Jo Vandesompele

74.9k total citations · 10 hit papers
299 papers, 50.4k citations indexed

About

Jo Vandesompele is a scholar working on Molecular Biology, Cancer Research and Neurology. According to data from OpenAlex, Jo Vandesompele has authored 299 papers receiving a total of 50.4k indexed citations (citations by other indexed papers that have themselves been cited), including 229 papers in Molecular Biology, 119 papers in Cancer Research and 86 papers in Neurology. Recurrent topics in Jo Vandesompele's work include Neuroblastoma Research and Treatments (83 papers), Molecular Biology Techniques and Applications (71 papers) and Cancer-related molecular mechanisms research (58 papers). Jo Vandesompele is often cited by papers focused on Neuroblastoma Research and Treatments (83 papers), Molecular Biology Techniques and Applications (71 papers) and Cancer-related molecular mechanisms research (58 papers). Jo Vandesompele collaborates with scholars based in Belgium, United States and Germany. Jo Vandesompele's co-authors include Katleen De Preter, Anne De Paepe, Filip Pattyn, Nadine Van Roy, Frank Speleman, Bruce Poppe, Jan Hellemans, Michael W. Pfaffl, Stephen A. Bustin and Jim F. Huggett and has published in prestigious journals such as Chemical Society Reviews, Nucleic Acids Research and Nature Genetics.

In The Last Decade

Jo Vandesompele

294 papers receiving 49.8k citations

Hit Papers

align trajectories sort by overperformance

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.

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

2002 16.7k citations Jo Vandesompele, Katleen De Preter et al. profile →
The MIQE Guidelines: Minimum Information for Publication of Quantitative Real-Time PCR Experiments

2009 12.4k citations Vladimı́r Beneš, Jo Vandesompele et al. profile →
qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data

2007 3.4k citations Geert Mortier, Frank Speleman et al. profile →
miR-9, a MYC/MYCN-activated microRNA, regulates E-cadherin and cancer metastasis

2010 1.1k citations Pieter Mestdagh, Frank Westermann et al. profile →
A novel and universal method for microRNA RT-qPCR data normalization

2009 841 citations Pieter Mestdagh, Pieter Van Vlierberghe et al. profile →
The impact of disparate isolation methods for extracellular vesicles on downstream RNA profiling

2014 755 citations Pieter Mestdagh, Véronique Cocquyt et al. profile →
The Digital MIQE Guidelines: Minimum Information for Publication of Quantitative Digital PCR Experiments

2013 646 citations Vladimı́r Beneš, Jo Vandesompele et al. profile →
How to do successful gene expression analysis using real-time PCR

2009 585 citations Jo Vandesompele et al. profile →
LNCipedia 5: towards a reference set of human long non-coding RNAs

2018 368 citations Pieter‐Jan Volders, Jasper Anckaert et al. Nucleic Acids Research profile →
MIQE 2.0: Revision of the Minimum Information for Publication of Quantitative Real-Time PCR Experiments Guidelines

2025 22 citations Jo Vandesompele et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jo Vandesompele Belgium	70	29.8k	11.2k	5.6k	5.3k	4.5k	299	50.4k
Damian Szklarczyk Switzerland	32	31.9k 1.1×	6.7k 0.6×	4.9k 0.9×	4.5k 0.9×	4.8k 1.1×	43	51.0k
Guangchuang Yu China	33	23.6k 0.8×	8.1k 0.7×	4.2k 0.8×	4.0k 0.7×	6.5k 1.4×	82	41.8k
Michael I. Love United States	31	39.1k 1.3×	8.9k 0.8×	11.3k 2.0×	7.0k 1.3×	8.8k 2.0×	93	68.1k
Wei Shi Australia	39	29.5k 1.0×	9.2k 0.8×	4.4k 0.8×	4.7k 0.9×	10.1k 2.2×	94	51.3k
Mark D. Robinson Switzerland	57	29.2k 1.0×	7.4k 0.7×	6.7k 1.2×	5.5k 1.0×	5.5k 1.2×	173	46.9k
T Gingeras United States	65	33.3k 1.1×	8.4k 0.8×	5.1k 0.9×	7.0k 1.3×	7.7k 1.7×	134	51.6k
Brad T. Sherman United States	23	37.7k 1.3×	11.4k 1.0×	2.8k 0.5×	7.7k 1.5×	7.0k 1.5×	43	59.6k
Michael W. Pfaffl Germany	47	30.7k 1.0×	6.1k 0.5×	9.5k 1.7×	6.7k 1.3×	7.1k 1.6×	247	62.0k
Da Wei Huang United States	27	28.2k 0.9×	8.6k 0.8×	2.4k 0.4×	5.7k 1.1×	5.4k 1.2×	69	45.1k
Richard A. Lempicki United States	46	36.6k 1.2×	11.0k 1.0×	2.6k 0.5×	7.5k 1.4×	8.5k 1.9×	130	60.5k

Countries citing papers authored by Jo Vandesompele

Since Specialization

Citations

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

Fields of papers citing papers by Jo Vandesompele

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jo Vandesompele

This figure shows the co-authorship network connecting the top 25 collaborators of Jo Vandesompele. A scholar is included among the top collaborators of Jo Vandesompele 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 Jo Vandesompele. Jo Vandesompele is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Chen, Yao, Ward De Spiegelaere, Matthijs Vynck, et al.. (2025). Flexible methods for uncertainty estimation of digital PCR data. iScience. 28(3). 111772–111772. 1 indexed citations

Meuris, Leander, Olivier Thas, Lieven Depypere, et al.. (2024). Therapy response monitoring in blood plasma from esophageal adenocarcinoma patients using cell-free DNA methylation profiling. Scientific Reports. 14(1). 31112–31112.

