Mark D. Burow

5.2k total citations
88 papers, 2.7k citations indexed

About

Mark D. Burow is a scholar working on Plant Science, Inorganic Chemistry and Molecular Biology. According to data from OpenAlex, Mark D. Burow has authored 88 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 81 papers in Plant Science, 36 papers in Inorganic Chemistry and 13 papers in Molecular Biology. Recurrent topics in Mark D. Burow's work include Peanut Plant Research Studies (67 papers), Agricultural pest management studies (37 papers) and Coconut Research and Applications (36 papers). Mark D. Burow is often cited by papers focused on Peanut Plant Research Studies (67 papers), Agricultural pest management studies (37 papers) and Coconut Research and Applications (36 papers). Mark D. Burow collaborates with scholars based in United States, India and Ghana. Mark D. Burow's co-authors include Andrew H. Paterson, Charles E. Simpson, J. L. Starr, Naveen Puppala, Paxton Payton, Michael R. Baring, Gloria Burow, Norimoto Murai, Kameswara Rao Kottapalli and G. T. Church and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and The Plant Cell.

In The Last Decade

Mark D. Burow

86 papers receiving 2.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark D. Burow United States 31 2.4k 896 737 176 101 88 2.7k
Jean‐Luc Verdeil France 33 2.3k 1.0× 1.6k 1.8× 223 0.3× 110 0.6× 12 0.1× 95 2.9k
Christophe Riondet France 18 749 0.3× 1.2k 1.3× 106 0.1× 40 0.2× 72 0.7× 26 1.7k
Kiran K. Sharma India 33 2.6k 1.1× 1.7k 1.9× 78 0.1× 124 0.7× 12 0.1× 75 3.2k
Sabine Zachgo Germany 29 2.2k 0.9× 2.2k 2.4× 129 0.2× 73 0.4× 47 0.5× 58 2.9k
Theodor Lange Germany 29 2.2k 0.9× 1.7k 1.9× 53 0.1× 83 0.5× 19 0.2× 48 2.6k
Qingchuan Yang China 25 1.5k 0.6× 777 0.9× 50 0.1× 188 1.1× 21 0.2× 133 2.0k
Jeong Sheop Shin South Korea 31 2.5k 1.1× 1.8k 2.0× 31 0.0× 244 1.4× 26 0.3× 103 3.3k
Loreto Holuigue Chile 31 2.0k 0.8× 1.6k 1.8× 36 0.0× 43 0.2× 53 0.5× 54 2.7k
Anping Guo China 21 949 0.4× 580 0.6× 48 0.1× 57 0.3× 27 0.3× 66 1.2k
Rakesh Kumar India 17 1.2k 0.5× 452 0.5× 51 0.1× 109 0.6× 12 0.1× 97 1.6k

Countries citing papers authored by Mark D. Burow

Since Specialization
Citations

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

Fields of papers citing papers by Mark D. Burow

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark D. Burow. 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 Mark D. Burow. The network helps show where Mark D. Burow may publish in the future.

