure shows the co-authorship network connecting the top 25 collaborators of Barbara Gilmore. A scholar is included among the top collaborators of Barbara Gilmore 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 Barbara Gilmore. Barbara Gilmore 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.
Bassil, Nahla, R. B. King, Jason D. Zurn, et al.. (2023). Progress on the molecular characterization of the USDA National Pear Collection. Acta Horticulturae. 273–280. 2 indexed citations
2.
Dombrowski, James E., et al.. (2022). Horizontal transmission and expression of Epichloë typhina in orchardgrass (Dactylis glomerata). European Journal of Plant Pathology. 163(2). 415–428. 2 indexed citations
3.
Gilmore, Barbara, Ruth C. Martin, James E. Dombrowski, et al.. (2017). Virus Incidence in Orchardgrass (Dactylis glomerata L.) Seed Production Fields in the Willamette Valley. Crop Forage & Turfgrass Management. 3(1). 1–3. 1 indexed citations
4.
Gilmore, Barbara, Brian J. Knaus, Nahla Bassil, et al.. (2016). Simple sequence repeat markers that identify Claviceps species and strains. Europe PMC (PubMed Central). 3(1). 25 indexed citations
5.
Dossett, Michael, Jill M. Bushakra, Barbara Gilmore, et al.. (2015). Development and Transferability of Black and Red Raspberry Microsatellite Markers from Short-Read Sequences. Journal of the American Society for Horticultural Science. 140(3). 243–252. 6 indexed citations
6.
Bushakra, Jill M., Douglas W. Bryant, Michael Dossett, et al.. (2015). A genetic linkage map of black raspberry (Rubus occidentalis) and the mapping of Ag 4 conferring resistance to the aphid Amphorophora agathonica. Theoretical and Applied Genetics. 128(8). 1631–1646. 27 indexed citations
7.
Alderman, S. C., Ruth C. Martin, Barbara Gilmore, et al.. (2015). First Report of Cocksfoot mottle virus Infecting Dactylis glomerata in Oregon and the United States. Plant Disease. 100(5). 1030–1030. 4 indexed citations
8.
Bassil, Nahla, Barbara Gilmore, Kim E. Hummer, et al.. (2014). GENETIC AND DEVELOPING GENOMIC RESOURCES IN BLACK RASPBERRY. Acta Horticulturae. 19–24. 2 indexed citations
9.
Gilmore, Barbara, Nahla Bassil, Danny L. Barney, Brian J. Knaus, & Kim E. Hummer. (2014). Short-read DNA Sequencing Yields Microsatellite Markers for Rheum. Journal of the American Society for Horticultural Science. 139(1). 22–29. 4 indexed citations
10.
Gilmore, Barbara, et al.. (2013). Microsatellite Marker Development in Peony using Next Generation Sequencing. Journal of the American Society for Horticultural Science. 138(1). 64–74. 18 indexed citations
11.
Chagné, David, Ross Crowhurst, Michela Troggio, et al.. (2012). Genome-Wide SNP Detection, Validation, and Development of an 8K SNP Array for Apple. PLoS ONE. 7(2). e31745–e31745. 220 indexed citations
12.
Peace, Cameron, Nahla Bassil, Dorrie Main, et al.. (2012). Development and Evaluation of a Genome-Wide 6K SNP Array for Diploid Sweet Cherry and Tetraploid Sour Cherry. PLoS ONE. 7(12). e48305–e48305. 96 indexed citations
13.
Bassil, Nahla, et al.. (2008). Genic SSRs for European and North American hop (Humulus lupulus L.). Genetic Resources and Crop Evolution. 55(7). 959–969. 27 indexed citations
14.
Myers, James R., et al.. (2008). Progress in characterization and transfer of white mold resistance from runner to common bean. 2 indexed citations
15.
Bassil, Nahla, et al.. (2005). GENBANK-DERIVED MICROSATELLITE MARKERS IN HOP. Acta Horticulturae. 47–52. 3 indexed citations
16.
Chipps, Timothy J., Barbara Gilmore, James R. Myers, & Henrik U. Stotz. (2005). Relationship Between Oxalate, Oxalate Oxidase Activity, Oxalate Sensitivity, and White Mold Susceptibility in Phaseolus coccineus. Phytopathology. 95(3). 292–299. 24 indexed citations
17.
Gilmore, Barbara & James R. Myers. (2004). A preliminary molecular marker map for Phaseolus coccineus. 5 indexed citations
18.
Gilmore, Barbara, et al.. (2002). Completion of testing of Phaseolus coccineus plant introductions (PIs) for white mold, Sclerotinia sclerotiorum, resistance. 28 indexed citations
19.
Gilmore, Barbara & James R. Myers. (2000). 061 Examining the Phaseolus coccineus Collection for White Mold Resistance. HortScience. 35(3). 399A–399. 3 indexed citations
20.
Myers, James R., et al.. (1999). Correlation between the field and straw test for white mold resistance in common bean. 7 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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