Tim Becker

4.3k total citations · 2 hit papers
33 papers, 2.4k citations indexed

About

Tim Becker is a scholar working on Biophysics, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Tim Becker has authored 33 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Biophysics, 8 papers in Molecular Biology and 7 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Tim Becker's work include Cell Image Analysis Techniques (11 papers), Single-cell and spatial transcriptomics (5 papers) and Digital Radiography and Breast Imaging (5 papers). Tim Becker is often cited by papers focused on Cell Image Analysis Techniques (11 papers), Single-cell and spatial transcriptomics (5 papers) and Digital Radiography and Breast Imaging (5 papers). Tim Becker collaborates with scholars based in Germany, United States and Netherlands. Tim Becker's co-authors include Shantanu Singh, Anne E. Carpenter, Kyle W. Karhohs, Claire McQuin, Allen Goodman, Minh Doan, Beth A. Cimini, Liya Ding, Lee Kamentsky and Derek Thirstrup and has published in prestigious journals such as Nature Communications, Journal of the American College of Cardiology and PLoS ONE.

In The Last Decade

Tim Becker

29 papers receiving 2.3k citations

Hit Papers

CellProfiler 3.0: Next-generation image processing for bi... 2018 2026 2020 2023 2018 2019 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tim Becker Germany 15 913 865 372 365 312 33 2.4k
Claire McQuin United States 8 877 1.0× 870 1.0× 369 1.0× 377 1.0× 306 1.0× 10 2.0k
Minh Doan United States 11 920 1.0× 813 0.9× 330 0.9× 347 1.0× 242 0.8× 21 2.1k
Allen Goodman United States 12 1.4k 1.6× 1.1k 1.3× 409 1.1× 415 1.1× 372 1.2× 18 3.1k
Carolina Wählby Sweden 26 1.7k 1.8× 943 1.1× 475 1.3× 445 1.2× 297 1.0× 101 3.2k
Kyle W. Karhohs United States 10 1.5k 1.6× 850 1.0× 344 0.9× 332 0.9× 276 0.9× 14 2.7k
Vannary Meas‐Yedid France 24 834 0.9× 593 0.7× 165 0.4× 273 0.7× 195 0.6× 47 2.6k
Carsten Marr Germany 27 1.6k 1.7× 543 0.6× 386 1.0× 341 0.9× 117 0.4× 103 3.1k
Shantanu Singh United States 27 1.7k 1.9× 1.8k 2.1× 452 1.2× 494 1.4× 615 2.0× 79 3.8k
Lee Kamentsky United States 13 1.5k 1.7× 984 1.1× 166 0.4× 125 0.3× 213 0.7× 21 2.9k
Tim Wang China 2 877 1.0× 638 0.7× 142 0.4× 135 0.4× 174 0.6× 5 1.7k

Countries citing papers authored by Tim Becker

Since Specialization
Citations

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

Fields of papers citing papers by Tim Becker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tim Becker

