Robrecht Cannoodt

6.1k total citations · 3 hit papers
20 papers, 2.5k citations indexed

About

Robrecht Cannoodt is a scholar working on Molecular Biology, Biophysics and Immunology. According to data from OpenAlex, Robrecht Cannoodt has authored 20 papers receiving a total of 2.5k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 3 papers in Biophysics and 2 papers in Immunology. Recurrent topics in Robrecht Cannoodt's work include Single-cell and spatial transcriptomics (10 papers), Gene Regulatory Network Analysis (6 papers) and Bioinformatics and Genomic Networks (5 papers). Robrecht Cannoodt is often cited by papers focused on Single-cell and spatial transcriptomics (10 papers), Gene Regulatory Network Analysis (6 papers) and Bioinformatics and Genomic Networks (5 papers). Robrecht Cannoodt collaborates with scholars based in Belgium, United States and France. Robrecht Cannoodt's co-authors include Yvan Saeys, Wouter Saelens, Helena Todorov, Gert Hulselmans, Dries De Maeyer, Christopher Flerin, Maxime De Waegeneer, Joke Reumers, Stein Aerts and Sara Aibar and has published in prestigious journals such as Nature Communications, Nature Biotechnology and Bioinformatics.

In The Last Decade

Robrecht Cannoodt

17 papers receiving 2.4k citations

Hit Papers

A comparison of single-cell trajectory inference methods 2019 2026 2021 2023 2019 2020 2020 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Robrecht Cannoodt Belgium 10 1.9k 561 403 326 237 20 2.5k
Romain Lopez United States 8 2.3k 1.2× 652 1.2× 495 1.2× 490 1.5× 254 1.1× 12 2.9k
Laleh Haghverdi Germany 9 2.5k 1.3× 637 1.1× 491 1.2× 557 1.7× 250 1.1× 14 3.1k
Maren Büttner Germany 16 2.2k 1.1× 489 0.9× 422 1.0× 514 1.6× 240 1.0× 27 2.7k
Marco Mignardi Sweden 11 1.4k 0.7× 604 1.1× 452 1.1× 187 0.6× 249 1.1× 17 2.2k
Valentine Svensson United Kingdom 14 2.6k 1.3× 594 1.1× 644 1.6× 401 1.2× 267 1.1× 16 3.1k
Marius Lange Germany 7 1.5k 0.8× 476 0.8× 290 0.7× 213 0.7× 232 1.0× 11 2.0k
Kelly Street United States 11 1.5k 0.7× 589 1.0× 329 0.8× 174 0.5× 263 1.1× 15 2.3k
Brian Houck‐Loomis United States 9 2.2k 1.1× 812 1.4× 424 1.1× 302 0.9× 380 1.6× 16 2.7k
Fredrik Salmén Sweden 14 2.0k 1.0× 438 0.8× 524 1.3× 315 1.0× 268 1.1× 15 2.4k
Ludvig Larsson Sweden 20 1.7k 0.9× 429 0.8× 420 1.0× 262 0.8× 246 1.0× 31 2.2k

Countries citing papers authored by Robrecht Cannoodt

Since Specialization
Citations

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

Fields of papers citing papers by Robrecht Cannoodt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Robrecht Cannoodt

