Amy M. Sheflin

3.3k total citations · 2 hit papers
17 papers, 2.4k citations indexed

About

Amy M. Sheflin is a scholar working on Molecular Biology, Plant Science and Genetics. According to data from OpenAlex, Amy M. Sheflin has authored 17 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 8 papers in Plant Science and 3 papers in Genetics. Recurrent topics in Amy M. Sheflin's work include Gut microbiota and health (8 papers), Plant-Microbe Interactions and Immunity (4 papers) and Legume Nitrogen Fixing Symbiosis (4 papers). Amy M. Sheflin is often cited by papers focused on Gut microbiota and health (8 papers), Plant-Microbe Interactions and Immunity (4 papers) and Legume Nitrogen Fixing Symbiosis (4 papers). Amy M. Sheflin collaborates with scholars based in United States. Amy M. Sheflin's co-authors include Daniel K. Manter, Tiffany L. Weir, Jorge M. Vivanco, Jacqueline M. Chaparro, Elizabeth P. Ryan, Adam L. Heuberger, Alyssa K. Whitney, Matthew G. Bakker, Christopher L. Melby and Corey D. Broeckling and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and Applied and Environmental Microbiology.

In The Last Decade

Amy M. Sheflin

17 papers receiving 2.3k citations

Hit Papers

Manipulating the soil microbiome to increase soil health ... 2012 2026 2016 2021 2012 2013 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Amy M. Sheflin United States 14 1.1k 998 369 288 276 17 2.4k
Shanshan Qi China 31 731 0.7× 756 0.8× 160 0.4× 178 0.6× 121 0.4× 135 2.9k
Matthieu Barret France 32 1.5k 1.4× 2.5k 2.5× 374 1.0× 625 2.2× 456 1.7× 68 4.8k
Xue Qiang Zhao China 30 647 0.6× 1.3k 1.3× 331 0.9× 210 0.7× 84 0.3× 87 2.9k
Hongjian Yang China 29 751 0.7× 631 0.6× 90 0.2× 160 0.6× 160 0.6× 163 3.0k
Renaud Nalin France 24 1.5k 1.4× 663 0.7× 108 0.3× 721 2.5× 157 0.6× 30 2.5k
E. A. Gomes Brazil 25 440 0.4× 964 1.0× 178 0.5× 122 0.4× 151 0.5× 71 1.9k
Ke Zhao China 28 1.0k 0.9× 1.1k 1.1× 92 0.2× 123 0.4× 39 0.1× 102 2.9k
Hua-Fang Sheng China 14 893 0.8× 205 0.2× 86 0.2× 701 2.4× 215 0.8× 22 2.0k
Yu Bai China 24 715 0.6× 161 0.2× 95 0.3× 189 0.7× 158 0.6× 72 1.7k
Jung‐Ho Park South Korea 24 1.4k 1.3× 539 0.5× 76 0.2× 737 2.6× 65 0.2× 93 3.0k

Countries citing papers authored by Amy M. Sheflin

Since Specialization
Citations

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

Fields of papers citing papers by Amy M. Sheflin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Amy M. Sheflin. 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 Amy M. Sheflin. The network helps show where Amy M. Sheflin may publish in the future.

