Hendrik Nogai

1.5k total citations
35 papers, 1.0k citations indexed

About

Hendrik Nogai is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine and Genetics. According to data from OpenAlex, Hendrik Nogai has authored 35 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 12 papers in Pulmonary and Respiratory Medicine and 11 papers in Genetics. Recurrent topics in Hendrik Nogai's work include Fibroblast Growth Factor Research (9 papers), Chronic Lymphocytic Leukemia Research (8 papers) and Chronic Myeloid Leukemia Treatments (7 papers). Hendrik Nogai is often cited by papers focused on Fibroblast Growth Factor Research (9 papers), Chronic Lymphocytic Leukemia Research (8 papers) and Chronic Myeloid Leukemia Treatments (7 papers). Hendrik Nogai collaborates with scholars based in Germany, United States and Switzerland. Hendrik Nogai's co-authors include Bernd Dörken, Georg Lenz, Peter Lenz, Michael Grau, Martin Janz, Margot Thome, Stephan Hailfinger, Annette Wolf, Brigitte Wollert‐Wulf and Matthias Pfeifer and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.

In The Last Decade

Hendrik Nogai

31 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Hendrik Nogai Germany 15 404 340 283 262 224 35 1.0k
Marina Cinelli Italy 16 404 1.0× 169 0.5× 394 1.4× 131 0.5× 167 0.7× 32 884
Gerardo Ferrer United States 19 439 1.1× 175 0.5× 383 1.4× 278 1.1× 386 1.7× 45 1.2k
Karl Köchert Germany 15 504 1.2× 368 1.1× 714 2.5× 222 0.8× 572 2.6× 26 1.6k
Karoline Kollmann Austria 18 629 1.6× 413 1.2× 106 0.4× 180 0.7× 114 0.5× 31 1.2k
Jingyi Shi China 12 536 1.3× 183 0.5× 103 0.4× 170 0.6× 101 0.5× 32 1.1k
Kaname Yamashita Japan 15 411 1.0× 442 1.3× 108 0.4× 361 1.4× 67 0.3× 51 976
Althea McCourty United States 18 248 0.6× 369 1.1× 302 1.1× 84 0.3× 66 0.3× 27 766
Jennifer M. Tran United States 12 909 2.3× 377 1.1× 64 0.2× 296 1.1× 209 0.9× 21 1.3k
Irene A. Rigault de la Longrais Italy 20 799 2.0× 345 1.0× 109 0.4× 435 1.7× 64 0.3× 26 1.4k
Federica Frezzato Italy 23 546 1.4× 191 0.6× 307 1.1× 82 0.3× 439 2.0× 61 1.2k

Countries citing papers authored by Hendrik Nogai

Since Specialization
Citations

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

Fields of papers citing papers by Hendrik Nogai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hendrik Nogai

