Michael P. Menden

6.8k total citations
41 papers, 1.2k citations indexed

About

Michael P. Menden is a scholar working on Molecular Biology, Cancer Research and Computational Theory and Mathematics. According to data from OpenAlex, Michael P. Menden has authored 41 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 10 papers in Cancer Research and 8 papers in Computational Theory and Mathematics. Recurrent topics in Michael P. Menden's work include Cancer Genomics and Diagnostics (8 papers), Computational Drug Discovery Methods (8 papers) and Bioinformatics and Genomic Networks (7 papers). Michael P. Menden is often cited by papers focused on Cancer Genomics and Diagnostics (8 papers), Computational Drug Discovery Methods (8 papers) and Bioinformatics and Genomic Networks (7 papers). Michael P. Menden collaborates with scholars based in Germany, Australia and United Kingdom. Michael P. Menden's co-authors include Julio Sáez-Rodríguez, Francesco Iorio, Mathew J. Garnett, Ultan McDermott, Pedro J. Ballester, Cyril H. Benes, Timothy Rittman, Hong Ge, Raul Rodriguez‐Esteban and Fabian Schmich and has published in prestigious journals such as Journal of Clinical Investigation, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Michael P. Menden

34 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael P. Menden Germany 15 677 489 151 119 87 41 1.2k
Petr Smirnov Canada 14 636 0.9× 353 0.7× 232 1.5× 124 1.0× 99 1.1× 25 969
Zhaleh Safikhani Canada 11 543 0.8× 263 0.5× 211 1.4× 139 1.2× 99 1.1× 20 861
Jaegyoon Ahn South Korea 19 883 1.3× 285 0.6× 206 1.4× 97 0.8× 58 0.7× 52 1.2k
Neel S. Madhukar United States 11 523 0.8× 255 0.5× 195 1.3× 145 1.2× 83 1.0× 28 1.2k
Minjie Mou China 14 664 1.0× 284 0.6× 123 0.8× 65 0.5× 64 0.7× 30 941
Tianyi Zhao China 17 727 1.1× 263 0.5× 166 1.1× 42 0.4× 67 0.8× 56 1.2k
Ivan V. Ozerov United States 20 699 1.0× 272 0.6× 188 1.2× 293 2.5× 157 1.8× 34 1.3k
Jeremy L. Muhlich United States 19 1.1k 1.6× 402 0.8× 88 0.6× 141 1.2× 36 0.4× 25 1.4k
Shuyu Zheng China 14 600 0.9× 246 0.5× 115 0.8× 144 1.2× 68 0.8× 36 1.0k
Samson Fong United States 7 510 0.8× 230 0.5× 100 0.7× 49 0.4× 39 0.4× 11 790

Countries citing papers authored by Michael P. Menden

Since Specialization
Citations

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

Fields of papers citing papers by Michael P. Menden

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael P. Menden. 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 Michael P. Menden. The network helps show where Michael P. Menden may publish in the future.

