Kimberly A. Marshall

13.6k total citations · 4 hit papers
12 papers, 9.2k citations indexed

About

Kimberly A. Marshall is a scholar working on Molecular Biology, Genetics and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Kimberly A. Marshall has authored 12 papers receiving a total of 9.2k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 5 papers in Genetics and 3 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Kimberly A. Marshall's work include Genetic diversity and population structure (5 papers), Genomics and Phylogenetic Studies (4 papers) and Gene expression and cancer classification (3 papers). Kimberly A. Marshall is often cited by papers focused on Genetic diversity and population structure (5 papers), Genomics and Phylogenetic Studies (4 papers) and Gene expression and cancer classification (3 papers). Kimberly A. Marshall collaborates with scholars based in United States. Kimberly A. Marshall's co-authors include Irene F. Kim, Pierre Ledoux, Tanya Barrett, Katherine Phillippy, Michelle Holko, Hyeseung Lee, Naigong Zhang, Carlos Evangelista, Sean Davis and S. E. Wilhite and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Genetics.

In The Last Decade

Kimberly A. Marshall

12 papers receiving 9.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

NCBI GEO: archive for functional genomics data sets—update

2012 7.1k citations Tanya Barrett, Pierre Ledoux et al. Nucleic Acids Research profile →
NCBI GEO: archive for functional genomics data sets--10 years on

2010 863 citations Tanya Barrett, D. B. Troup et al. Nucleic Acids Research profile →
NCBI GEO: archive for high-throughput functional genomic data

2008 786 citations Tanya Barrett, D. B. Troup et al. Nucleic Acids Research profile →
NCBI GEO: archive for gene expression and epigenomics data sets: 23-year update

2023 137 citations Emily Clough, Tanya Barrett et al. Nucleic Acids Research profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Kimberly A. Marshall United States	12	6.5k	2.0k	1.3k	996	994	12	9.2k
Pierre Ledoux United States	8	7.2k 1.1×	2.3k 1.1×	1.4k 1.1×	1.1k 1.1×	910 0.9×	9	10.1k
Irene F. Kim United States	8	7.2k 1.1×	2.3k 1.1×	1.4k 1.1×	1.1k 1.1×	939 0.9×	8	10.1k
Katherine Phillippy United States	11	6.5k 1.0×	2.0k 1.0×	1.3k 1.0×	1000 1.0×	812 0.8×	12	9.1k
Carlos Evangelista United States	10	5.2k 0.8×	1.8k 0.9×	1.2k 0.9×	902 0.9×	601 0.6×	12	7.5k
Douglas A Hosack United States	9	7.5k 1.1×	2.0k 1.0×	942 0.7×	1.2k 1.2×	1.6k 1.6×	10	11.7k
Benjamin M. Bolstad United States	8	7.7k 1.2×	2.0k 1.0×	987 0.8×	1.2k 1.2×	1.3k 1.3×	10	11.5k
Michelle Holko United States	12	7.2k 1.1×	2.3k 1.1×	1.3k 1.0×	1.9k 1.9×	1.0k 1.0×	14	10.4k
Naigong Zhang United States	7	5.0k 0.8×	1.8k 0.9×	1.2k 0.9×	903 0.9×	593 0.6×	7	7.3k
Glynn Dennis United States	12	7.5k 1.2×	2.0k 1.0×	950 0.7×	1.6k 1.6×	1.6k 1.6×	13	12.3k
Tanya Barrett United States	21	10.0k 1.5×	3.0k 1.5×	1.9k 1.5×	1.4k 1.4×	1.3k 1.3×	24	13.8k

Countries citing papers authored by Kimberly A. Marshall

Since Specialization

Citations

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

Fields of papers citing papers by Kimberly A. Marshall

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kimberly A. Marshall. 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 Kimberly A. Marshall. The network helps show where Kimberly A. Marshall may publish in the future.

Co-authorship network of co-authors of Kimberly A. Marshall

This figure shows the co-authorship network connecting the top 25 collaborators of Kimberly A. Marshall. A scholar is included among the top collaborators of Kimberly A. Marshall 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 Kimberly A. Marshall. Kimberly A. Marshall is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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12 of 12 papers shown

Clough, Emily, Tanya Barrett, S. E. Wilhite, et al.. (2023). NCBI GEO: archive for gene expression and epigenomics data sets: 23-year update. Nucleic Acids Research. 52(D1). D138–D144. 137 indexed citations breakdown →

Barrett, Tanya, Pierre Ledoux, Carlos Evangelista, et al.. (2012). NCBI GEO: archive for functional genomics data sets—update. Nucleic Acids Research. 41(D1). D991–D995. 7062 indexed citations breakdown →

Barrett, Tanya, D. B. Troup, S. E. Wilhite, et al.. (2010). NCBI GEO: archive for functional genomics data sets--10 years on. Nucleic Acids Research. 39(Database). D1005–D1010. 863 indexed citations breakdown →

Barrett, Tanya, D. B. Troup, S. E. Wilhite, et al.. (2008). NCBI GEO: archive for high-throughput functional genomic data. Nucleic Acids Research. 37(Database). D885–D890. 786 indexed citations breakdown →

Brown, Garth, Edward E. Kadel, Daniel L. Bassoni, et al.. (2001). Anchored Reference Loci in Loblolly Pine (Pinus taeda L.) for Integrating Pine Genomics. Genetics. 159(2). 799–809. 72 indexed citations

Hipkins, Valerie D., Kimberly A. Marshall, David B. Neale, William H. Rottmann, & Steven H. Strauss. (1995). A mutation hotspot in the chloroplast genome of a conifer (Douglas-fir: Pseudotsuga) is caused by variability in the number of direct repeats derived from a partially duplicated tRNA gene. Current Genetics. 27(6). 572–579. 58 indexed citations

Neale, David B., et al.. (1992). Use of DNA markers in forest tree improvement research. New Forests. 6(1-4). 391–407. 20 indexed citations

Marshall, Kimberly A. & David B. Neale. (1992). The inheritance of mitochondrial DNA in Douglas-fir (Pseudotsugamenziesii). Canadian Journal of Forest Research. 22(1). 73–75. 20 indexed citations

Millar, Constance I. & Kimberly A. Marshall. (1991). Allozyme Variation of Port-Orford-Cedar (Chamaecyparis lawsoniana): Implications for Genetic Conservation. Forest Science. 37(4). 1060–1077. 26 indexed citations

10.

Neale, David B., et al.. (1991). Chloroplast DNA restriction fragment length polymorphism in Sequoia sempervirens D. Don Endl., Pseudotsuga menziesii (Mirb.) Franco, Calocedrus decurrens (Torr.), and Pinus taeda L.. Theoretical and Applied Genetics. 81(1). 83–89. 17 indexed citations

11.

Neale, David B., Kimberly A. Marshall, & David E. Harry. (1991). Inheritance of chloroplast and mitochondrial DNA in incense-cedar (Calocedrusdecurrens). Canadian Journal of Forest Research. 21(5). 717–720. 60 indexed citations

12.

Neale, David B., Kimberly A. Marshall, & Ronald R. Sederoff. (1989). Chloroplast and mitochondrial DNA are paternally inherited in Sequoia sempervirens D. Don Endl. Proceedings of the National Academy of Sciences. 86(23). 9347–9349. 125 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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