World's Best Scientists 2026 revealed!

D-Index & Metrics

Genetics

D-Index
63
Citations
11340
World Ranking
2919
National Ranking
141

Alain Charcosset publication distribution in Genetics in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Genetics in 2026. The highlighted bar marks where Alain Charcosset sits on this spectrum.

45–54 publications: 6 scientists 55–64 publications: 10 scientists 65–74 publications: 35 scientists 75–84 publications: 84 scientists 85–94 publications: 102 scientists 95–104 publications: 151 scientists 105–114 publications: 175 scientists 115–124 publications: 203 scientists 125–134 publications: 217 scientists 135–144 publications: 205 scientists 145–154 publications: 193 scientists 155–164 publications: 188 scientists 165–174 publications: 170 scientists 175–184 publications: 178 scientists 185–194 publications: 164 scientists 195–204 publications: 173 scientists 205–214 publications: 159 scientists 215–224 publications: 134 scientists 225–234 publications: 143 scientists 235–244 publications: 105 scientists 245–254 publications: 114 scientists 255–264 publications: 92 scientists 265–274 publications: 88 scientists 275–284 publications: 87 scientists 285–294 publications: 80 scientists 295–304 publications: 62 scientists 305–314 publications: 75 scientists 315–324 publications: 67 scientists 325–334 publications: 60 scientists 335–344 publications: 52 scientists 345–354 publications: 40 scientists 355–364 publications: 48 scientists 365–374 publications: 47 scientists 375–384 publications: 46 scientists 385–394 publications: 31 scientists 395–404 publications: 27 scientists 405–414 publications: 40 scientists 415–424 publications: 30 scientists 425–434 publications: 43 scientists 435–444 publications: 29 scientists 445–454 publications: 14 scientists 455–464 publications: 28 scientists 465–474 publications: 21 scientists 475–484 publications: 21 scientists 485–494 publications: 22 scientists 495–504 publications: 17 scientists 505–514 publications: 12 scientists 515–524 publications: 11 scientists 525–534 publications: 8 scientists 535–544 publications: 8 scientists 545–554 publications: 14 scientists 555–564 publications: 4 scientists 565–574 publications: 11 scientists 575–584 publications: 5 scientists 585–594 publications: 11 scientists 595–604 publications: 12 scientists 605–614 publications: 7 scientists 615–624 publications: 6 scientists 625–634 publications: 10 scientists 635–644 publications: 9 scientists 645–654 publications: 10 scientists 655–664 publications: 6 scientists 665–674 publications: 6 scientists 675–684 publications: 6 scientists 685–694 publications: 4 scientists 695–702 publications: 6 scientists 703+ publications: 100 scientists
45 publications 703+

This scientist: 122 publications — 17th percentile

17% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 703 publications or more.

Alain Charcosset D-index placement in Genetics in 2026

The chart shows the D-index (discipline H-index) distribution of Genetics scientists ranked by Research.com in 2026. The highlighted bar marks where Alain Charcosset sits on this spectrum.

