Daniel Hübschmann

262 total papers · 22.1k total citations
44 papers, 587 citations indexed

About

Daniel Hübschmann is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Daniel Hübschmann has authored 44 papers receiving a total of 587 indexed citations (citations by other indexed papers that have themselves been cited), including 30 papers in Molecular Biology, 13 papers in Oncology and 11 papers in Cancer Research. Recurrent topics in Daniel Hübschmann's work include Cancer Genomics and Diagnostics (11 papers), Bioinformatics and Genomic Networks (11 papers) and Gene expression and cancer classification (9 papers). Daniel Hübschmann is often cited by papers focused on Cancer Genomics and Diagnostics (11 papers), Bioinformatics and Genomic Networks (11 papers) and Gene expression and cancer classification (9 papers). Daniel Hübschmann collaborates with scholars based in Germany, United Kingdom and United States. Daniel Hübschmann's co-authors include Zuguang Gu, Matthias Schlesner, Stefan Fröhling, Carolin Andresen, Roland Eils, Albrecht Stenzinger, Simon Kreutzfeldt, Christoph E. Heilig, Veronica Teleanu and Christian P. Schaaf and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Daniel Hübschmann

39 papers receiving 582 citations

Hit Papers

SimplifyEnrichment : A Bi... 2022 2026 2023 2024 2022 40 80 120

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Daniel Hübschmann 322 131 123 76 76 44 587
Zhihao Ding 411 1.3× 128 1.0× 101 0.8× 79 1.0× 57 0.8× 32 623
Lixia Luo 335 1.0× 162 1.2× 158 1.3× 47 0.6× 64 0.8× 54 634
Duc Nguyen 338 1.0× 190 1.5× 75 0.6× 72 0.9× 38 0.5× 37 552
Jinhui Wang 349 1.1× 108 0.8× 139 1.1× 50 0.7× 46 0.6× 29 535
Yusuke Koga 379 1.2× 94 0.7× 135 1.1× 60 0.8× 107 1.4× 23 663
Fang Tong 254 0.8× 130 1.0× 61 0.5× 64 0.8× 48 0.6× 66 594
Hisashi Hashimoto 227 0.7× 107 0.8× 71 0.6× 59 0.8× 70 0.9× 68 639
Xun Sun 220 0.7× 153 1.2× 79 0.6× 41 0.5× 110 1.4× 44 631
Jun Wang 306 1.0× 129 1.0× 121 1.0× 67 0.9× 45 0.6× 39 595
Sahng‐June Kwak 392 1.2× 147 1.1× 93 0.8× 61 0.8× 46 0.6× 28 682

Countries citing papers authored by Daniel Hübschmann

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Hübschmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Hübschmann

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

All Works

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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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