This figure shows the co-authorship network connecting the top 25 collaborators of Tim Becker. A scholar is included among the top collaborators of Tim Becker 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 Tim Becker. Tim Becker 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.
Moshkov, Nikita, Tim Becker, Kevin Yang, et al.. (2023). Predicting compound activity from phenotypic profiles and chemical structures. Nature Communications. 14(1). 1967–1967. 40 indexed citations
2.
Rusch, René, G. Hoffmann, Rouven Berndt, et al.. (2023). Roboter und Aorta – Beginn einer neuen Freundschaft?. Gefässchirurgie. 29(1). 18–24.
3.
Becker, Tim, et al.. (2023). SAXRegEx: Multivariate time series pattern search with symbolic representation, regular expression, and query expansion. Computers & Graphics. 112. 13–21. 1 indexed citations
4.
Jiao, Jiao, et al.. (2022). PSEUDo: Interactive Pattern Search in Multivariate Time Series with Locality-Sensitive Hashing and Relevance Feedback. IEEE Transactions on Visualization and Computer Graphics. 29(1). 1–10. 9 indexed citations
5.
Way, Gregory P., Maria Kost‐Alimova, Tsukasa Shibue, et al.. (2021). Predicting cell health phenotypes using image-based morphology profiling. Molecular Biology of the Cell. 32(9). 995–1005. 77 indexed citations
6.
Caicedo, Juan C., Allen Goodman, Kyle W. Karhohs, et al.. (2019). Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl. Nature Methods. 16(12). 1247–1253. 463 indexed citations breakdown →
7.
Wegmann, Michael, Lars Lunding, Christina Vock, et al.. (2018). Tumstatin fragment selectively inhibits neutrophil infiltration in experimental asthma exacerbation. Clinical & Experimental Allergy. 48(11). 1483–1493. 17 indexed citations
8.
McQuin, Claire, Allen Goodman, Vasiliy S. Chernyshev, et al.. (2018). CellProfiler 3.0: Next-generation image processing for biology. PLoS Biology. 16(7). e2005970–e2005970. 1172 indexed citations breakdown →
9.
Florman, Sander, Tim Becker, Barbara A. Bresnahan, et al.. (2016). Efficacy and Safety Outcomes of Extended Criteria Donor Kidneys by Subtype: Subgroup Analysis of BENEFIT-EXT at 7 Years After Transplant. American Journal of Transplantation. 17(1). 180–190. 22 indexed citations
10.
Becker, Tim, et al.. (2014). The benchmark data SET CeTReS.B-MI for in vitro mitosis detection. Publikationsdatenbank der Fraunhofer-Gesellschaft (Fraunhofer-Gesellschaft). 504. 469–472.
11.
Becker, Tim, et al.. (2012). Morphology-based Features for Adaptive Mitosis Detection of In Vitro Stem Cell Tracking Data. Methods of Information in Medicine. 51(5). 449–456. 5 indexed citations
12.
Danner, Sandra, Ziyang Zhang, Úrsula Hopfner, et al.. (2012). The Use of Human Sweat Gland–Derived Stem Cells for Enhancing Vascularization during Dermal Regeneration. Journal of Investigative Dermatology. 132(6). 1707–1716. 42 indexed citations
13.
Becker, Tim, Daniel H. Rapoport, & Amir Madany Mamlouk. (2012). From time lapse-data to genealogic trees: Using different contrast mechanisms to improve cell tracking. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 9. 386–389. 5 indexed citations
14.
Nazirizadeh, Yousef, Tim Becker, Christine Selhuber‐Unkel, et al.. (2012). Photonic crystal slabs for surface contrast enhancement in microscopy of transparent objects. Optics Express. 20(13). 14451–14451. 5 indexed citations
15.
Rapoport, Daniel H., et al.. (2011). A Novel Validation Algorithm Allows for Automated Cell Tracking and the Extraction of Biologically Meaningful Parameters. PLoS ONE. 6(11). e27315–e27315. 45 indexed citations
16.
Schwarz, Anke, et al.. (2008). Course and Relevance of Arteriovenous Fistulas After Renal Transplant Biopsies. American Journal of Transplantation. 8(4). 826–831. 30 indexed citations
17.
Mattos, Angelo M. de, Jonathan C. Prather, Ali J. Olyaei, et al.. (2006). Cardiovascular events following renal transplantation: Role of traditional and transplant-specific risk factors. Kidney International. 70(4). 757–764. 100 indexed citations
19.
Eliason, E. M., James A. Anderson, K. J. Becker, et al.. (2001). ISIS Image Processing Capabilities for MGS/MOC Imaging Data. Lunar and Planetary Science Conference. 2081. 7 indexed citations
20.
Brennecke, Rüdiger, et al.. (2000). American College of Cardiology/ European Society of Cardiology international study of angiographic data compression phase III. Journal of the American College of Cardiology. 35(5). 1388–1397. 13 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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