Thomas Sakoparnig

445 total citations
10 papers, 219 citations indexed

About

Thomas Sakoparnig is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Thomas Sakoparnig has authored 10 papers receiving a total of 219 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Genetics and 3 papers in Cancer Research. Recurrent topics in Thomas Sakoparnig's work include Evolution and Genetic Dynamics (3 papers), Cancer Genomics and Diagnostics (3 papers) and RNA Research and Splicing (2 papers). Thomas Sakoparnig is often cited by papers focused on Evolution and Genetic Dynamics (3 papers), Cancer Genomics and Diagnostics (3 papers) and RNA Research and Splicing (2 papers). Thomas Sakoparnig collaborates with scholars based in Switzerland, Denmark and Singapore. Thomas Sakoparnig's co-authors include Niko Beerenwinkel, Ke Yuan, Florian Markowetz, Erik van Nimwegen, Christopher M. Field, Ewa Szczurek, Christoph Handschin, Balthasar L. Hug, Martin Gerber and Thomas E. Jensen and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Bioinformatics and eLife.

In The Last Decade

Thomas Sakoparnig

10 papers receiving 218 citations

Peers

Thomas Sakoparnig

MB

CR

GENET

PFM

ONCOL

Guangqing Sun China

Joel Nulsen United Kingdom

Melissa delaBastide United States

Ignacio Vázquez-Garćıa United Kingdom

Milad Miladi Germany

Jianan Lin United States

Cristian Caloian Canada

Benjamin Kreck Germany

Carl Murie Canada

Paulina Siejka-Zielińska United Kingdom

Guangqing Sun China

Thomas Sakoparnig

205 ×1.2

MB

122 ×1.1

CR

211 ×4.2

GENET

27 ×0.9

PFM

14 ×0.8

ONCOL

Citations per year, relative to Thomas Sakoparnig Thomas Sakoparnig (= 1×) peers Guangqing Sun

Countries citing papers authored by Thomas Sakoparnig

Since Specialization

Citations

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

Fields of papers citing papers by Thomas Sakoparnig

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Sakoparnig

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas Sakoparnig. A scholar is included among the top collaborators of Thomas Sakoparnig 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 Sakoparnig. Thomas Sakoparnig is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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10 of 10 papers shown

1.

Sakoparnig, Thomas, et al.. (2024). Identifying cell states in single-cell RNA-seq data at statistically maximal resolution. PLoS Computational Biology. 20(7). e1012224–e1012224. 4 indexed citations

2.

Pérez‐Schindler, Joaquín, Bastian Kohl, Carlos Henríquez‐Olguín, et al.. (2021). RNA-bound PGC-1α controls gene expression in liquid-like nuclear condensates. Proceedings of the National Academy of Sciences. 118(36). 16 indexed citations

3.

Sakoparnig, Thomas, Christopher M. Field, & Erik van Nimwegen. (2021). Whole genome phylogenies reflect the distributions of recombination rates for many bacterial species. eLife. 10. 42 indexed citations

4.

Sakoparnig, Thomas, et al.. (2020). Bayesian networks to identify potential high-risk multimorbidity and intervention clusters in inpatients: an explorative data mining study. Swiss Medical Weekly. 150. w20299–w20299. 3 indexed citations

5.

Sakoparnig, Thomas, Martin Gerber, Andreas F. Widmer, et al.. (2018). Secondary use of routine data in hospitals: description of a scalable analytical platform based on a business intelligence system. JAMIA Open. 1(2). 172–177. 5 indexed citations

6.

Szczurek, Ewa, et al.. (2017). Predicting cancer type from tumour DNA signatures. Genome Medicine. 9(1). 104–104. 38 indexed citations

7.

Sakoparnig, Thomas, et al.. (2015). Identification of Constrained Cancer Driver Genes Based on Mutation Timing. PLoS Computational Biology. 11(1). e1004027–e1004027. 16 indexed citations

8.

Yuan, Ke, Thomas Sakoparnig, Florian Markowetz, & Niko Beerenwinkel. (2015). BitPhylogeny: a probabilistic framework for reconstructing intra-tumor phylogenies. Genome Biology. 16(1). 36–36. 72 indexed citations

9.

Sakoparnig, Thomas & Niko Beerenwinkel. (2012). Efficient sampling for Bayesian inference of conjunctive Bayesian networks. Bioinformatics. 28(18). 2318–2324. 17 indexed citations

10.

Sakoparnig, Thomas, Tobias Kockmann, Renato Paro, Christian Beisel, & Niko Beerenwinkel. (2012). Binding Profiles of Chromatin-Modifying Proteins Are Predictive for Transcriptional Activity and Promoter-Proximal Pausing. Journal of Computational Biology. 19(2). 126–138. 6 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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