Beate Sick

2.1k total citations
42 papers, 1.4k citations indexed

About

Beate Sick is a scholar working on Molecular Biology, Biophysics and Artificial Intelligence. According to data from OpenAlex, Beate Sick has authored 42 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 9 papers in Biophysics and 7 papers in Artificial Intelligence. Recurrent topics in Beate Sick's work include Advanced Fluorescence Microscopy Techniques (7 papers), Gene expression and cancer classification (5 papers) and Acute Ischemic Stroke Management (5 papers). Beate Sick is often cited by papers focused on Advanced Fluorescence Microscopy Techniques (7 papers), Gene expression and cancer classification (5 papers) and Acute Ischemic Stroke Management (5 papers). Beate Sick collaborates with scholars based in Switzerland, United States and Germany. Beate Sick's co-authors include Bert Hecht, Lukáš Novotný, Urs P. Wild, Oliver Dürr, Steffen Heber, Michael Prummer, Christian Fokas, Volker Deckert, Raoul M. Stöckle and Renato Zenobi and has published in prestigious journals such as Physical Review Letters, JAMA and Nucleic Acids Research.

In The Last Decade

Beate Sick

41 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Beate Sick Switzerland 19 512 370 351 305 259 42 1.4k
J.J. Vaquero Spain 30 938 1.8× 509 1.4× 411 1.2× 461 1.5× 134 0.5× 205 4.0k
Amit Mehta United States 22 672 1.3× 880 2.4× 988 2.8× 342 1.1× 288 1.1× 53 3.1k
Maria Filomena Santarelli Italy 24 274 0.5× 151 0.4× 159 0.5× 189 0.6× 100 0.4× 148 2.3k
Dan Ma United States 35 247 0.5× 532 1.4× 125 0.4× 247 0.8× 127 0.5× 91 4.5k
Kyoung Jin Lee South Korea 19 554 1.1× 345 0.9× 206 0.6× 99 0.3× 155 0.6× 58 1.8k
L Hirvonen United Kingdom 20 430 0.8× 148 0.4× 237 0.7× 598 2.0× 183 0.7× 93 1.5k
Hiroyuki Yokoyama Japan 24 248 0.5× 767 2.1× 115 0.3× 231 0.8× 714 2.8× 81 1.6k
Dvir Yelin Israel 26 1.1k 2.1× 847 2.3× 330 0.9× 688 2.3× 312 1.2× 70 2.3k
Gregory J. Metzger United States 31 499 1.0× 482 1.3× 402 1.1× 257 0.8× 97 0.4× 104 3.3k
İkbal Şencan United States 16 1.0k 2.0× 643 1.7× 341 1.0× 503 1.6× 183 0.7× 38 1.8k

Countries citing papers authored by Beate Sick

Since Specialization
Citations

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

Fields of papers citing papers by Beate Sick

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Beate Sick

This figure shows the co-authorship network connecting the top 25 collaborators of Beate Sick. A scholar is included among the top collaborators of Beate Sick 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 Beate Sick. Beate Sick 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.
Kook, Lucas, et al.. (2024). Estimating Conditional Distributions with Neural Networks Using R Package deeptrafo. Journal of Statistical Software. 111(10).
2.
Kook, Lucas, Janne Hamann, Christoph Globas, et al.. (2023). Deep Learning Versus Neurologists: Functional Outcome Prediction in LVO Stroke Patients Undergoing Mechanical Thrombectomy. Stroke. 54(7). 1761–1769. 18 indexed citations
3.
Kook, Lucas, Beate Sick, & Peter Bühlmann. (2022). Distributional anchor regression. Statistics and Computing. 32(3). 39–39. 4 indexed citations
4.
Sick, Beate, et al.. (2021). Deep transformation models. URN-Resolver at the German National Library (German National Library). 6 indexed citations
5.
Kook, Lucas, et al.. (2020). Ordinal Neural Network Transformation Models: Deep and interpretable regression models for ordinal outcomes.. arXiv (Cornell University). 1 indexed citations
6.
Dürr, Oliver, et al.. (2020). Integrating uncertainty in deep neural networks for MRI based stroke analysis. Medical Image Analysis. 65. 101790–101790. 43 indexed citations
7.
Hartnack, Sonja, et al.. (2020). A prospective observational study on trajectories and prognostic factors of mid back pain. BMC Musculoskeletal Disorders. 21(1). 554–554. 3 indexed citations
8.
Dürr, Oliver, et al.. (2018). Know When You Don't Know: A Robust Deep Learning Approach in the Presence of Unknown Phenotypes. Assay and Drug Development Technologies. 16(6). 343–349. 10 indexed citations
9.
Heyse, Stephan, et al.. (2018). Developing Deep Learning Applications for Life Science and Pharma Industry. Drug Research. 68(6). 305–310. 7 indexed citations
10.
Porz, Nicole, Urspeter Knecht, Beate Sick, et al.. (2018). Computer-aided radiological diagnostics improves the preoperative diagnoses of medulloblastoma, pilocytic astrocytoma, and ependymoma. 2(2). 2514183X1878660–2514183X1878660. 2 indexed citations
11.
12.
Natalucci, Giancarlo, Beatrice Latal, Brigitte Koller, et al.. (2016). Effect of Early Prophylactic High-Dose Recombinant Human Erythropoietin in Very Preterm Infants on Neurodevelopmental Outcome at 2 Years. JAMA. 315(19). 2079–2079. 83 indexed citations
13.
Dürr, Oliver & Beate Sick. (2016). Single-Cell Phenotype Classification Using Deep Convolutional Neural Networks. SLAS DISCOVERY. 21(9). 998–1003. 60 indexed citations
14.
Schneider, Juliane, Beate Sick, Andreas R. Luft, & Susanne Wegener. (2015). Ultrasound and Clinical Predictors of Recurrent Ischemia in Symptomatic Internal Carotid Artery Occlusion. Stroke. 46(11). 3274–3276. 15 indexed citations
15.
Sick, Beate, et al.. (2008). A New Method for Travel Time Estimation on Long Freeway Sections. European journal of transport and infrastructure research. 4 indexed citations
16.
Heber, Steffen & Beate Sick. (2006). Automatic quality assessment of Affymetrix GeneChip data. Zürcher Hochschule für Angewandte Wissenschaften digital collection (Zurich University of Applied Sciences). 411–416. 2 indexed citations
17.
Heber, Steffen & Beate Sick. (2006). Quality Assessment of Affymetrix GeneChip Data. OMICS A Journal of Integrative Biology. 10(3). 358–368. 84 indexed citations
18.
Heber, Steffen, et al.. (2005). RACE: Remote Analysis Computation for gene Expression data. Nucleic Acids Research. 33(Web Server). W638–W643. 52 indexed citations
19.
Prummer, Michael, et al.. (2003). The Citrate Carrier CitS Probed by Single-Molecule Fluorescence Spectroscopy. Biophysical Journal. 84(3). 1651–1659. 18 indexed citations
20.
Sick, Beate, Bert Hecht, Urs P. Wild, & Lukáš Novotný. (2001). Probing confined fields with single molecules and vice versa. Journal of Microscopy. 202(2). 365–373. 49 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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