P. Lambert

1.9k total citations
30 papers, 1.2k citations indexed

About

P. Lambert is a scholar working on Plant Science, Molecular Biology and Genetics. According to data from OpenAlex, P. Lambert has authored 30 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Plant Science, 13 papers in Molecular Biology and 6 papers in Genetics. Recurrent topics in P. Lambert's work include Plant Reproductive Biology (11 papers), Plant Physiology and Cultivation Studies (10 papers) and Plant Virus Research Studies (9 papers). P. Lambert is often cited by papers focused on Plant Reproductive Biology (11 papers), Plant Physiology and Cultivation Studies (10 papers) and Plant Virus Research Studies (9 papers). P. Lambert collaborates with scholars based in France, Morocco and Spain. P. Lambert's co-authors include Thierry Pascal, Lynda Hagen, J.M. Audergon, Pere Arús, Denis Rasschaert, Jean Marc Audergon, Bénédicte Quilot‐Turion, Véronique Decroocq, Bouchaïb Khadari and M. Rubio and has published in prestigious journals such as New Phytologist, The Plant Journal and Journal of Experimental Botany.

In The Last Decade

P. Lambert

30 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
P. Lambert France 21 903 466 211 169 165 30 1.2k
Fanny Calenge France 16 1.0k 1.1× 379 0.8× 125 0.6× 228 1.3× 190 1.2× 39 1.4k
Brenda G. Hunter United States 16 1.1k 1.2× 464 1.0× 242 1.1× 53 0.3× 50 0.3× 24 1.2k
Bin Tan China 19 864 1.0× 679 1.5× 102 0.5× 39 0.2× 45 0.3× 82 1.2k
Zsuzsanna Sasvári United States 17 726 0.8× 334 0.7× 83 0.4× 54 0.3× 34 0.2× 28 951
Hélène Chiapello France 18 409 0.5× 648 1.4× 160 0.8× 179 1.1× 15 0.1× 39 995
José Cleydson F. Silva Brazil 17 1.1k 1.2× 341 0.7× 36 0.2× 68 0.4× 56 0.3× 40 1.3k
D. Gallitelli Italy 24 2.0k 2.2× 353 0.8× 43 0.2× 268 1.6× 56 0.3× 122 2.1k
Michael Alonge United States 7 528 0.6× 549 1.2× 239 1.1× 67 0.4× 14 0.1× 8 955
Eckhard Tacke Germany 23 1.3k 1.4× 478 1.0× 85 0.4× 64 0.4× 29 0.2× 32 1.5k
Gary Gustafson United States 14 529 0.6× 359 0.8× 42 0.2× 43 0.3× 29 0.2× 19 745

Countries citing papers authored by P. Lambert

Since Specialization
Citations

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

Fields of papers citing papers by P. Lambert

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of P. Lambert

This figure shows the co-authorship network connecting the top 25 collaborators of P. Lambert. A scholar is included among the top collaborators of P. Lambert 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 P. Lambert. P. Lambert 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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Gattolin, Stefano, Marco Cirilli, Igor Pacheco, et al.. (2018). Deletion of the miR172 target site in a TOE‐type gene is a strong candidate variant for dominant double‐flower trait in Rosaceae. The Plant Journal. 96(2). 358–371. 46 indexed citations
3.
Confolent, Carole, et al.. (2017). Mapping of new resistance (Vr2, Rm1) and ornamental (Di2, pl) Mendelian trait loci in peach. Euphytica. 213(6). 26 indexed citations
4.
Biscarini, Filippo, Nelson Nazzicari, M.C.A.M. Bink, et al.. (2017). Genome-enabled predictions for fruit weight and quality from repeated records in European peach progenies. BMC Genomics. 18(1). 432–432. 59 indexed citations
5.
Baldazzi, Valentina, et al.. (2016). Dynamic QTLs for sugars and enzyme activities provide an overview of genetic control of sugar metabolism during peach fruit development. Journal of Experimental Botany. 67(11). 3419–3431. 47 indexed citations
6.
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Decroocq, Stéphane, P. Lambert, Guillaume Roch, et al.. (2014). Selecting with markers linked to the PPVres major QTL is not sufficient to predict resistance to Plum Pox Virus (PPV) in apricot. Tree Genetics & Genomes. 10(5). 1161–1170. 30 indexed citations
8.
Dirlewanger, Elisabeth, José Quero‐García, Loı̈ck Le Dantec, et al.. (2012). Comparison of the genetic determinism of two key phenological traits, flowering and maturity dates, in three Prunus species: peach, apricot and sweet cherry. Heredity. 109(5). 280–292. 120 indexed citations
9.
Audergon, Jean Marc, Guillaume Roch, P. Lambert, et al.. (2012). INHERITANCE OF PHENOLOGICAL TRAITS IN APRICOT PROGENIES. Acta Horticulturae. 27–35. 3 indexed citations
10.
11.
Lambert, P. & Thierry Pascal. (2011). Mapping Rm2 gene conferring resistance to the green peach aphid (Myzus persicae Sulzer) in the peach cultivar “Rubira®”. Tree Genetics & Genomes. 7(5). 1057–1068. 31 indexed citations
12.
Illa-Berenguer, Eudald, Iban Eduardo, Jean Marc Audergon, et al.. (2010). Saturating the Prunus (stone fruits) genome with candidate genes for fruit quality. Molecular Breeding. 28(4). 667–682. 49 indexed citations
13.
Soriano, José Miguel, P. Lambert, J. Salava, et al.. (2007). Flanking the major Plum pox virus resistance locus in apricot with co-dominant markers (SSRs) derived from candidate resistance genes. Tree Genetics & Genomes. 4(2). 359–365. 19 indexed citations
14.
Decroocq, Véronique, Marie Foulongne‐Oriol, P. Lambert, et al.. (2005). Analogues of virus resistance genes map to QTLs for resistance to sharka disease in Prunus davidiana. Molecular Genetics and Genomics. 272(6). 680–689. 69 indexed citations
15.
Hagen, Lynda, Jamila Chaïb, Bruno Fady, et al.. (2004). Genomic and cDNA microsatellites from apricot (Prunus armeniaca L.). Molecular Ecology Notes. 4(4). 742–745. 60 indexed citations
16.
Lambert, P., Lynda Hagen, Pere Arús, & J.M. Audergon. (2003). Genetic linkage maps of two apricot cultivars (Prunus armeniaca L.) compared with the almond Texas × peach Earlygold reference map for Prunus. Theoretical and Applied Genetics. 108(6). 1120–1130. 67 indexed citations
17.
Besnard, Guillaume, Yves Griveau, Marie-Christine Quillet, et al.. (1997). Specifying the introgressed regions from H. argophyllus in cultivated sunflower (Helianthus annuus L.) to mark Phomopsis resistance genes. Theoretical and Applied Genetics. 94(1). 131–138. 12 indexed citations
18.
Eléouët, Jean‐François, Denis Rasschaert, P. Lambert, et al.. (1995). Complete Genomic Sequence of the Transmissible Gastroenteritis Virus. Advances in experimental medicine and biology. 380. 459–461. 4 indexed citations
19.
Eléouët, Jean‐François, et al.. (1995). Complete Sequence (20 Kilobases) of the Polyprotein-Encoding Gene 1 of Transmissible Gastroenteritis Virus. Virology. 206(2). 817–822. 95 indexed citations
20.
Duarte, Manoela Mendes, J. Gelfi, P. Lambert, Denis Rasschaert, & Hubert Laude. (1994). Genome Organization of Porcine Epidemic Diarrhoea Virus. Advances in experimental medicine and biology. 342. 55–60. 85 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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