Co-authorship network of co-authors of Mark D. Burow

This figure shows the co-authorship network connecting the top 25 collaborators of Mark D. Burow. A scholar is included among the top collaborators of Mark D. Burow 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 Mark D. Burow. Mark D. Burow 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
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Rustgi, Sachin, Ruth Welti, Mary R. Roth, et al.. (2023). Lipid modulation contributes to heat stress adaptation in peanut. Frontiers in Plant Science. 14. 1299371–1299371. 11 indexed citations
4.
Cazenave, A., Mark D. Burow, Rebecca S. Bennett, et al.. (2022). Evaluation of the U.S. Peanut Germplasm Mini-Core Collection in the Virginia-Carolina Region Using Traditional and New High-Throughput Methods. Agronomy. 12(8). 1945–1945. 11 indexed citations
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Dampanaboina, Lavanya, Manish K. Pandey, Hari Kishan Sudini, et al.. (2021). Peanut Seed Coat Acts as a Physical and Biochemical Barrier against Aspergillus flavus Infection. Journal of Fungi. 7(12). 1000–1000. 21 indexed citations
7.
Chopra, Ratan, Charles E. Simpson, Andrew Hillhouse, et al.. (2018). SNP genotyping reveals major QTLs for plant architectural traits between A-genome peanut wild species. Molecular Genetics and Genomics. 293(6). 1477–1491. 4 indexed citations
8.
Chopra, Ratan, et al.. (2016). Transcriptome Sequencing of Diverse Peanut (Arachis) Wild Species and the Cultivated Species Reveals a Wealth of Untapped Genetic Variability. G3 Genes Genomes Genetics. 6(12). 3825–3836. 14 indexed citations
9.
Clevenger, Josh, Ye Chu, Carolina Chavarro, et al.. (2016). Genome-wide SNP Genotyping Resolves Signatures of Selection and Tetrasomic Recombination in Peanut. Molecular Plant. 10(2). 309–322. 106 indexed citations
10.
Chopra, Ratan, Gloria Burow, Andrew Farmer, et al.. (2014). Comparisons of De Novo Transcriptome Assemblers in Diploid and Polyploid Species Using Peanut (Arachis spp.) RNA-Seq Data. PLoS ONE. 9(12). e115055–e115055. 47 indexed citations
11.
Jiang, Yuelu, et al.. (2013). Effects of fluctuating temperature and silicate supply on the growth, biochemical composition and lipid accumulation of Nitzschia sp.. Bioresource Technology. 154. 336–344. 21 indexed citations
12.
Rowland, Diane, Naveen Puppala, John P. Beasley, et al.. (2012). Variation in carbon isotope ratio and its relation to other traits in peanut breeding lines and cultivars from U.S. trials. Journal of Plant Breeding and Crop Science. 4(8). 144–155. 4 indexed citations
13.
Gu, Qing, Li Sun, Sundaram Kuppu, et al.. (2011). Regulated Expression of an Isopentenyltransferase Gene (IPT) in Peanut Significantly Improves Drought Tolerance and Increases Yield Under Field Conditions. Plant and Cell Physiology. 52(11). 1904–1914. 152 indexed citations
14.
Simpson, Charles E., et al.. (2010). Marker assisted selection in the transfer of root-knot nematode resistance in the commercial peanut (Arachis hypogaea L.).. 62(1). 49–58. 3 indexed citations
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Selvaraj, Michael Gomez, et al.. (2009). Identification of QTLs for pod and kernel traits in cultivated peanut by bulked segregant analysis. Electronic Journal of Biotechnology. 12(2). 3–4. 51 indexed citations
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Burow, Mark D., et al.. (2006). PeanutMap: an online genome database for comparative molecular maps of peanut. BMC Bioinformatics. 7(1). 375–375. 5 indexed citations
17.
Ferguson, Morag, Mark D. Burow, Stefan Schulze, et al.. (2003). Microsatellite identification and characterization in peanut (A. hypogaea L.). Theoretical and Applied Genetics. 108(6). 1064–1070. 174 indexed citations
18.
Park, Chang‐Hwan, Mark D. Burow, Charles E. Simpson, & Andrew H. Paterson. (2002). Transmission Genetics of Chromatin from a Synthetic Amphidiploid to Cultivated Peanut (Arachis hypogaea L.). 154–154. 43 indexed citations
19.
Church, G. T., Charles E. Simpson, Mark D. Burow, Andrew H. Paterson, & J. L. Starr. (2000). Use of RFLP markers for identification of individuals homozygous for resistance to Meloidogyne arenaria in peanut. Nematology. 2(5). 575–580. 26 indexed citations
20.
Burow, Mark D., et al.. (1996). Isolation of cDNA clones of genes induced upon transfer of Chlamydomonas reinhardtii cells to low CO2. Plant Molecular Biology. 31(2). 443–448. 46 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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