This figure shows the co-authorship network connecting the top 25 collaborators of Robrecht Cannoodt. A scholar is included among the top collaborators of Robrecht Cannoodt 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 Robrecht Cannoodt. Robrecht Cannoodt 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.
Li, Zhijian, Z. Patel, Dongyuan Song, et al.. (2025). Systematic benchmarking of computational methods to identify spatially variable genes. Genome biology. 26(1). 285–285.
2.
Cannoodt, Robrecht, et al.. (2024). Viash: A meta-framework for building reusable workflowmodules. The Journal of Open Source Software. 9(93). 6089–6089.
3.
Anchang, Benedict, Robrecht Cannoodt, Mauricio Cortes, et al.. (2024). A benchmark for prediction of transcriptomic responses to chemical perturbations across cell types. 20566–20616. 1 indexed citations
4.
Todorov, Helena, Daphné Laubreton, Shaoying Wang, et al.. (2022). CD8 memory precursor cell generation is a continuous process. iScience. 25(9). 104927–104927. 2 indexed citations
5.
Cannoodt, Robrecht, et al.. (2021). Recent advances in trajectory inference from single-cell omics data. Current Opinion in Systems Biology. 27. 100344–100344. 28 indexed citations
6.
Cannoodt, Robrecht, et al.. (2021). Spearheading future omics analyses using dyngen, a multi-modal simulator of single cells. Nature Communications. 12(1). 3942–3942. 63 indexed citations
7.
Hastie, Trevor, Andreas Weingessel, Kurt Hornik, & Robrecht Cannoodt. (2021). Fit a Principal Curve in Arbitrary Dimension [R package princurve version 2.1.6]. 1 indexed citations
8.
Berge, Koen Van den, Hector Roux de Bézieux, Kelly Street, et al.. (2020). Trajectory-based differential expression analysis for single-cell sequencing data. Nature Communications. 11(1). 1201–1201. 352 indexed citations breakdown →
9.
Sande, Bram Van de, Christopher Flerin, Kristofer Davie, et al.. (2020). A scalable SCENIC workflow for single-cell gene regulatory network analysis. Nature Protocols. 15(7). 2247–2276. 723 indexed citations breakdown →
10.
Cannoodt, Robrecht & Wouter Saelens. (2020). Dimensionality Reduction Methods in a Common Format [R package dyndimred version 1.0.3]. 1 indexed citations
11.
Todorov, Helena, Robrecht Cannoodt, Wouter Saelens, & Yvan Saeys. (2020). TinGa: fast and flexible trajectory inference with Growing Neural Gas. Bioinformatics. 36(Supplement_1). i66–i74. 16 indexed citations
12.
Saelens, Wouter, Robrecht Cannoodt, Helena Todorov, & Yvan Saeys. (2019). A comparison of single-cell trajectory inference methods. Nature Biotechnology. 37(5). 547–554. 922 indexed citations breakdown →
13.
Pineda‐Krch, Mario & Robrecht Cannoodt. (2019). Gillespie's Stochastic Simulation Algorithm (SSA) [R package GillespieSSA version 0.6.1]. 1 indexed citations
14.
Cannoodt, Robrecht, Joeri Ruyssinck, Jan Ramon, Katleen De Preter, & Yvan Saeys. (2018). IncGraph: Incremental graphlet counting for topology optimisation. PLoS ONE. 13(4). e0195997–e0195997. 2 indexed citations
15.
Saelens, Wouter, Robrecht Cannoodt, & Yvan Saeys. (2018). A comprehensive evaluation of module detection methods for gene expression data. Nature Communications. 9(1). 1090–1090. 171 indexed citations
16.
Todorov, Helena, Robrecht Cannoodt, Wouter Saelens, & Yvan Saeys. (2018). Network Inference from Single-Cell Transcriptomic Data. Methods in molecular biology. 1883. 235–249. 17 indexed citations
17.
Denecker, Geertrui, Robrecht Cannoodt, Candy Kumps, et al.. (2017). Early and late effects of pharmacological ALK inhibition on the neuroblastoma transcriptome. Oncotarget. 8(63). 106820–106832. 2 indexed citations
18.
Cauwenbergh, Caroline Van, Kristof Van Schil, Robrecht Cannoodt, et al.. (2016). arrEYE: a customized platform for high-resolution copy number analysis of coding and noncoding regions of known and candidate retinal dystrophy genes and retinal noncoding RNAs. Genetics in Medicine. 19(4). 457–466. 28 indexed citations
19.
Cannoodt, Robrecht, Wouter Saelens, & Yvan Saeys. (2016). Computational methods for trajectory inference from single‐cell transcriptomics. European Journal of Immunology. 46(11). 2496–2506. 123 indexed citations
20.
Cannoodt, Robrecht, Joeri Ruyssinck, Katleen De Preter, Tom Dhaene, & Yvan Saeys. (2013). Network inference by integrating biclustering and feature selection. Ghent University Academic Bibliography (Ghent University). 33–33. 1 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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