Ralf Eggeling

666 total citations
19 papers, 240 citations indexed

About

Ralf Eggeling is a scholar working on Molecular Biology, Artificial Intelligence and Infectious Diseases. According to data from OpenAlex, Ralf Eggeling has authored 19 papers receiving a total of 240 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 7 papers in Artificial Intelligence and 3 papers in Infectious Diseases. Recurrent topics in Ralf Eggeling's work include Bayesian Modeling and Causal Inference (6 papers), Gene expression and cancer classification (5 papers) and Genomics and Chromatin Dynamics (4 papers). Ralf Eggeling is often cited by papers focused on Bayesian Modeling and Causal Inference (6 papers), Gene expression and cancer classification (5 papers) and Genomics and Chromatin Dynamics (4 papers). Ralf Eggeling collaborates with scholars based in Germany, Finland and Slovakia. Ralf Eggeling's co-authors include Ivo Große, Mikko Koivisto, Nico Pfeifer, Petri Myllymäki, Teemu Roos, Henning Gruell, Florian Klein, Lutz Gieselmann, Christoph Kreer and Marylyn M. Addo and has published in prestigious journals such as Nucleic Acids Research, Nature Medicine and Bioinformatics.

In The Last Decade

Ralf Eggeling

17 papers receiving 235 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ralf Eggeling Germany	8	111	86	36	35	25	19	240
R. A. Leo Elworth United States	10	227 2.0×	41 0.5×	41 1.1×	18 0.5×	18 0.7×	17	347
Ulykbek Kairov Kazakhstan	9	144 1.3×	40 0.5×	21 0.6×	26 0.7×	16 0.6×	47	284
G.R. Kulkarni India	10	125 1.1×	26 0.3×	19 0.5×	25 0.7×	21 0.8×	35	302
Rohit Tyagi India	10	88 0.8×	42 0.5×	27 0.8×	29 0.8×	14 0.6×	28	288
José Dı́az Mexico	9	115 1.0×	61 0.7×	20 0.6×	10 0.3×	13 0.5×	42	276
Manh-Duy Nguyen Vietnam	10	94 0.8×	80 0.9×	63 1.8×	15 0.4×	8 0.3×	14	366
Jingjing Chen China	9	146 1.3×	36 0.4×	24 0.7×	48 1.4×	13 0.5×	29	328
Geoffrey Siwo United States	9	91 0.8×	21 0.2×	16 0.4×	21 0.6×	21 0.8×	22	236
Xiaoqian Wu China	7	90 0.8×	147 1.7×	31 0.9×	36 1.0×	16 0.6×	14	335
Kreshna Gopal United States	5	222 2.0×	31 0.4×	17 0.5×	22 0.6×	8 0.3×	12	347

Countries citing papers authored by Ralf Eggeling

Since Specialization

Citations

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

Fields of papers citing papers by Ralf Eggeling

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ralf Eggeling

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

All Works

Sort: Min cites: Since: Top N: Style:

19 of 19 papers shown

Eggeling, Ralf, et al.. (2025). Long-term impact of the SARS-CoV-2 pandemic on respiratory viruses in Germany. BMC Public Health. 25(1). 2654–2654.

Eggeling, Ralf, Bernhard Reuter, Kristel Van Laethem, et al.. (2024). HIV multidrug class resistance prediction with a time sliding anchor approach. Bioinformatics Advances. 5(1). vbaf099–vbaf099.

Eggeling, Ralf, et al.. (2021). DNA-binding properties of the MADS-domain transcription factor SEPALLATA3 and mutant variants characterized by SELEX-seq. Plant Molecular Biology. 105(4-5). 543–557. 8 indexed citations

Herath, Steven C., et al.. (2021). Deep Learning in the Detection of Rare Fractures – Development of a “Deep Learning Convolutional Network” Model for Detecting Acetabular Fractures. Zeitschrift für Orthopädie und Unfallchirurgie. 161(1). 42–50. 5 indexed citations

Korenkov, Michael, Kanika Vanshylla, Ralf Eggeling, et al.. (2021). Evaluation of a Rapid Antigen Test To Detect SARS-CoV-2 Infection and Identify Potentially Infectious Individuals. Journal of Clinical Microbiology. 59(9). e0089621–e0089621. 43 indexed citations

Eggeling, Ralf, et al.. (2019). On Structure Priors for Learning Bayesian Networks. Työväentutkimus Vuosikirja. 1687–1695. 2 indexed citations

Zehner, Matthias, Verena Krähling, Hadas Cohen‐Dvashi, et al.. (2019). Polyclonal and convergent antibody response to Ebola virus vaccine rVSV-ZEBOV. Nature Medicine. 25(10). 1589–1600. 65 indexed citations

Eggeling, Ralf, et al.. (2019). Learning Bayesian networks with local structure, mixed variables, and exact algorithms. International Journal of Approximate Reasoning. 115. 69–95. 16 indexed citations

Handl, Lisa, et al.. (2019). Weighted elastic net for unsupervised domain adaptation with application to age prediction from DNA methylation data. Bioinformatics. 35(14). i154–i163. 7 indexed citations

10.

Eggeling, Ralf, et al.. (2018). Finding Optimal Bayesian Networks with Local Structure.. 451–462. 3 indexed citations

11.

Eggeling, Ralf. (2018). Disentangling transcription factor binding site complexity. Nucleic Acids Research. 46(20). e121–e121. 12 indexed citations

12.

Eggeling, Ralf, et al.. (2018). Intersection-Validation: A Method for Evaluating Structure Learning without Ground Truth. Työväentutkimus Vuosikirja. 84. 1570–1578. 5 indexed citations

13.

Eggeling, Ralf, Ivo Große, & Mikko Koivisto. (2018). Algorithms for learning parsimonious context trees. Machine Learning. 108(6). 879–911. 2 indexed citations

14.

Eggeling, Ralf & Mikko Koivisto. (2016). Pruning rules for learning parsimonious context trees. Työväentutkimus Vuosikirja. 152–161. 3 indexed citations

15.

Eggeling, Ralf, Ivo Große, & Jan Grau. (2016). InMoDe: tools for learning and visualizing intra-motif dependencies of DNA binding sites. Bioinformatics. 33(4). 580–582. 13 indexed citations

16.

Eggeling, Ralf, Mikko Koivisto, & Ivo Große. (2015). Dealing with small data: On the generalization of context trees. International Conference on Machine Learning. 1245–1253. 5 indexed citations

17.

Eggeling, Ralf, Teemu Roos, Petri Myllymäki, & Ivo Große. (2015). Inferring intra-motif dependencies of DNA binding sites from ChIP-seq data. BMC Bioinformatics. 16(1). 375–375. 27 indexed citations

18.

Eggeling, Ralf, Teemu Roos, Petri Myllymäki, & Ivo Große. (2014). Robust learning of inhomogeneous PMMs. Työväentutkimus Vuosikirja. 229–237. 5 indexed citations

19.

Eggeling, Ralf, André Gohr, Jens Keilwagen, et al.. (2014). On the Value of Intra-Motif Dependencies of Human Insulator Protein CTCF. PLoS ONE. 9(1). e85629–e85629. 19 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.

Explore authors with similar magnitude of impact