Thomas Walter

8.0k total citations · 2 hit papers
79 papers, 3.7k citations indexed

About

Thomas Walter is a scholar working on Molecular Biology, Biophysics and Artificial Intelligence. According to data from OpenAlex, Thomas Walter has authored 79 papers receiving a total of 3.7k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 22 papers in Biophysics and 19 papers in Artificial Intelligence. Recurrent topics in Thomas Walter's work include Cell Image Analysis Techniques (21 papers), Single-cell and spatial transcriptomics (13 papers) and Security and Verification in Computing (9 papers). Thomas Walter is often cited by papers focused on Cell Image Analysis Techniques (21 papers), Single-cell and spatial transcriptomics (13 papers) and Security and Verification in Computing (9 papers). Thomas Walter collaborates with scholars based in France, Germany and United Kingdom. Thomas Walter's co-authors include Ali Erginay, Pascale Massin, J.C. Klein, Peter Naylor, Fabien Reyal, Marick Laé, Jan Ellenberg, Beate Neumann, Michael Held and Richard C. Ordoñez and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and The Journal of Experimental Medicine.

In The Last Decade

Thomas Walter

74 papers receiving 3.5k citations

Hit Papers

A contribution of image processing to the diagnosis of di... 2002 2026 2010 2018 2002 2018 200 400 600
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.

  1. A contribution of image processing to the diagnosis of diabetic retinopathy-detection of exudates in color fundus images of the human retina
    2002 624 citations Thomas Walter et al. profile →
  2. Segmentation of Nuclei in Histopathology Images by Deep Regression of the Distance Map
    2018 397 citations Peter Naylor, Fabien Reyal et al. profile →

Peers

Thomas Walter
Ali Can United States
Cheng Lu China
I. Goldberg United States
Xiaobo Zhou United States
David J. Foran United States
Jun Kong United States
Hong Liu United States
Hwee Kuan Lee Singapore
Lin Gu Japan
Ali Can United States
Thomas Walter
Citations per year, relative to Thomas Walter Thomas Walter (= 1×) peers Ali Can

Countries citing papers authored by Thomas Walter

Since Specialization
Citations

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

Fields of papers citing papers by Thomas Walter

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Walter

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Walter. A scholar is included among the top collaborators of Thomas Walter 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 Thomas Walter. Thomas Walter 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.
2.
Lerousseau, Marvin, Fanny Orlhac, Christine Lonjou, et al.. (2025). Integration of clinical, pathological, radiological, and transcriptomic data improves prediction for first-line immunotherapy outcome in metastatic non-small cell lung cancer. Nature Communications. 16(1). 614–614. 13 indexed citations
3.
Berlemont, Sylvain, et al.. (2023). Diagnosis with confidence: deep learning for reliable classification of laryngeal dysplasia. Histopathology. 84(2). 343–355. 5 indexed citations
4.
Curras-Alonso, Sandra, Christian Weber, Sophie Heinrich, et al.. (2023). An interactive murine single-cell atlas of the lung responses to radiation injury. Nature Communications. 14(1). 2445–2445. 37 indexed citations
5.
Ribeiro, Susana A., et al.. (2023). Cell segmentation in images without structural fluorescent labels. SHILAP Revista de lepidopterología. 3. e16–e16. 1 indexed citations
6.
Bataillon, Guillaume, Peter Naylor, Tatiana Popova, et al.. (2022). Deep learning identifies morphological patterns of homologous recombination deficiency in luminal breast cancers from whole slide images. Cell Reports Medicine. 3(12). 100872–100872. 33 indexed citations
7.
Imbert, Arthur, Wei Ouyang, Adham Safieddine, et al.. (2022). FISH-quant v2: a scalable and modular tool for smFISH image analysis. RNA. 28(6). 786–795. 64 indexed citations
8.
Safieddine, Adham, Emeline Coleno, Frédéric Lionneton, et al.. (2022). HT-smFISH: a cost-effective and flexible workflow for high-throughput single-molecule RNA imaging. Nature Protocols. 18(1). 157–187. 26 indexed citations
9.
Safieddine, Adham, Emeline Coleno, Arthur Imbert, et al.. (2021). A choreography of centrosomal mRNAs reveals a conserved localization mechanism involving active polysome transport. Nature Communications. 12(1). 1352–1352. 59 indexed citations
10.
Pichon, Xavier, Konstadinos Moissoglu, Emeline Coleno, et al.. (2021). The kinesin KIF1C transports APC-dependent mRNAs to cell protrusions. RNA. 27(12). 1528–1544. 32 indexed citations
11.
Lundberg, Emma, Jan Funke, Virginie Uhlmann, et al.. (2021). Which image-based phenotypes are most promising for using AI to understand cellular functions and why?. Cell Systems. 12(5). 384–387. 1 indexed citations
12.
Curras-Alonso, Sandra, et al.. (2021). Spatial transcriptomics for respiratory research and medicine. European Respiratory Journal. 58(1). 2004314–2004314. 2 indexed citations
13.
Boyd, Joseph, et al.. (2019). Domain-invariant features for mechanism of action prediction in a multi-cell-line drug screen. Bioinformatics. 36(5). 1607–1613. 7 indexed citations
14.
Samacoïts, Aubin, Racha Chouaib, Adham Safieddine, et al.. (2018). A computational framework to study sub-cellular RNA localization. Nature Communications. 9(1). 4584–4584. 41 indexed citations
15.
Bernard, Elsa, et al.. (2017). Kernel Multitask Regression for Toxicogenetics. Molecular Informatics. 36(10). 4 indexed citations
16.
Neumann, Beate, et al.. (2014). MAP1S controls microtubule stability throughout the cell cycle in human cells. Journal of Cell Science. 127(Pt 23). 5007–13. 16 indexed citations
17.
Conrad, Christian, Tze Heng Tan, Jutta Bulkescher, et al.. (2011). Micropilot: automation of fluorescence microscopy–based imaging for systems biology. Nature Methods. 8(3). 246–249. 100 indexed citations
18.
Pretschner, Alexander, et al.. (2009). Usage Control Enforcement with Data Flow Tracking for X11. 20 indexed citations
19.
Simonis, Georg & Thomas Walter. (2006). LernOrt Universität : Umbruch durch Internationalisierung und Multimedia. VS Verlag für Sozialwissenschaften eBooks. 1 indexed citations
20.
Walter, Thomas & Jens Grabowski. (1997). Test Case Specification with Real-time TTCN.. 231–240.

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Ali Can Breakdown of academic impact, for papers by Cheng Lu Breakdown of academic impact, for papers by I. Goldberg Breakdown of academic impact, for papers by Xiaobo Zhou Breakdown of academic impact, for papers by David J. Foran Breakdown of academic impact, for papers by Jun Kong Breakdown of academic impact, for papers by Hong Liu Breakdown of academic impact, for papers by Hwee Kuan Lee Breakdown of academic impact, for papers by Lin Gu
Rankless by CCL
2026