Helsmoortel, Céline, Pieter‐Jan Volders, Jo Vandesompele, et al.. (2022). Performance Evaluation of Three DNA Sample Tracking Tools in a Whole Exome Sequencing Workflow. Molecular Diagnosis & Therapy. 26(4). 411–419. 2 indexed citations

Vandesompele, Jo, et al.. (2020). SPsimSeq: semi-parametric simulation of bulk and single-cell RNA-sequencing data. Bioinformatics. 36(10). 3276–3278. 26 indexed citations

Verboom, Karen, Celine Everaert, Nathalie Bolduc, et al.. (2019). SMARTer single cell total RNA sequencing. Nucleic Acids Research. 47(16). e93–e93. 35 indexed citations

Conickx, Griet, Pieter Mestdagh, Francisco Avila Cobos, et al.. (2016). MicroRNA Profiling Reveals a Role for MicroRNA-218-5p in the Pathogenesis of Chronic Obstructive Pulmonary Disease. American Journal of Respiratory and Critical Care Medicine. 195(1). 43–56. 99 indexed citations

Mets, Evelien, Joni Van der Meulen, Gert Van Peer, et al.. (2014). MicroRNA-193b-3p acts as a tumor suppressor by targeting the MYB oncogene in T-cell acute lymphoblastic leukemia. Leukemia. 29(4). 798–806. 88 indexed citations

Lapeire, Lore, An Hendrix, Kathleen Lambein, et al.. (2014). Cancer-Associated Adipose Tissue Promotes Breast Cancer Progression by Paracrine Oncostatin M and Jak/STAT3 Signaling. Cancer Research. 74(23). 6806–6819. 116 indexed citations

Beckers, Anneleen, Andrew D. Ludwig, Gert Van Peer, et al.. (2014). The MYCN/miR-26a-5p/LIN28B regulatory axis controls MYCN-driven LIN28B upregulation in neuroblastoma. Ghent University Academic Bibliography (Ghent University). 1 indexed citations

10.

Schulte, Johannes H., Lukas C. Heukamp, Theresa Thor, et al.. (2012). ALK(F1174L) is a driving oncogene of neuroblastoma in transgenic mice. Pediatric Blood & Cancer. 59(6). 989–989. 1 indexed citations

11.

Maerken, Tom Van, Ali Rihani, Daniel Dreidax, et al.. (2011). Functional Analysis of the p53 Pathway in Neuroblastoma Cells Using the Small-Molecule MDM2 Antagonist Nutlin-3. Molecular Cancer Therapeutics. 10(6). 983–993. 61 indexed citations

12.

Schulte, Johannes H., Hagen S. Bachmann, Katleen De Preter, et al.. (2011). High ALK Receptor Tyrosine Kinase Expression Supersedes ALK Mutation as a Determining Factor of an Unfavorable Phenotype in Primary Neuroblastoma. Clinical Cancer Research. 17(15). 5082–5092. 72 indexed citations

13.

Preter, Katleen De, Joëlle Vermeulen, Benedikt Brors, et al.. (2010). Accurate Outcome Prediction in Neuroblastoma across Independent Data Sets Using a Multigene Signature. Clinical Cancer Research. 16(5). 1532–1541. 65 indexed citations

14.

Buckley, Patrick G., Leah Alcock, Kenneth Bryan, et al.. (2010). Chromosomal and MicroRNA Expression Patterns Reveal Biologically Distinct Subgroups of 11q− Neuroblastoma. Clinical Cancer Research. 16(11). 2971–2978. 54 indexed citations

15.

Pottelberge, Geert R. Van, Pieter Mestdagh, Ken R. Bracke, et al.. (2010). MicroRNA Expression in Induced Sputum of Smokers and Patients with Chronic Obstructive Pulmonary Disease. American Journal of Respiratory and Critical Care Medicine. 183(7). 898–906. 195 indexed citations

16.

Preter, Katleen De, Sara De Brouwer, Tom Van Maerken, et al.. (2009). Meta-mining of Neuroblastoma and Neuroblast Gene Expression Profiles Reveals Candidate Therapeutic Compounds. Clinical Cancer Research. 15(11). 3690–3696. 37 indexed citations

17.

Mestdagh, Pieter, Tom Feys, Nathalie Bernard‐Marissal, et al.. (2008). High-throughput stem-loop RT-PCR miRNA expression profiling using minute amounts of input RNA. Ghent University Academic Bibliography (Ghent University). 1 indexed citations

18.

Menten, Björn, Karen Buysse, Stefan Vermeulen, et al.. (2007). Report of a female patient with mental retardation and tall stature due to a chromosomal rearrangement disrupting the OPHN1 gene on Xq12. European Journal of Medical Genetics. 50(6). 446–454. 11 indexed citations

19.

Maerken, Tom Van, Frank Speleman, Joëlle Vermeulen, et al.. (2006). Small-Molecule MDM2 Antagonists as a New Therapy Concept for Neuroblastoma. Cancer Research. 66(19). 9646–9655. 120 indexed citations

20.

Gantois, Ilse, Jo Vandesompele, Frank Speleman, et al.. (2005). Expression profiling suggests underexpression of the GABAA receptor subunit δ in the fragile X knockout mouse model. Neurobiology of Disease. 21(2). 346–357. 129 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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