40–41 D-Index: 24 scientists 42–43 D-Index: 52 scientists 44–45 D-Index: 84 scientists 46–47 D-Index: 112 scientists 48–49 D-Index: 118 scientists 50–51 D-Index: 141 scientists 52–53 D-Index: 143 scientists 54–55 D-Index: 145 scientists 56–57 D-Index: 179 scientists 58–59 D-Index: 162 scientists 60–61 D-Index: 175 scientists 62–63 D-Index: 191 scientists 64–65 D-Index: 172 scientists 66–67 D-Index: 184 scientists 68–69 D-Index: 164 scientists 70–71 D-Index: 158 scientists 72–73 D-Index: 150 scientists 74–75 D-Index: 136 scientists 76–77 D-Index: 127 scientists 78–79 D-Index: 127 scientists 80–81 D-Index: 111 scientists 82–83 D-Index: 110 scientists 84–85 D-Index: 110 scientists 86–87 D-Index: 84 scientists 88–89 D-Index: 102 scientists 90–91 D-Index: 66 scientists 92–93 D-Index: 72 scientists 94–95 D-Index: 70 scientists 96–97 D-Index: 54 scientists 98–99 D-Index: 60 scientists 100–101 D-Index: 49 scientists 102–103 D-Index: 55 scientists 104–105 D-Index: 45 scientists 106–107 D-Index: 42 scientists 108–109 D-Index: 28 scientists 110–111 D-Index: 39 scientists 112–113 D-Index: 25 scientists 114–115 D-Index: 31 scientists 116–117 D-Index: 29 scientists 118–119 D-Index: 34 scientists 120–121 D-Index: 29 scientists 122–123 D-Index: 29 scientists 124–125 D-Index: 18 scientists 126–127 D-Index: 27 scientists 128–129 D-Index: 22 scientists 130–131 D-Index: 16 scientists 132–133 D-Index: 11 scientists 134–135 D-Index: 17 scientists 136–137 D-Index: 12 scientists 138–139 D-Index: 21 scientists 140–141 D-Index: 4 scientists 142–143 D-Index: 9 scientists 144–145 D-Index: 14 scientists 146–147 D-Index: 6 scientists 148–149 D-Index: 10 scientists 150–151 D-Index: 7 scientists 152–153 D-Index: 9 scientists 154–155 D-Index: 8 scientists 156–157 D-Index: 8 scientists 158–159 D-Index: 9 scientists 160+ D-Index: 96 scientists
40 D-Index 160+

This scientist: 63 D-Index — 35th percentile

35% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 160 D-Index or more.

Overview

Alain Charcosset is affiliated with INRAE, the Institut national de recherche pour l'agriculture, l'alimentation et l'environnement in France. Their research career spans multiple aspects of genetics and plant breeding, with a primary focus on agricultural genetics and molecular biology.

Their publication record includes recent papers such as "Optimized breeding strategies to harness genetic resources with different performance levels" (2020) published in BMC Genomics, "Improving the use of plant genetic resources to sustain breeding programs' efficiency" (2023) in Proceedings of the National Academy of Sciences, "Physiological adaptive traits are a potential allele reservoir for maize genetic progress under challenging conditions" (2022) in Nature Communications, "Genomic prediction of hybrid crops allows disentangling dominance and epistasis" (2021) in Genetics, and "Efficient ReML inference in variance component mixed models using a Min-Max algorithm" (2022) in PLoS Computational Biology.

The frequent co-authors collaborating with Alain Charcosset include Tristan Mary-Huard, Laurence Moreau, Delphine Madur, Cyril Bauland, and Stéphane Nicolas. These collaborators have contributed to many of their works across different projects and publications.

The primary publication venues for their research include Theoretical and Applied Genetics with eight publications, bioRxiv (Cold Spring Harbor Laboratory) with six, Genetics with five, and both PLoS Genetics and PLoS ONE with two publications each.

Alain Charcosset's main fields of study are Biochemistry, Genetics and Molecular Biology and Agricultural and Biological Sciences. Within these broader fields, their work focuses on several subfields including Genetics, Plant Science, Agronomy and Crop Science, Molecular Biology, and Ecology, Evolution, Behavior and Systematics.

The topics most frequently addressed in their research are Genetic Mapping and Diversity in Plants and Animals, Genetics and Plant Breeding, Genetic and phenotypic traits in livestock, Crop Yield and Soil Fertility, Wheat and Barley Genetics and Pathology, Genetic diversity and population structure, and Genetic Associations and Epidemiology.

Best Publications

  • A large maize (Zea mays L.) SNP genotyping array: development and germplasm genotyping, and genetic mapping to compare with the B73 reference genome.

