David Gacquer

1.2k citations
18 papers · 766 indexed · h-index 11

Impact in

Papers in

    • RNA Research and Splicing 3
    • Gene expression and cancer classification 3
    • Genomics and Chromatin Dynamics 2
    • Molecular Biology Techniques and Applications 2
    • RNA modifications and cancer 2
    • Bioinformatics and Genomic Networks 2
    • Thyroid Cancer Diagnosis and Treatment 4

David Gacquer

16 papers receiving 755 citations

Peers

David Gacquer
Comparison fields: 5 of 92
  • Developmental Neuroscience 75
  • Cancer Research 166
  • Molecular Biology 582
  • Endocrinology, Diabetes and Metabolism 101
  • Aging 10
Replace Stefanie Engler with:
Stefanie Engler Switzerland
Philip Brennecke Germany
Daniel G. Pankratz United States
Melissa Hancock United States
Holger Hiemisch Germany
Rongxin Fang United States
Vida Senkus Melvin United States
Ena Ladi United States
Nicole Assard France
Siavash Fazel Darbandi United States
David Gacquer relative to Stefanie Engler Switzerland Stefanie Engler's profile →
Citations per field
00.5×4.3×
Stefanie Engler · 1×
Citations per year

Countries citing papers authored by David Gacquer

Since Specialization
Citations

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

Fields of papers citing papers by David Gacquer

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Gacquer, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with David Gacquer Line = papers co-authored together David Gacquer links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2018255
2 2015171
3 2012106
4 201557
5 201442
6 201837
7 201523
8 201517
9 201815
10 201114
11 201810
12
Detection of defective sources with belief function s
20089
13 20196
14 20221
15 20061
16 20121
17
A genetic approach for training diverse classifier ensembles
20081
18 20220

About David Gacquer

David Gacquer is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism, Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Management Science and Operations Research, having authored 18 papers that have together received 766 indexed citations. Recurring topics across this work include Thyroid Cancer Diagnosis and Treatment (4 papers), RNA Research and Splicing (3 papers), Gene expression and cancer classification (3 papers), Genomics and Chromatin Dynamics (2 papers), Molecular Biology Techniques and Applications (2 papers), Multi-Criteria Decision Making (2 papers), RNA modifications and cancer (2 papers) and Bioinformatics and Genomic Networks (2 papers). The work is most often cited by research in Developmental Neuroscience (75 citations), Cancer Research (166 citations), Molecular Biology (582 citations), Endocrinology, Diabetes and Metabolism (101 citations) and Aging (10 citations). David Gacquer has collaborated with scholars based in Belgium, France and United States. Frequent co-authors include Vincent Detours, Carine Maenhaut, Ikuo Suzuki, Franck Polleux, Adèle Herpoel, Devesh Kumar, Marta Wojno, Julian Chéron, Roxane Van Heurck and Pierre Vanderhaeghen. Their work appears in journals such as BMC Genomics, Cancer Research, The Journal of Clinical Endocrinology & Metabolism, Genes Chromosomes and Cancer and Scientific Reports.

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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