Co-authorship network of co-authors of Amy M. Sheflin

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

All Works

17 of 17 papers shown
1.
Chai, Yen Ning, Emily Goren, Dawn Chiniquy, et al.. (2023). Root-associated bacterial communities and root metabolite composition are linked to nitrogen use efficiency in sorghum. mSystems. 9(1). e0119023–e0119023. 13 indexed citations
2.
Berry, Jeffrey C., Mingsheng Qi, Balasaheb V. Sonawane, et al.. (2022). Increased signal-to-noise ratios within experimental field trials by regressing spatially distributed soil properties as principal components. eLife. 11. 4 indexed citations
3.
McGivern, Bridget B., Rebecca A. Daly, Jacqueline M. Chaparro, et al.. (2022). Variation in Root Exudate Composition Influences Soil Microbiome Membership and Function. Applied and Environmental Microbiology. 88(11). e0022622–e0022622. 76 indexed citations
4.
Goren, Emily, Amy M. Sheflin, Dawn Chiniquy, et al.. (2021). Feature selection and causal analysis for microbiome studies in the presence of confounding using standardization. BMC Bioinformatics. 22(1). 362–362. 4 indexed citations
5.
Yao, Linxing, Amy M. Sheflin, Corey D. Broeckling, & Jessica E. Prenni. (2019). Data Processing for GC-MS- and LC-MS-Based Untargeted Metabolomics. Methods in molecular biology. 1978. 287–299. 27 indexed citations
6.
Sheflin, Amy M., Jay S. Kirkwood, Lisa M. Wolfe, et al.. (2019). High-throughput quantitative analysis of phytohormones in sorghum leaf and root tissue by ultra-performance liquid chromatography-mass spectrometry. Analytical and Bioanalytical Chemistry. 411(19). 4839–4848. 29 indexed citations
7.
Sheflin, Amy M., Dawn Chiniquy, Emily Goren, et al.. (2019). Metabolomics of sorghum roots during nitrogen stress reveals compromised metabolic capacity for salicylic acid biosynthesis. Plant Direct. 3(3). e00122–e00122. 32 indexed citations
8.
Wang, Peng, Ellen L. Marsh, Elizabeth A. Ainsworth, et al.. (2017). Shifts in microbial communities in soil, rhizosphere and roots of two major crop systems under elevated CO2 and O3. Scientific Reports. 7(1). 15019–15019. 81 indexed citations
9.
Sheflin, Amy M., Erica C. Borresen, Jay S. Kirkwood, et al.. (2016). Dietary supplementation with rice bran or navy bean alters gut bacterial metabolism in colorectal cancer survivors. Molecular Nutrition & Food Research. 61(1). 92 indexed citations
10.
Sheflin, Amy M., Christopher L. Melby, Franck Carbonero, & Tiffany L. Weir. (2016). Linking dietary patterns with gut microbial composition and function. Gut Microbes. 8(2). 113–129. 113 indexed citations
11.
Sheflin, Amy M., Erica C. Borresen, Melissa Wdowik, et al.. (2015). Pilot Dietary Intervention with Heat-Stabilized Rice Bran Modulates Stool Microbiota and Metabolites in Healthy Adults. Nutrients. 7(2). 1282–1300. 71 indexed citations
12.
Cox‐York, Kimberly, Amy M. Sheflin, Michelle T. Foster, et al.. (2015). Ovariectomy results in differential shifts in gut microbiota in low versus high aerobic capacity rats. Physiological Reports. 3(8). e12488–e12488. 71 indexed citations
13.
Sheflin, Amy M., Alyssa K. Whitney, & Tiffany L. Weir. (2014). Cancer-Promoting Effects of Microbial Dysbiosis. Current Oncology Reports. 16(10). 406–406. 207 indexed citations
14.
Weir, Tiffany L., et al.. (2013). Stool Microbiome and Metabolome Differences between Colorectal Cancer Patients and Healthy Adults. PLoS ONE. 8(8). e70803–e70803. 519 indexed citations breakdown →
15.
Weir, Tiffany L., Robert F. Marschke, Regina J. Brown, et al.. (2013). Fecal metabolome and microflora differences between colorectal cancer patients and healthy adults.. Journal of Clinical Oncology. 31(15_suppl). 11050–11050. 3 indexed citations
16.
Chaparro, Jacqueline M., Amy M. Sheflin, Daniel K. Manter, & Jorge M. Vivanco. (2012). Manipulating the soil microbiome to increase soil health and plant fertility. Biology and Fertility of Soils. 48(5). 489–499. 772 indexed citations breakdown →
17.
Bakker, Matthew G., Daniel K. Manter, Amy M. Sheflin, Tiffany L. Weir, & Jorge M. Vivanco. (2012). Harnessing the rhizosphere microbiome through plant breeding and agricultural management. Plant and Soil. 360(1-2). 1–13. 271 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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