Michael Krauthammer

11.8k total citations · 2 hit papers
115 papers, 4.6k citations indexed

About

Michael Krauthammer is a scholar working on Molecular Biology, Artificial Intelligence and Oncology. According to data from OpenAlex, Michael Krauthammer has authored 115 papers receiving a total of 4.6k indexed citations (citations by other indexed papers that have themselves been cited), including 84 papers in Molecular Biology, 31 papers in Artificial Intelligence and 16 papers in Oncology. Recurrent topics in Michael Krauthammer's work include Biomedical Text Mining and Ontologies (40 papers), Semantic Web and Ontologies (17 papers) and Bioinformatics and Genomic Networks (12 papers). Michael Krauthammer is often cited by papers focused on Biomedical Text Mining and Ontologies (40 papers), Semantic Web and Ontologies (17 papers) and Bioinformatics and Genomic Networks (12 papers). Michael Krauthammer collaborates with scholars based in United States, Switzerland and Germany. Michael Krauthammer's co-authors include Ruth Halaban, Andrey Rzhetsky, Goran Nenadić, Pauline Kra, Stephan Ariyan, Hua Yu, Cynthia Friedman, Mario Sznol, Jamie P. McCusker and Carol Friedman and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nature Communications.

In The Last Decade

Michael Krauthammer

109 papers receiving 4.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

In Vivo Identification of Tumor- Suppressive PTEN ceRNAs in an Oncogenic BRAF-Induced Mouse Model of Melanoma

2011 534 citations Michael Krauthammer, Ruth Halaban et al. profile →
Predicting prime editing efficiency and product purity by deep learning

2023 84 citations Nicolas Mathis, Ahmed Allam et al. Nature Biotechnology profile →

Peers

Michael Krauthammer

ONCOL

IMMUN

Ivan G. Costa Germany

Ralf Zimmer Germany

Jane Staunton United States

Jan Komorowski Poland

Adam A. Margolin United States

Pingzhao Hu Canada

Lynn M. Schriml United States

John V. Pearson Australia

Florian Markowetz United Kingdom

Gabriela Alexe United States

Ivan G. Costa Germany

Michael Krauthammer

3.0k ×0.9

634 ×0.6

328 ×0.4

ONCOL

672 ×0.9

554 ×1.5

IMMUN

Citations per year, relative to Michael Krauthammer Michael Krauthammer (= 1×) peers Ivan G. Costa

Countries citing papers authored by Michael Krauthammer

Since Specialization

Citations

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

Fields of papers citing papers by Michael Krauthammer

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michael Krauthammer

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

All Works

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20 of 20 papers shown

Tian, Yuan, Anna Mallone, Michael Koller, et al.. (2025). Enhancing post-kidney transplant prognostication: an interpretable machine learning approach for longitudinal outcome prediction. npj Digital Medicine. 8(1). 684–684. 1 indexed citations

Zheng, Xiaochen, et al.. (2024). Simple Contrastive Representation Learning for Time Series Forecasting. 6005–6009. 7 indexed citations

Marquart, Kim Fabiano, Nicolas Mathis, Lucas Kissling, et al.. (2024). Effective genome editing with an enhanced ISDra2 TnpB system and deep learning-predicted ωRNAs. Nature Methods. 21(11). 2084–2093. 8 indexed citations

Mathis, Nicolas, Ahmed Allam, András Tálas, et al.. (2024). Machine learning prediction of prime editing efficiency across diverse chromatin contexts. Nature Biotechnology. 43(5). 712–719. 27 indexed citations

Balázs, Zsolt, Panagiotis Balermpas, Jonas Willmann, et al.. (2024). Longitudinal cell-free DNA characterization by low-coverage whole-genome sequencing in patients undergoing high-dose radiotherapy. Radiotherapy and Oncology. 197. 110364–110364. 1 indexed citations