Co-authorship network of co-authors of Michael P. Menden

This figure shows the co-authorship network connecting the top 25 collaborators of Michael P. Menden. A scholar is included among the top collaborators of Michael P. Menden 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 Michael P. Menden. Michael P. Menden 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.
Sulaj, Alba, Gernot Poschet, Thomas Fleming, et al.. (2025). Periodic fasting induced reconstitution of metabolic flexibility improves albuminuria in patients with type 2 diabetes. Molecular Metabolism. 102. 102257–102257.
2.
Pauli, Jessica, Nadja Sachs, Katja Steiger, et al.. (2025). Single cell spatial transcriptomics integration deciphers the morphological heterogeneity of atherosclerotic carotid arteries. Nature Communications. 16(1). 11282–11282. 1 indexed citations
3.
Holch, Julian Walter, Sebastian Stintzing, Kathrin Heinrich, et al.. (2025). FOLFIRI with cetuximab or bevacizumab in RAS wild-type metastatic colorectal cancer: Refining first-line treatment selection by combining clinical parameters. European Journal of Cancer. 220. 115388–115388.
4.
Nair, Vidya Padmanabhan, Gabriele Ciceri, Ina Rothenaigner, et al.. (2024). Suppression of ferroptosis by vitamin A or radical-trapping antioxidants is essential for neuronal development. Nature Communications. 15(1). 7611–7611. 23 indexed citations
5.
Maalmi, Haïfa, Gidon J. Bönhof, Wolfgang Rathmann, et al.. (2024). Prediction Model for Polyneuropathy in Recent‐Onset Diabetes Based on Serum Neurofilament Light Chain, Fibroblast Growth Factor‐19 and Standard Anthropometric and Clinical Variables. Diabetes/Metabolism Research and Reviews. 40(8). e70009–e70009.
6.
Maalmi, Haïfa, Holger Prokisch, Barbara Thorand, et al.. (2024). Interpretable multimodal machine learning (IMML) framework reveals pathological signatures of distal sensorimotor polyneuropathy. SHILAP Revista de lepidopterología. 4(1). 265–265.
7.
Nagarajan, Divya, David Corujo, Thale Kristin Olsen, et al.. (2024). Epigenetic regulation of cell state by H2AFY governs immunogenicity in high-risk neuroblastoma. Journal of Clinical Investigation. 134(21). 2 indexed citations
8.
Holch, Julian Walter, Sebastian Stintzing, Kathrin Heinrich, et al.. (2024). Refining first-line treatment decision in RAS wildtype (RAS-WT) metastatic colorectal cancer (mCRC) by combining clinical biomarkers: Results of the randomized phase 3 trial FIRE-3 (AIO KRK0306).. Journal of Clinical Oncology. 42(3_suppl). 13–13. 1 indexed citations
9.
Nagarajan, Divya, et al.. (2024). Loss of NEDD8 in cancer cells causes vulnerability to immune checkpoint blockade in triple-negative breast cancer. Nature Communications. 15(1). 3581–3581. 3 indexed citations
10.
Mubarak, Mohammad S., Peter Seiringer, Michael P. Menden, et al.. (2024). Death-Associated Protein Kinase 1 Dampens Keratinocyte Necroptosis and Expression of Inflammatory Genes in Lichen Planus. Journal of Investigative Dermatology. 145(8). 1921–1929.e13.
11.
Gonçalves, Emanuel, et al.. (2023). The pharmacoepigenomic landscape of cancer cell lines reveals the epigenetic component of drug sensitivity. Communications Biology. 6(1). 825–825. 4 indexed citations
12.
Rodriguez‐Esteban, Raul, et al.. (2023). Generative artificial intelligence empowers digital twins in drug discovery and clinical trials. Expert Opinion on Drug Discovery. 19(1). 33–42. 97 indexed citations
13.
Stahler, Arndt, Sebastian Stintzing, Dominik Paul Modest, et al.. (2023). The Oncology Biomarker Discovery framework reveals cetuximab and bevacizumab response patterns in metastatic colorectal cancer. Nature Communications. 14(1). 5391–5391. 10 indexed citations
14.
Garzorz‐Stark, Natalie, et al.. (2023). The impact of the cardiovascular component and somatic mutations on ageing. Aging Cell. 22(10). e13957–e13957. 2 indexed citations
15.
Vick, Binje, Karsten Spiekermann, Maja Rothenberg‐Thurley, et al.. (2022). WT1 and DNMT3A play essential roles in the growth of certain patient AML cells in mice. Blood. 141(8). 955–960. 1 indexed citations
16.
Scala, Emanuele, et al.. (2022). 033 A “two-strike” model for psoriasis: an in vivo human study. Journal of Investigative Dermatology. 142(12). S186–S186.
17.
Yang, Mi, Patricia Jaaks, Jonathan R. Dry, et al.. (2020). Stratification and prediction of drug synergy based on target functional similarity. npj Systems Biology and Applications. 6(1). 16–16. 41 indexed citations
18.
Cokelaer, Thomas, Elisabeth Chen, Francesco Iorio, et al.. (2017). GDSCTools for mining pharmacogenomic interactions in cancer. Bioinformatics. 34(7). 1226–1228. 41 indexed citations
19.
Iorio, Francesco, Timothy Rittman, Hong Ge, Michael P. Menden, & Julio Sáez-Rodríguez. (2012). Transcriptional data: a new gateway to drug repositioning?. Drug Discovery Today. 18(7-8). 350–357. 173 indexed citations
20.
Niepel, Mario, et al.. (2011). Adaptive informatics for multifactorial and high-content biological data. Nature Methods. 8(6). 487–492. 52 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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