David A. Lightfoot

12.3k total citations · 1 hit paper
228 papers, 8.1k citations indexed

About

David A. Lightfoot is a scholar working on Plant Science, Molecular Biology and Cell Biology. According to data from OpenAlex, David A. Lightfoot has authored 228 papers receiving a total of 8.1k indexed citations (citations by other indexed papers that have themselves been cited), including 162 papers in Plant Science, 39 papers in Molecular Biology and 27 papers in Cell Biology. Recurrent topics in David A. Lightfoot's work include Soybean genetics and cultivation (91 papers), Legume Nitrogen Fixing Symbiosis (64 papers) and Nematode management and characterization studies (39 papers). David A. Lightfoot is often cited by papers focused on Soybean genetics and cultivation (91 papers), Legume Nitrogen Fixing Symbiosis (64 papers) and Nematode management and characterization studies (39 papers). David A. Lightfoot collaborates with scholars based in United States, Egypt and Japan. David A. Lightfoot's co-authors include Ammar B. Altemimi, Dennis G. Watson, Naoufal Lakhssassi, Khalid Meksem, Andrew J. Wood, V. N. Njiti, Ahmed J. Afzal, Hany A. El‐Shemy, My Abdelmajid Kassem and Kanokporn Triwitayakorn and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and PLoS ONE.

In The Last Decade

David A. Lightfoot

220 papers receiving 7.7k citations

Hit Papers

Phytochemicals: Extraction, Isolation, and Identification... 2017 2026 2020 2023 2017 400 800 1.2k
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.

  1. Phytochemicals: Extraction, Isolation, and Identification of Bioactive Compounds from Plant Extracts
    2017 1.3k citations Naoufal Lakhssassi, David A. Lightfoot et al. Plants profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David A. Lightfoot United States 50 5.7k 1.4k 773 682 564 228 8.1k
Bernd Schneider Germany 50 4.9k 0.9× 5.0k 3.5× 532 0.7× 343 0.5× 394 0.7× 319 9.8k
J. Christopher Young Canada 47 3.5k 0.6× 1.8k 1.2× 1.4k 1.8× 866 1.3× 1.6k 2.8× 109 7.0k
Michael Rychlik Germany 47 3.4k 0.6× 1.6k 1.2× 2.1k 2.7× 549 0.8× 410 0.7× 258 7.0k
Dongmei Wang China 37 2.4k 0.4× 2.3k 1.6× 721 0.9× 265 0.4× 649 1.2× 228 5.3k
Paul W. Paré United States 43 7.9k 1.4× 3.0k 2.1× 782 1.0× 514 0.8× 283 0.5× 174 11.5k
Lloyd W. Sumner United States 59 5.7k 1.0× 7.4k 5.2× 848 1.1× 301 0.4× 757 1.3× 156 12.0k
Lanping Guo China 38 2.5k 0.4× 2.6k 1.8× 925 1.2× 370 0.5× 351 0.6× 522 6.6k
Seung Hwan Yang South Korea 39 3.0k 0.5× 2.0k 1.4× 618 0.8× 322 0.5× 176 0.3× 203 5.3k
Paulo Mazzafera Brazil 50 4.9k 0.9× 2.3k 1.6× 786 1.0× 204 0.3× 344 0.6× 268 8.5k
Liang Chen China 49 3.5k 0.6× 3.2k 2.2× 801 1.0× 339 0.5× 639 1.1× 323 8.5k

Countries citing papers authored by David A. Lightfoot

Since Specialization
Citations

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

Fields of papers citing papers by David A. Lightfoot

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David A. Lightfoot

This figure shows the co-authorship network connecting the top 25 collaborators of David A. Lightfoot. A scholar is included among the top collaborators of David A. Lightfoot 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 David A. Lightfoot. David A. Lightfoot 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.
Badad, Oussama, Naoufal Lakhssassi, Nabil Zaïd, et al.. (2021). Genome Wide MeDIP-Seq Profiling of Wild and Cultivated Olives Trees Suggests DNA Methylation Fingerprint on the Sensory Quality of Olive Oil. Plants. 10(7). 1405–1405. 7 indexed citations
2.
Lightfoot, David A., et al.. (2018). Classification and experimental identification of plant long non-coding RNAs. Genomics. 111(5). 997–1005. 82 indexed citations
3.
Lightfoot, David A., et al.. (2017). QTL Underlying Reniform Nematode Resistance in Soybean Cultivar Hartwig. SHILAP Revista de lepidopterología. 308–312. 6 indexed citations
4.
Lightfoot, David A., et al.. (2017). A Rapid Method for Cannabis Species Determination by DNA Sequencing. 292–294. 1 indexed citations
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Khalafalla, Mutasim M., et al.. (2010). Active principle from Moringa oleifera Lam leaves effective against two leukemias and a hepatocarcinoma. AFRICAN JOURNAL OF BIOTECHNOLOGY. 9(49). 8467–8471. 170 indexed citations
7.
Attia, Kotb A., et al.. (2009). Antisense Phenotypes Reveal a Functional Expression ofOsARF1, an Auxin Response Factor, in Transgenic Rice. Current Issues in Molecular Biology. 11 Suppl 1. i29–34. 54 indexed citations
8.
Shukla, Abhijit, et al.. (2009). The Interactions of the Largest Subunit of RNA Polymerase II with Other Cellular Proteins: a Bioinformatic Approach. Current Issues in Molecular Biology. 11 Suppl 1. i65–71. 3 indexed citations
9.
El-Shihy, Osama, et al.. (2009). Establishment of the Regeneration System forVicia fabaL.. Current Issues in Molecular Biology. 11 Suppl 1. i47–54. 15 indexed citations
10.
Yuan, Jiazheng, Muhammad Haroon, David A. Lightfoot, et al.. (2009). A High-Resolution Melting Approach for Analyzing Allelic Expression Dynamics. PubMed. 11 Suppl 1. i1–9. 4 indexed citations
11.
Nassrallah, Amr, et al.. (2009). Anti-cancer and anti-oxidant activity of some Egyptian medicinal plants.. Journal of Medicinal Plants Research. 3(10). 799–808. 31 indexed citations
12.
Khalafalla, Mutasim M., et al.. (2009). Antileukemia activity from root cultures of Vernonia amygdalina.. Journal of Medicinal Plants Research. 3(8). 556–562. 35 indexed citations
13.
Triwitayakorn, Kanokporn, et al.. (2005). Genomic analysis of a region encompassingQRfs1andQRfs2: genes that underlie soybean resistance to sudden death syndrome. Genome. 48(1). 125–138. 51 indexed citations
14.
Triwitayakorn, Kanokporn, Jörg B. Schulz, Khalid Meksem, et al.. (2004). Genomic approaches to molecular breeding of resistance to soybean sudden death syndrome and cyst nematode in elite cultivars.. 471–480. 2 indexed citations
15.
Johnson, J. W., et al.. (1998). Biotechnology approaches to improving resistance to SCN and SDS: methods for high throughput marker assisted selection.. 25. 115–117. 27 indexed citations
16.
Chang, S. J. C., et al.. (1997). Development and utility of sequence characterized amplified regions (SCARS) from RAPD markers linked to SDS and SCN QTLs.. 24. 128–131. 4 indexed citations
17.
Lightfoot, David A., et al.. (1996). Genetic analysis of resistance to manganese toxicity in soybean using molecular markers. 23. 155–157. 4 indexed citations
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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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