    Martin W. Ganal;Gregor Durstewitz;Andreas Polley;Aurélie Bérard

  • Two Cytosolic Glutamine Synthetase Isoforms of Maize Are Specifically Involved in the Control of Grain Production

    Antoine Martin;Judy Lee;Thomas Kichey;Denise Gerentes

  • Combining Quantitative Trait Loci Analysis and an Ecophysiological Model to Analyze the Genetic Variability of the Responses of Maize Leaf Growth to Temperature and Water Deficit

    Matthieu Reymond;Bertrand Muller;Agnès Leonardi;Alain Charcosset

  • Marker-Assisted Introgression of Quantitative Trait Loci

    Alain Charcosset

  • Maximizing the Reliability of Genomic Selection by Optimizing the Calibration Set of Reference Individuals: Comparison of Methods in Two Diverse Groups of Maize Inbreds ( Zea mays L.)

    Renaud Rincent;Denis Laloë;Stephane Nicolas;T. Altmann

  • More on the efficiency of marker-assisted selection

    L. Moreau;F. Lacoudre;A. Charcosset

  • BioMercator V3

    Olivier Sosnowski;Alain Charcosset;Johann Joets

  • Maize introduction into Europe: the history reviewed in the light of molecular data

    C Rebourg;M Chastanet;B Gouesnard;C Welcker

  • Marker-assisted selection efficiency in populations of finite size.

    Laurence Moreau;Alain Charcosset;André Gallais;André Gallais

  • Intraspecific variation of recombination rate in maize

    Eva Bauer;Matthieu Falque;Hildrun Walter;Cyril Bauland

  • Usefulness of gene information in marker-assisted recurrent selection: A simulation appraisal

    Rex Bernardo;Alain Charcosset

  • Marker-assisted introgression of favorable alleles at quantitative trait loci between maize elite lines.

    Agnès Bouchez;Mathilde Causse;André Gallais

  • The Genetic Basis of Heterosis: Multiparental Quantitative Trait Loci Mapping Reveals Contrasted Levels of Apparent Overdominance Among Traits of Agronomical Interest in Maize ( Zea mays L.)

    Amandine Larièpe;Brigitte Mangin;Sylvain Jasson;Valérie Combes

  • Key Impact of Vgt1 on Flowering Time Adaptation in Maize: Evidence From Association Mapping and Ecogeographical Information

    Sébastien Ducrocq;Delphine Madur;Jean-Baptiste Veyrieras;Létizia Camus-Kulandaivelu

  • Genetic analysis and QTL mapping of cell wall digestibility and lignification in silage maize

    Valérie Méchin;Odile Argillier;Yannick Hébert;Emmanuelle Guingo

  • Relationship between heterosis and heterozygosity at marker loci: a theoretical computation

    A Charcosset;M Lefort-Buson;A Gallais

  • The effect of population structure on the relationship between heterosis and heterozygosity at marker loci

    A. Charcosset;L. Essioux

  • Usefulness of Multiparental Populations of Maize (Zea mays L.) for Genome-Based Prediction

    Christina Lehermeier;Nicole Krämer;Eva Bauer;Cyril Bauland

  • Large scale molecular analysis of traditional European maize populations. Relationships with morphological variation.

    C Rebourg;B Gouesnard;A Charcosset

  • Relationship between phenotypic and marker distances: theoretical and experimental investigations

    Judith Burstin;Alain Charcosset

Frequent Co-Authors

Albrecht E. Melchinger
Albrecht E. Melchinger University of Hohenheim
Thomas Altmann
Thomas Altmann Institute of Plant Genetics and Crop Plant Research
Chris-Carolin Schön
Chris-Carolin Schön Technical University of Munich
Dominique Brunel
Dominique Brunel INRAE : Institut national de recherche pour l'agriculture, l'alimentation et l'environnement
Pedro Revilla
Pedro Revilla Spanish National Research Council
Yves Barrière
Yves Barrière INRAE : Institut national de recherche pour l'agriculture, l'alimentation et l'environnement
Mathilde Causse
Mathilde Causse INRAE : Institut national de recherche pour l'agriculture, l'alimentation et l'environnement
Catherine Damerval
Catherine Damerval University of Paris-Saclay
Marilyn L. Warburton
Marilyn L. Warburton United States Department of Agriculture
Boddupalli M. Prasanna
Boddupalli M. Prasanna International Maize and Wheat Improvement Center

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