World's Best Scientists 2026 revealed!
Franki Speleman

Franki Speleman

Award Badge
Genetics
Belgium
2026

D-Index & Metrics

Genetics

D-Index
108
Citations
67898
World Ranking
558
National Ranking
5

Franki Speleman 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 Franki Speleman 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: 664 publications — 97th percentile

97% of scientists in this discipline score the same or lower.

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

Franki Speleman 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 Franki Speleman 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: 108 D-Index — 87th percentile

87% of scientists in this discipline score the same or lower.

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

Research.com Recognitions

  • 2026 - Research.com Genetics in Belgium Leader Award
  • 2025 - Research.com Genetics in Belgium Leader Award
  • 2024 - Research.com Genetics in Belgium Leader Award
  • 2023 - Research.com Genetics in Belgium Leader Award

Overview

What is he best known for?

The fields of study he is best known for:

  • Gene
  • Cancer
  • DNA

Franki Speleman mostly deals with Genetics, Cancer research, Neuroblastoma, Gene and Molecular biology. His Cancer research research is multidisciplinary, relying on both Carcinogenesis, microRNA, Chromosomal rearrangement and Immunology. His research in Neuroblastoma intersects with topics in Oncology, Pathology, Internal medicine, Survival analysis and Loss of heterozygosity.

His research investigates the connection between Molecular biology and topics such as Regulation of gene expression that intersect with problems in Transcriptome. Franki Speleman has included themes like Microarray analysis techniques, Real-time polymerase chain reaction and Computational biology in his Gene expression profiling study. His studies in Microarray analysis techniques integrate themes in fields like Housekeeping gene and Proportional hazards model.

His most cited work include:

  • Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes (14653 citations)
  • qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data (2808 citations)
  • Gain of chromosome arm 17q and adverse outcome in patients with neuroblastoma (409 citations)

What are the main themes of his work throughout his whole career to date?

His primary areas of investigation include Cancer research, Genetics, Neuroblastoma, Gene and Molecular biology. His work investigates the relationship between Cancer research and topics such as microRNA that intersect with problems in Gene silencing. His studies examine the connections between Neuroblastoma and genetics, as well as such issues in Pathology, with regards to Internal medicine.

The concepts of his Gene study are interwoven with issues in Computational biology and Cell biology. His study looks at the relationship between Molecular biology and fields such as Cytogenetics, as well as how they intersect with chemical problems. Franki Speleman has researched Gene expression in several fields, including RNA and Real-time polymerase chain reaction.

He most often published in these fields:

  • Cancer research (30.84%)
  • Genetics (29.67%)
  • Neuroblastoma (28.74%)

What were the highlights of his more recent work (between 2015-2021)?

  • Cancer research (30.84%)
  • Neuroblastoma (28.74%)
  • Cell biology (8.64%)

In recent papers he was focusing on the following fields of study:

Franki Speleman focuses on Cancer research, Neuroblastoma, Cell biology, Gene and Computational biology. His Cancer research research is multidisciplinary, incorporating perspectives in Genetics, Leukemia, Signal transduction, Gene knockdown and Non invasive. Franki Speleman is interested in Long non-coding RNA, which is a branch of Genetics.

His Neuroblastoma study combines topics in areas such as Phenotype, Circulating Cell-Free DNA, Downregulation and upregulation, FOXM1 and Epigenetics. His research on Gene frequently connects to adjacent areas such as Cell growth. His Computational biology course of study focuses on Zebrafish and Real-time polymerase chain reaction.

Between 2015 and 2021, his most popular works were:

  • A mechanistic classification of clinical phenotypes in neuroblastoma (74 citations)
  • Shallow Whole Genome Sequencing on Circulating Cell-Free DNA Allows Reliable Noninvasive Copy-Number Profiling in Neuroblastoma Patients (55 citations)
  • Long noncoding RNA expression profiling in cancer: Challenges and opportunities. (54 citations)

In his most recent research, the most cited papers focused on:

  • Gene
  • Cancer
  • DNA

His scientific interests lie mostly in Cancer research, Neuroblastoma, Gene, microRNA and RNA. His Cancer research research integrates issues from Molecular biology, Stem cell, N-Myc, FOXM1 and Leukemia. His Neuroblastoma study integrates concerns from other disciplines, such as Viability assay, Regulation of gene expression and Pharmacology.

His study ties his expertise on Computational biology together with the subject of Gene. The Computational biology study combines topics in areas such as Three prime untranslated region, Real-time polymerase chain reaction, Zebrafish and Gene expression profiling. MicroRNA is a subfield of Genetics that Franki Speleman investigates.

