David B. Blumenthal

1.3k total citations
48 papers, 544 citations indexed

About

David B. Blumenthal is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, David B. Blumenthal has authored 48 papers receiving a total of 544 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 14 papers in Computational Theory and Mathematics and 13 papers in Artificial Intelligence. Recurrent topics in David B. Blumenthal's work include Bioinformatics and Genomic Networks (19 papers), Computational Drug Discovery Methods (10 papers) and Gene expression and cancer classification (9 papers). David B. Blumenthal is often cited by papers focused on Bioinformatics and Genomic Networks (19 papers), Computational Drug Discovery Methods (10 papers) and Gene expression and cancer classification (9 papers). David B. Blumenthal collaborates with scholars based in Germany, Italy and Denmark. David B. Blumenthal's co-authors include Johann Gamper, Markus List, Jan Baumbach, Tim Kacprowski, Olga Lazareva, Sébastien Bougleux, Luc Brun, Sepideh Sadegh, Reihaneh Torkzadehmahani and Julian Matschinske and has published in prestigious journals such as Nature Communications, Bioinformatics and Nature Methods.

In The Last Decade

David B. Blumenthal

37 papers receiving 527 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
David B. Blumenthal Germany 13 218 169 112 105 58 48 544
Zhongxiao Li Saudi Arabia 11 401 1.8× 181 1.1× 64 0.6× 62 0.6× 23 0.4× 18 822
Florence d’Alché–Buc France 16 629 2.9× 233 1.4× 77 0.7× 43 0.4× 59 1.0× 34 965
Minbyul Jeong South Korea 9 229 1.1× 468 2.8× 46 0.4× 96 0.9× 14 0.2× 13 736
Bei Yang China 13 136 0.6× 155 0.9× 89 0.8× 48 0.5× 27 0.5× 35 494
Charalampos Moschopoulos Greece 8 377 1.7× 80 0.5× 113 1.0× 33 0.3× 11 0.2× 15 692
Turki Turki Saudi Arabia 13 233 1.1× 175 1.0× 110 1.0× 62 0.6× 33 0.6× 53 550
Xuan Wang China 18 371 1.7× 726 4.3× 50 0.4× 91 0.9× 16 0.3× 113 1.1k
Yiwei Zhang China 14 91 0.4× 281 1.7× 43 0.4× 77 0.7× 30 0.5× 60 612
Barbara Pes Italy 12 154 0.7× 270 1.6× 26 0.2× 125 1.2× 23 0.4× 47 563
Xiuquan Du China 18 502 2.3× 153 0.9× 158 1.4× 165 1.6× 21 0.4× 54 1.1k

Countries citing papers authored by David B. Blumenthal

Since Specialization
Citations

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

Fields of papers citing papers by David B. Blumenthal

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David B. Blumenthal. 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 David B. Blumenthal. The network helps show where David B. Blumenthal may publish in the future.

Co-authorship network of co-authors of David B. Blumenthal

This figure shows the co-authorship network connecting the top 25 collaborators of David B. Blumenthal. A scholar is included among the top collaborators of David B. Blumenthal 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 David B. Blumenthal. David B. Blumenthal 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.
Regensburger, Martin, et al.. (2025). Novel co-culture model of T cells and midbrain organoids for investigating neurodegeneration in Parkinson’s disease. npj Parkinson s Disease. 11(1). 36–36. 3 indexed citations
2.
Blumenthal, David B., et al.. (2025). Deep learning models for unbiased sequence-based PPI prediction plateau at an accuracy of 0.65. Bioinformatics. 41(Supplement_1). i590–i598.
3.
4.
Blumenthal, David B., et al.. (2024). Emergence of power law distributions in protein-protein interaction networks through study bias. eLife. 13. 1 indexed citations
5.
Lazareva, Olga, et al.. (2024). DysRegNet: Patient‐specific and confounder‐aware dysregulated network inference towards precision therapeutics. British Journal of Pharmacology. 183(8). 1709–1724.
6.
Blumenthal, David B., et al.. (2024). Cracking the black box of deep sequence-based protein–protein interaction prediction. Briefings in Bioinformatics. 25(2). 29 indexed citations
7.
Sadegh, Sepideh, Elisa Anastasi, Nils M. Kriege, et al.. (2023). Lacking mechanistic disease definitions and corresponding association data hamper progress in network medicine and beyond. Nature Communications. 14(1). 1662–1662. 8 indexed citations
8.
Wang, Dandan, Samir Jabari, Ingmar Blümcke, et al.. (2023). The specific DNA methylation landscape in focal cortical dysplasia ILAE type 3D. Acta Neuropathologica Communications. 11(1). 129–129. 3 indexed citations
9.
Röttger, Richard, et al.. (2023). Federated singular value decomposition for high-dimensional data. Data Mining and Knowledge Discovery. 38(3). 938–975. 10 indexed citations
10.
11.
Lucchetta, Marta, et al.. (2023). Online bias-aware disease module mining with ROBUST-Web. Bioinformatics. 39(6). 3 indexed citations
12.
Blumenthal, David B., et al.. (2023). Demographic confounders distort inference of gene regulatory and gene co-expression networks in cancer. Briefings in Bioinformatics. 24(6). 2 indexed citations
13.
Blumenthal, David B., Sébastien Bougleux, Anton Dignös, & Johann Gamper. (2022). Enumerating dissimilar minimum cost perfect and error-correcting bipartite matchings for robust data matching. Information Sciences. 596. 202–221.
14.
Matschinske, Julian, Marisol Salgado-Albarrán, Sepideh Sadegh, et al.. (2020). Individuating Possibly Repurposable Drugs and Drug Targets for COVID-19 Treatment Through Hypothesis-Driven Systems Medicine Using CoVex. Assay and Drug Development Technologies. 18(8). 348–355. 7 indexed citations
15.
Canzar, Stefan, Jan Baumbach, David B. Blumenthal, et al.. (2020). BiCoN: network-constrained biclustering of patients and omics data. Bioinformatics. 37(16). 2398–2404. 15 indexed citations
16.
Helmer, Sven, et al.. (2020). What is meaningful research and how should we measure it?. Scientometrics. 125(1). 153–169. 14 indexed citations
17.
Blumenthal, David B., Lorenzo Viola, Markus List, et al.. (2020). EpiGEN: an epistasis simulation pipeline. Bioinformatics. 36(19). 4957–4959. 10 indexed citations
18.
Blumenthal, David B., Jan Baumbach, Markus Hoffmann, Tim Kacprowski, & Markus List. (2020). A framework for modeling epistatic interaction. Bioinformatics. 37(12). 1708–1716. 4 indexed citations
19.
Blumenthal, David B., et al.. (2019). Improved local search for graph edit distance. Pattern Recognition Letters. 129. 19–25. 7 indexed citations
20.
Blumenthal, David B. & Johann Gamper. (2018). On the exact computation of the graph edit distance. Pattern Recognition Letters. 134. 46–57. 54 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

Breakdown of academic impact, for papers by Zhongxiao Li Breakdown of academic impact, for papers by Florence d’Alché–Buc Breakdown of academic impact, for papers by Minbyul Jeong Breakdown of academic impact, for papers by Bei Yang Breakdown of academic impact, for papers by Charalampos Moschopoulos Breakdown of academic impact, for papers by Turki Turki Breakdown of academic impact, for papers by Xuan Wang Breakdown of academic impact, for papers by Yiwei Zhang Breakdown of academic impact, for papers by Barbara Pes Breakdown of academic impact, for papers by Xiuquan Du
Rankless by CCL
2026