Esposito, Mauro, Zsolt Balázs, Evelyn Lattmann, et al.. (2024). COL10A1 expression distinguishes a subset of cancer-associated fibroblasts present in the stroma of high-risk basal cell carcinoma. British Journal of Dermatology. 191(5). 775–790. 3 indexed citations

Scharl, Michael, Barbara M. Szczerba, Yasser Morsy, et al.. (2022). Prospective observational study of the role of the microbiome in BCG responsiveness prediction (SILENT-EMPIRE): a study protocol. BMJ Open. 12(4). e061421–e061421. 12 indexed citations

Ramelyte, Egle, Aizhan Tastanova, Zsolt Balázs, et al.. (2021). Oncolytic virotherapy-mediated anti-tumor response: a single-cell perspective. Cancer Cell. 39(3). 394–406.e4. 79 indexed citations

Frick-Cheng, Arwen E., Anna Sintsova, Sara N. Smith, et al.. (2020). The Gene Expression Profile of Uropathogenic Escherichia coli in Women with Uncomplicated Urinary Tract Infections Is Recapitulated in the Mouse Model. mBio. 11(4). 32 indexed citations

10.

Wang, Xuefeng, Xiaoqing Yu, Michael Krauthammer, et al.. (2020). The Association of MUC16 Mutation with Tumor Mutation Burden and Its Prognostic Implications in Cutaneous Melanoma. Cancer Epidemiology Biomarkers & Prevention. 29(9). 1792–1799. 15 indexed citations

11.

Boddupalli, Chandra Sekhar, Noffar Bar, Krishna Kadaveru, et al.. (2016). Interlesional diversity of T cell receptors in melanoma with immune checkpoints enriched in tissue-resident memory T cells. JCI Insight. 1(21). 111 indexed citations

12.

Robles‐Espinoza, Carla Daniela, Nicola D. Roberts, Shuyang Chen, et al.. (2016). Germline MC1R status influences somatic mutation burden in melanoma. Nature Communications. 7(1). 12064–12064. 87 indexed citations

13.

Bukhari, Syed Ahmad Chan, et al.. (2015). iCyrus: A Semantic Framework for Biomedical Image Discovery.. 13–22. 1 indexed citations

14.

Bukhari, Syed Ahmad Chan, et al.. (2015). BIM: an open ontology for the annotation of biomedical images.. 5 indexed citations

15.

Bukhari, Syed Ahmad Chan, Michael Krauthammer, & Christopher J. O. Baker. (2014). SEBI: An Architecture for Biomedical Image Discovery, Interoperability and Reusability Based on Semantic Enrichment.. 6 indexed citations

16.

Ha, Byung Hak, Matthew J. Davis, Catherine Chen, et al.. (2012). Type II p21-activated kinases (PAKs) are regulated by an autoinhibitory pseudosubstrate. Proceedings of the National Academy of Sciences. 109(40). 16107–16112. 66 indexed citations

17.

Singhal, Garima, Sebastian Szpakowski, Christina Ivins Zito, et al.. (2011). Phosphoproteomic Screen Identifies Potential Therapeutic Targets in Melanoma. Molecular Cancer Research. 9(6). 801–812. 73 indexed citations

18.

Krauthammer, Michael, Charles A. Kaufmann, T. Conrad Gilliam, & Andrey Rzhetsky. (2004). Molecular triangulation: Bridging linkage and molecular-network information for identifying candidate genes in Alzheimer's disease. Proceedings of the National Academy of Sciences. 101(42). 15148–15153. 125 indexed citations

19.

Wacholder, Nina, et al.. (2000). Designing a Navigational Ontology for Browsing and Accessing 3D Anatomical Images.. Europe PMC (PubMed Central). 1152–1152. 1 indexed citations

20.

Krauthammer, Michael, Andrey Rzhetsky, Pavel Morozov, & Carol Friedman. (2000). Using BLAST, A DNA and Protein Sequence Comparison Tool, for Finding Gene and Protein Names in Journal Articles. Europe PMC (PubMed Central).

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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