Best Publications

  • Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes

    Jo Vandesompele;Katleen De Preter;Filip Pattyn;Bruce Poppe

  • qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data

    Jan Hellemans;Geert Mortier;Anne De Paepe;Franki Speleman

  • miR-9, a MYC/MYCN-activated microRNA, regulates E-cadherin and cancer metastasis

    Li Ma;Jennifer Young;Harsha Prabhala;Elizabeth Pan

  • Identification of ALK as a major familial neuroblastoma predisposition gene

    Yaël P. Mossé;Marci Laudenslager;Luca Longo;Kristina A. Cole

  • A novel and universal method for microRNA RT-qPCR data normalization

    Pieter Mestdagh;Pieter Van Vlierberghe;An-Sofie De Weer;Daniel Muth

  • Loss-of-function mutations in FGFR1 cause autosomal dominant Kallmann syndrome.

    Catherine Dodé;Jacqueline Levilliers;Jean-Michel Dupont;Anne De Paepe

  • Recurrent Rearrangements of Chromosome 1q21.1 and Variable Pediatric Phenotypes

    Heather C Mefford;Andrew J Sharp;Carl Baker;Andy Itsara

  • Gain of chromosome arm 17q and adverse outcome in patients with neuroblastoma

    N Bown;S Cotterill;M Lastowska;S O'Neill

  • RNA G-quadruplexes cause eIF4A-dependent oncogene translation in cancer

    Andrew L Wolfe;Kamini Singh;Yi Zhong;Philipp Drewe

  • Exhaustive mutation analysis of the NF1 gene allows identification of 95% of mutations and reveals a high frequency of unusual splicing defects.

    Ludwine M. Messiaen;Tom Callens;Geert Mortier;Diane Beysen

  • Genome dynamics of the human embryonic kidney 293 lineage in response to cell biology manipulations.

    Yao-Cheng Lin;Morgane Boone;Leander Meuris;Irma Lemmens

  • EWS and ATF-1 gene fusion induced by t(12;22) translocation in malignant melanoma of soft parts

    Jessica Zucman;Olivier Delattre;Chantal Desmaze;Alan L. Epstein

  • Loss-of-function mutations in LEMD3 result in osteopoikilosis, Buschke-Ollendorff syndrome and melorheostosis.

    Jan Hellemans;Olena Preobrazhenska;Andy Willaert;Philippe Debeer

  • International consensus for neuroblastoma molecular diagnostics: report from the International Neuroblastoma Risk Group (INRG) Biology Committee.

    PF Ambros;IM Ambros;GM Brodeur;M Haber

  • LIN28B induces neuroblastoma and enhances MYCN levels via let-7 suppression

    Jan J Molenaar;Raquel Domingo-Fernández;Marli E Ebus;Sven Lindner

  • Emerging patterns of cryptic chromosomal imbalance in patients with idiopathic mental retardation and multiple congenital anomalies: a new series of 140 patients and review of published reports

    B. Menten;N. Maas;B. Thienpont;K. Buysse

  • Overall Genomic Pattern Is a Predictor of Outcome in Neuroblastoma

    Isabelle Janoueix-Lerosey;Gudrun Schleiermacher;Evi Michels;Véronique Mosseri

  • High-throughput stem-loop RT-qPCR miRNA expression profiling using minute amounts of input RNA

    Pieter Mestdagh;Tom Feys;Nathalie Bernard;Simone Guenther

  • The miR-17-92 MicroRNA Cluster Regulates Multiple Components of the TGF-β Pathway in Neuroblastoma

    Pieter Mestdagh;Anna-Karin Bostrom;Francis Impens;Erik Fredlund;Erik Fredlund

  • Mutational dynamics between primary and relapse neuroblastomas

    Alexander Schramm;Johannes Köster;Johannes Köster;Yassen Assenov;Kristina Althoff

Frequent Co-Authors

Jo Vandesompele
Jo Vandesompele Ghent University
Katleen De Preter
Katleen De Preter Ghent University
Nadine Van Roy
Nadine Van Roy Ghent University
Anne De Paepe
Anne De Paepe Ghent University Hospital
Bruce Poppe
Bruce Poppe Ghent University Hospital
Genevieve Laureys
Genevieve Laureys Ghent University Hospital
Pieter Mestdagh
Pieter Mestdagh Ghent University
Björn Menten
Björn Menten Ghent University Hospital
Johannes H. Schulte
Johannes H. Schulte Charité - University Medicine Berlin
Rogier Versteeg
Rogier Versteeg University of Amsterdam

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Many professionals begin their journey with a online nursing degree, making it a widely accessible entry point into healthcare and research careers. No matter which online pathway you choose, integrating genetics knowledge with a nursing background can provide a competitive advantage in the rapidly evolving world of healthcare.

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