Daniel Gusenleitner

3.2k total citations · 1 hit paper
20 papers, 1.3k citations indexed

About

Daniel Gusenleitner is a scholar working on Molecular Biology, Oncology and Pathology and Forensic Medicine. According to data from OpenAlex, Daniel Gusenleitner has authored 20 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 10 papers in Oncology and 4 papers in Pathology and Forensic Medicine. Recurrent topics in Daniel Gusenleitner's work include CAR-T cell therapy research (9 papers), Cancer Immunotherapy and Biomarkers (7 papers) and Gene expression and cancer classification (6 papers). Daniel Gusenleitner is often cited by papers focused on CAR-T cell therapy research (9 papers), Cancer Immunotherapy and Biomarkers (7 papers) and Gene expression and cancer classification (6 papers). Daniel Gusenleitner collaborates with scholars based in United States, United Kingdom and Germany. Daniel Gusenleitner's co-authors include F. Stephen Hodi, Scott J. Rodig, Evisa Gjini, Anita Giobbie‐Hurder, Anna C. Pavlick, Jason L. Weirather, Christine E. Horak, Donald Jackson, Han Chang and Jason Chesney and has published in prestigious journals such as Nucleic Acids Research, Journal of Clinical Oncology and Blood.

In The Last Decade

Daniel Gusenleitner

20 papers receiving 1.3k 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.

MHC proteins confer differential sensitivity to CTLA-4 and PD-1 blockade in untreated metastatic melanoma

2018 408 citations Scott J. Rodig, Daniel Gusenleitner et al. Science Translational Medicine profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel Gusenleitner United States	13	771	552	474	212	179	20	1.3k
Shelley M. Herbrich United States	14	544 0.7×	386 0.7×	602 1.3×	76 0.4×	210 1.2×	35	1.4k
Vera Levina United States	13	688 0.9×	178 0.3×	581 1.2×	56 0.3×	296 1.7×	18	1.1k
Silke Reinartz Germany	24	657 0.9×	949 1.7×	879 1.9×	133 0.6×	426 2.4×	47	2.0k
Francesca Battaglin United States	21	944 1.2×	235 0.4×	519 1.1×	427 2.0×	370 2.1×	126	1.7k
Willie Wilson United States	10	657 0.9×	410 0.7×	667 1.4×	100 0.5×	257 1.4×	20	1.4k
Robin Hallett Canada	18	494 0.6×	136 0.2×	527 1.1×	47 0.2×	259 1.4×	40	978
Nail Fatkhutdinov United States	13	339 0.4×	147 0.3×	806 1.7×	149 0.7×	187 1.0×	15	1.1k
Susanna Leskelä Spain	22	457 0.6×	96 0.2×	577 1.2×	122 0.6×	415 2.3×	27	1.4k
Song‐Yang Wu China	14	693 0.9×	597 1.1×	571 1.2×	66 0.3×	382 2.1×	24	1.4k
Katrin Meissl Austria	15	431 0.6×	316 0.6×	1.1k 2.4×	120 0.6×	305 1.7×	21	1.7k

Countries citing papers authored by Daniel Gusenleitner

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Gusenleitner

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Gusenleitner

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Gusenleitner. A scholar is included among the top collaborators of Daniel Gusenleitner 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 Gusenleitner. Daniel Gusenleitner 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

Tawbi, Hussein A., Caroline Robert, Jan C. Brase, et al.. (2022). Spartalizumab or placebo in combination with dabrafenib and trametinib in patients with BRAF V600-mutant melanoma: exploratory biomarker analyses from a randomized phase 3 trial (COMBI-i). Journal for ImmunoTherapy of Cancer. 10(6). e004226–e004226. 19 indexed citations

Bortolin, Laura, Daniel P. Salem, Daniel Gusenleitner, et al.. (2022). Extracellular vesicle-based biomarker assay for the detection of early-stage ovarian cancer.. Journal of Clinical Oncology. 40(16_suppl). 5542–5542. 1 indexed citations

Dummer, Reinhard, Jan C. Brase, James E. Garrett, et al.. (2020). Adjuvant dabrafenib plus trametinib versus placebo in patients with resected, BRAFV600-mutant, stage III melanoma (COMBI-AD): exploratory biomarker analyses from a randomised, phase 3 trial. The Lancet Oncology. 21(3). 358–372. 85 indexed citations

Dummer, Reinhard, Kelly M. Biette, Daniel Gusenleitner, et al.. (2020). Effect of first-line spartalizumab + dabrafenib + trametinib on immunosuppressive features detected in peripheral blood and clinical outcome in patients (pts) with advanced BRAF V600–mutant melanoma.. Journal of Clinical Oncology. 38(15_suppl). 10034–10034. 2 indexed citations

