Jean-Marc Lacape

2.5k total citations
33 papers, 1.3k citations indexed

About

Jean-Marc Lacape is a scholar working on Plant Science, Endocrinology and Ecology, Evolution, Behavior and Systematics. According to data from OpenAlex, Jean-Marc Lacape has authored 33 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Plant Science, 9 papers in Endocrinology and 2 papers in Ecology, Evolution, Behavior and Systematics. Recurrent topics in Jean-Marc Lacape's work include Research in Cotton Cultivation (27 papers), Plant Virus Research Studies (12 papers) and Plant and Fungal Interactions Research (9 papers). Jean-Marc Lacape is often cited by papers focused on Research in Cotton Cultivation (27 papers), Plant Virus Research Studies (12 papers) and Plant and Fungal Interactions Research (9 papers). Jean-Marc Lacape collaborates with scholars based in France, Australia and Belgium. Jean-Marc Lacape's co-authors include Marc Giband, Brigitte Courtois, A.M. Risterucci, Philippe Brottier, Géo Coppens D'Eeckenbrugge, Danny Llewellyn, R. G. Cantrell, Sandra Thibivilliers, John Jacobs and B. Hau and has published in prestigious journals such as PLoS ONE, Theoretical and Applied Genetics and Field Crops Research.

In The Last Decade

Jean-Marc Lacape

32 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jean-Marc Lacape France 15 1.2k 472 82 72 43 33 1.3k
P. M. Thaxton United States 15 1.0k 0.8× 266 0.6× 165 2.0× 43 0.6× 104 2.4× 34 1.0k
Warwick N. Stiller Australia 18 698 0.6× 87 0.2× 143 1.7× 56 0.8× 70 1.6× 48 772
Xuebiao Pan China 20 1.4k 1.2× 118 0.3× 299 3.6× 465 6.5× 27 0.6× 93 1.5k
Edward L. Lubbers United States 15 734 0.6× 81 0.2× 115 1.4× 162 2.3× 23 0.5× 26 823
Seiji Uematsu Japan 16 607 0.5× 52 0.1× 260 3.2× 15 0.2× 17 0.4× 45 691
Stefan Buczacki United Kingdom 14 831 0.7× 256 0.5× 132 1.6× 10 0.1× 30 0.7× 51 882
Tatiana V. Roubtsova United States 11 396 0.3× 62 0.1× 68 0.8× 11 0.2× 11 0.3× 21 527
D. J. Lovell United Kingdom 12 736 0.6× 26 0.1× 79 1.0× 61 0.8× 17 0.4× 21 803
D. Hüberli United States 19 865 0.7× 44 0.1× 467 5.7× 17 0.2× 34 0.8× 65 955
Salliana R. Stetina United States 14 627 0.5× 53 0.1× 61 0.7× 29 0.4× 41 1.0× 61 675

Countries citing papers authored by Jean-Marc Lacape

Since Specialization
Citations

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

Fields of papers citing papers by Jean-Marc Lacape

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jean-Marc Lacape. 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 Jean-Marc Lacape. The network helps show where Jean-Marc Lacape may publish in the future.