This figure shows the co-authorship network connecting the top 25 collaborators of Hendrik Nogai. A scholar is included among the top collaborators of Hendrik Nogai 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 Hendrik Nogai. Hendrik Nogai 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.
Papayannidis, Cristina, Krzysztof Mądry, Witold Prejzner, et al.. (2024). River-52: A Multicenter, Open-Label Clinical Trial of RVU120 in Patients with Relapsed or Refractory High-Risk Myelodysplastic Syndrome or Acute Myeloid Leukemia. Blood. 144(Supplement 1). 6005–6005.
3.
Ellinghaus, Peter, Daniel Neureiter, Hendrik Nogai, Sebastian Stintzing, & Matthias Ocker. (2022). Patient Selection Approaches in FGFR Inhibitor Trials—Many Paths to the Same End?. Cells. 11(19). 3180–3180. 14 indexed citations
4.
Rudzinski, Erin R., Jaclyn F. Hechtman, Sinchita Roy‐Chowdhuri, et al.. (2021). Diagnostic testing approaches for the identification of patients with TRK fusion cancer prior to enrollment in clinical trials investigating larotrectinib. Cancer Genetics. 260-261. 46–52. 9 indexed citations
5.
Hong, David S., Lin Shen, Cornelis M. van Tilburg, et al.. (2021). Long-term efficacy and safety of larotrectinib in an integrated dataset of patients with TRK fusion cancer.. Journal of Clinical Oncology. 39(15_suppl). 3108–3108. 25 indexed citations
6.
Hong, David S., Antoîne Italiano, Andrew Briggs, et al.. (2021). Intra-patient comparison from larotrectinib clinical trials in TRK fusion cancer: An expanded dataset.. Journal of Clinical Oncology. 39(15_suppl). 3114–3114. 4 indexed citations
7.
Leyvraz, Serge, James Chih‐Hsin Yang, Paolo G. Casali, et al.. (2020). 604TiP ON-TRK: A non-interventional study of larotrectinib in patients with TRK fusion cancer. Annals of Oncology. 31. S503–S503. 2 indexed citations
8.
Joerger, Markus, Byoung Chul Cho, Nicolas Mach, et al.. (2019). Early clinical experience with the pan-FGFR inhibitor rogaratinib in patients with non-small cell lung cancer selected based on FGFR mRNA expression levels.. Journal of Clinical Oncology. 37(15_suppl). e20661–e20661. 6 indexed citations
10.
Cho, Byoung Chul, Grace K. Dy, Ramaswamy Govindan, et al.. (2018). Phase Ib/II study of the pan-cyclin-dependent kinase inhibitor roniciclib in combination with chemotherapy in patients with extensive-disease small-cell lung cancer. Lung Cancer. 123. 14–21. 25 indexed citations
11.
Bahleda, Rastislav, Juneko E. Grilley‐Olson, Ramaswamy Govindan, et al.. (2017). Phase I dose-escalation studies of roniciclib, a pan-cyclin-dependent kinase inhibitor, in advanced malignancies. British Journal of Cancer. 116(12). 1505–1512. 22 indexed citations
13.
Jehn, C., Bernd Flath, Hendrik Nogai, et al.. (2015). Neurocognitive function, brain-derived neurotrophic factor (BDNF) and IL-6 levels in cancer patients with depression. Journal of Neuroimmunology. 287. 88–92. 61 indexed citations
14.
Ostendorf, Benjamin N., Christian Jehn, Lam Vuong, et al.. (2014). Synchronous tuberculosis, Epstein-Barr virus-associated lymphoproliferative disorder and cytomegalovirus infection in an allogeneic transplant recipient: a case report. SpringerPlus. 3(1). 278–278. 6 indexed citations
15.
Nogai, Hendrik, Stephan Hailfinger, Michael Grau, et al.. (2013). IκB-ζ controls the constitutive NF-κB target gene network and survival of ABC DLBCL. Blood. 122(13). 2242–2250. 59 indexed citations
16.
Hailfinger, Stephan, Hendrik Nogai, Christiane Pelzer, et al.. (2011). Malt1-dependent RelB cleavage promotes canonical NF-κB activation in lymphocytes and lymphoma cell lines. Proceedings of the National Academy of Sciences. 108(35). 14596–14601. 179 indexed citations
17.
18.
Kim, Theo D., Michaela Schwarz, Hendrik Nogai, et al.. (2010). Thyroid Dysfunction Caused by Second-Generation Tyrosine Kinase Inhibitors in Philadelphia Chromosome-Positive Chronic Myeloid Leukemia. Thyroid. 20(11). 1209–1214. 66 indexed citations
19.
Türkmen, Seval, Michaela Schwarz, Gökhan Koca, et al.. (2009). Impact of additional chromosomal aberrations and BCR-ABL kinase domain mutations on the response to nilotinib in Philadelphia chromosome-positive chronic myeloid leukemia. Haematologica. 95(4). 582–588. 31 indexed citations
20.

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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