Dummer, Reinhard, Daniel Gusenleitner, Catarina D. Campbell, et al.. (2019). Tumor microenvironment (TME), longitudinal biomarker changes, and clinical outcome in patients (pts) with advanced BRAF V600–mutant melanoma treated with first-line spartalizumab (S) + dabrafenib (D) + trametinib (T).. Journal of Clinical Oncology. 37(15_suppl). 9515–9515. 1 indexed citations

Rodig, Scott J., Daniel Gusenleitner, Donald Jackson, et al.. (2018). MHC proteins confer differential sensitivity to CTLA-4 and PD-1 blockade in untreated metastatic melanoma. Science Translational Medicine. 10(450). 408 indexed citations breakdown →

Griffin, Gabriel K., Margaretha G.M. Roemer, Mikel Lipschitz, et al.. (2018). Integrated Genetic and Topological Analysis Reveals a Hodgkin-like Mechanism of Immune Escape in T-Cell/Histiocyte-Rich Large B-Cell Lymphoma. Blood. 132(Supplement 1). 1579–1579. 2 indexed citations

Subrahmanyam, Priyanka B., Zhiwan Dong, Daniel Gusenleitner, et al.. (2018). Distinct predictive biomarker candidates for response to anti-CTLA-4 and anti-PD-1 immunotherapy in melanoma patients. Journal for ImmunoTherapy of Cancer. 6(1). 18–18. 137 indexed citations

Rodig, Scott J., Daniel Gusenleitner, Donald Jackson, et al.. (2017). Association of distinct baseline tissue biomarkers with response to nivolumab (NIVO) and ipilimumab (IPI) in melanoma: CheckMate 064.. Journal of Clinical Oncology. 35(15_suppl). 9515–9515. 1 indexed citations

10.

Carey, Christopher D., Daniel Gusenleitner, Mikel Lipschitz, et al.. (2017). Topological analysis reveals a PD-L1-associated microenvironmental niche for Reed-Sternberg cells in Hodgkin lymphoma. Blood. 130(22). 2420–2430. 219 indexed citations

11.

Novikov, Olga, Zhongyan Wang, Elizabeth A. Stanford, et al.. (2016). An Aryl Hydrocarbon Receptor-Mediated Amplification Loop That Enforces Cell Migration in ER−/PR−/Her2− Human Breast Cancer Cells. Molecular Pharmacology. 90(5). 674–688. 132 indexed citations

12.

Morgan, Elizabeth A., Tamiwe Tomoka, Nadja Kopp, et al.. (2016). Targetable subsets of non-Hodgkin lymphoma in Malawi define therapeutic opportunities. Blood Advances. 1(1). 84–92. 8 indexed citations

13.

Shen, Ying, Stephen Piccolo, Daniel Gusenleitner, et al.. (2015). ASSIGN: context-specific genomic profiling of multiple heterogeneous biological pathways. Bioinformatics. 31(11). 1745–1753. 26 indexed citations

14.

Carey, Christopher D., Daniel Gusenleitner, Bjoern Chapuy, et al.. (2014). Molecular Classification of MYC-Driven B-Cell Lymphomas by Targeted Gene Expression Profiling of Fixed Biopsy Specimens. Journal of Molecular Diagnostics. 17(1). 19–30. 19 indexed citations

15.

Gusenleitner, Daniel, Scott S. Auerbach, Tisha Melia, et al.. (2014). Genomic Models of Short-Term Exposure Accurately Predict Long-Term Chemical Carcinogenicity and Identify Putative Mechanisms of Action. PLoS ONE. 9(7). e102579–e102579. 49 indexed citations

16.

Chapuy, Bjoern, Yuxiang Tan, Chip Stewart, et al.. (2014). Actionable Genetic Features of Primary Testicular and Primary Central Nervous System Lymphomas. Blood. 124(21). 74–74. 1 indexed citations

17.

Gusenleitner, Daniel, et al.. (2013). RamiGO: an R/Bioconductor package providing an AmiGO Visualize interface. Bioinformatics. 29(5). 666–668. 19 indexed citations

18.

Gusenleitner, Daniel, Eleanor Howe, Stefan Bentink, John Quackenbush, & Aedín C. Culhane. (2012). iBBiG: iterative binary bi-clustering of gene sets. Bioinformatics. 28(19). 2484–2492. 42 indexed citations

19.

Culhane, Aedín C., Răzvan Sultana, Serge Picard, et al.. (2011). GeneSigDB: a manually curated database and resource for analysis of gene expression signatures. Nucleic Acids Research. 40(D1). D1060–D1066. 88 indexed citations

20.

Liu, Fenglong, Joseph White, Corina Antonescu, Daniel Gusenleitner, & John Quackenbush. (2011). GCOD - GeneChip Oncology Database. BMC Bioinformatics. 12(1). 46–46. 12 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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