Co-authorship network of co-authors of Jean-Marc Lacape

This figure shows the co-authorship network connecting the top 25 collaborators of Jean-Marc Lacape. A scholar is included among the top collaborators of Jean-Marc Lacape 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 Jean-Marc Lacape. Jean-Marc Lacape 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.
Sawadogo, Mahamadou, et al.. (2016). SSR-based genetic diversity of traditional and perennial cotton (Gossypium spp.) populations collected in Burkina Faso. Genetic Resources and Crop Evolution. 64(7). 1743–1759. 8 indexed citations
2.
Liu, Shiming, Jean-Marc Lacape, G. A. Constable, & Danny Llewellyn. (2015). Inheritance and QTL Mapping of Leaf Nutrient Concentration in a Cotton Inter-Specific Derived RIL Population. PLoS ONE. 10(5). e0128100–e0128100. 6 indexed citations
3.
D'Eeckenbrugge, Géo Coppens & Jean-Marc Lacape. (2014). Distribution and Differentiation of Wild, Feral, and Cultivated Populations of Perennial Upland Cotton (Gossypium hirsutum L.) in Mesoamerica and the Caribbean. PLoS ONE. 9(9). e107458–e107458. 62 indexed citations
4.
Searchinger, Tim, Craig Hanson, & Jean-Marc Lacape. (2014). Crop Breeding: Renewing the Global Commitment. 1 indexed citations
5.
Searchinger, Tim, Craig Hanson, & Jean-Marc Lacape. (2014). Installment 7 of "Creating a Sustainable Food Future" CROP BREEdING: RENEWING thE GlOBAl COmmItmENt. 1 indexed citations
6.
Blenda, Anna V., David D. Fang, Jean‐François Rami, et al.. (2012). A High Density Consensus Genetic Map of Tetraploid Cotton That Integrates Multiple Component Maps through Molecular Marker Redundancy Check. PLoS ONE. 7(9). e45739–e45739. 84 indexed citations
7.
Lacape, Jean-Marc, Michel Claverie, Ramón Vidal, et al.. (2012). Deep Sequencing Reveals Differences in the Transcriptional Landscapes of Fibers from Two Cultivated Species of Cotton. PLoS ONE. 7(11). e48855–e48855. 31 indexed citations
8.
Claverie, Michel, Marlène Souquet, Janine Jean, et al.. (2011). cDNA-AFLP-based genetical genomics in cotton fibers. Theoretical and Applied Genetics. 124(4). 665–683. 14 indexed citations
9.
10.
Lacape, Jean-Marc, Marguerite Rodier-Goud, Halima Benbouza, et al.. (2010). Isolation of five new monosomic alien addition lines of Gossypium australe F. Muell in G. hirsutum L. by SSR and GISH analyses. Plant Breeding. 130(1). 60–66. 11 indexed citations
11.
Lacape, Jean-Marc, Danny Llewellyn, John Jacobs, et al.. (2010). Meta-analysis of cotton fiber quality QTLs across diverse environments in a Gossypium hirsutum x G. barbadense RIL population. BMC Plant Biology. 10(1). 132–132. 111 indexed citations
12.
13.
Lacape, Jean-Marc, John Jacobs, Tony Arioli, et al.. (2009). A new interspecific, Gossypium hirsutum × G. barbadense, RIL population: towards a unified consensus linkage map of tetraploid cotton. Theoretical and Applied Genetics. 119(2). 281–292. 81 indexed citations
14.
Stelly, David M., Jean-Marc Lacape, Dominique Dessauw, et al.. (2007). International genetic, cytogenetic and germplasm resources for cotton genomics and genetic improvement. Agritrop (Cirad). 1 indexed citations
15.
Lacape, Jean-Marc, et al.. (2006). Microsatellite diversity in tetraploid Gossypium germplasm: assembling a highly informative genotyping set of cotton SSRs. Molecular Breeding. 19(1). 45–58. 115 indexed citations
16.
Lacape, Jean-Marc & Tran B. Nguyen. (2005). Mapping Quantitative Trait Loci Associated with Leaf and Stem Pubescence in Cotton. Journal of Heredity. 96(4). 441–444. 39 indexed citations
17.
Lacape, Jean-Marc, et al.. (2004). Molecular markers for DNA-fingerprinting in cotton. Agritrop (Cirad). 3 indexed citations
18.
Giband, Marc, et al.. (2004). Wide coverage of the tetraploid cotton genome using newly developed microsatellite markers. Theoretical and Applied Genetics. 109(1). 167–175. 179 indexed citations
19.
Lacape, Jean-Marc, Sandra Thibivilliers, Brigitte Courtois, et al.. (2003). A combined RFLPSSRAFLP map of tetraploid cotton based on aGossypium hirsutum×Gossypium barbadensebackcross population. Genome. 46(4). 612–626. 190 indexed citations
20.
Schwendiman, Jacques, et al.. (1982). Les cotonniers primitifs G. hirsutum race yucatanense de la Pointe des Châteaux en Guadeloupe et l'origine possible des cotonniers tétraploïdes du Nouveau Monde. Agritrop (Cirad). 3 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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