Daniel Novak

1.2k total citations
29 papers, 861 citations indexed

About

Daniel Novak is a scholar working on Molecular Biology, Oncology and Cell Biology. According to data from OpenAlex, Daniel Novak has authored 29 papers receiving a total of 861 indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Molecular Biology, 6 papers in Oncology and 5 papers in Cell Biology. Recurrent topics in Daniel Novak's work include Pluripotent Stem Cells Research (9 papers), Melanoma and MAPK Pathways (7 papers) and CRISPR and Genetic Engineering (6 papers). Daniel Novak is often cited by papers focused on Pluripotent Stem Cells Research (9 papers), Melanoma and MAPK Pathways (7 papers) and CRISPR and Genetic Engineering (6 papers). Daniel Novak collaborates with scholars based in Germany, China and United States. Daniel Novak's co-authors include Jochen Utikal, Laura Hüser, Peter Altevogt, Viktor Umansky, Lionel Larribère, Viktor Umansky, Aniello Federico, Elias Orouji, Kasia Weina and Huizi Wu and has published in prestigious journals such as Scientific Reports, International Journal of Molecular Sciences and British Journal of Cancer.

In The Last Decade

Daniel Novak

27 papers receiving 856 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Daniel Novak Germany	17	637	258	205	115	77	29	861
Jun-Kyum Kim South Korea	14	428 0.7×	214 0.8×	213 1.0×	138 1.2×	67 0.9×	17	755
Minhao Yu China	17	461 0.7×	226 0.9×	296 1.4×	111 1.0×	66 0.9×	39	779
Yanhua Xuan China	18	539 0.8×	381 1.5×	221 1.1×	111 1.0×	115 1.5×	47	884
Violaine Goidts Germany	15	582 0.9×	306 1.2×	273 1.3×	105 0.9×	57 0.7×	21	878
Michael Papetti United States	10	637 1.0×	172 0.7×	216 1.1×	101 0.9×	67 0.9×	11	968
Ozlem Aksoy United States	7	744 1.2×	260 1.0×	241 1.2×	179 1.6×	109 1.4×	8	1.2k
Yeri Lee South Korea	13	510 0.8×	261 1.0×	289 1.4×	109 0.9×	141 1.8×	25	940
Maksim Sinyuk United States	13	398 0.6×	317 1.2×	205 1.0×	171 1.5×	84 1.1×	17	769
Yunuo Mao China	10	538 0.8×	198 0.8×	168 0.8×	102 0.9×	55 0.7×	13	826
Andrea M. Griesinger United States	17	759 1.2×	300 1.2×	196 1.0×	224 1.9×	139 1.8×	37	1.3k

Countries citing papers authored by Daniel Novak

Since Specialization

Citations

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

Fields of papers citing papers by Daniel Novak

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Novak

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

Liu, Ke, Yuxin Zhang, Daniel Novak, et al.. (2025). Direct transdifferentiation of tumorigenic melanoma cells induces tumor cell reversion. Cell Death and Disease. 16(1). 563–563.

Arkhypov, Ihor, Feyza Gül Özbay Kurt, Daniel Novak, et al.. (2022). HSP90α induces immunosuppressive myeloid cells in melanoma via TLR4 signaling. Journal for ImmunoTherapy of Cancer. 10(9). e005551–e005551. 32 indexed citations

Sun, Qian, et al.. (2022). ADCK2 Knockdown Affects the Migration of Melanoma Cells via MYL6. Cancers. 14(4). 1071–1071. 15 indexed citations

Federico, Aniello, Lionel Larribère, Daniel Novak, et al.. (2020). Mithramycin A and Mithralog EC-8042 Inhibit SETDB1 Expression and Its Oncogenic Activity in Malignant Melanoma. Molecular Therapy — Oncolytics. 18. 83–99. 26 indexed citations

Hüser, Laura, Aniello Federico, Gretchen Wolff, et al.. (2020). T-type calcium channel inhibition restores sensitivity to MAPK inhibitors in de-differentiated and adaptive melanoma cells. British Journal of Cancer. 122(7). 1023–1036. 22 indexed citations

Novak, Daniel, et al.. (2020). STAT3 Relays a Differential Response to Melanoma-Associated NRAS Mutations. Cancers. 12(1). 119–119. 7 indexed citations

Novak, Daniel, et al.. (2019). SOX2 in development and cancer biology. Seminars in Cancer Biology. 67(Pt 1). 74–82. 260 indexed citations

Orouji, Elias, Aniello Federico, Lionel Larribère, et al.. (2019). Histone methyltransferase SETDB1 contributes to melanoma tumorigenesis and serves as a new potential therapeutic target. International Journal of Cancer. 145(12). 3462–3477. 47 indexed citations

Wu, Huizi, Lionel Larribère, Qian Sun, et al.. (2018). Loss of neural crest‐associated gene FOXD1 impairs melanoma invasion and migration via RAC1B downregulation. International Journal of Cancer. 143(11). 2962–2972. 24 indexed citations

10.

Hüser, Laura, Daniel Novak, Viktor Umansky, Peter Altevogt, & Jochen Utikal. (2018). Targeting SOX2 in anticancer therapy. Expert Opinion on Therapeutic Targets. 22(12). 983–991. 63 indexed citations

11.

Hüser, Laura, Aniello Federico, Lionel Larribère, et al.. (2018). SOX2‐mediated upregulation of CD24 promotes adaptive resistance toward targeted therapy in melanoma. International Journal of Cancer. 143(12). 3131–3142. 60 indexed citations

12.

Larribère, Lionel, Daniel Novak, H. Christian Volz, et al.. (2017). An RNAi Screen Reveals an Essential Role for HIPK4 in Human Skin Epithelial Differentiation from iPSCs. Stem Cell Reports. 9(4). 1234–1245. 7 indexed citations

13.

Novak, Daniel, Yassen Assenov, Elias Orouji, et al.. (2017). Melanoma-Derived iPCCs Show Differential Tumorigenicity and Therapy Response. Stem Cell Reports. 8(5). 1379–1391. 32 indexed citations

14.

Larribère, Lionel, Daniel Novak, Huizi Wu, et al.. (2017). New role of ID3 in melanoma adaptive drug-resistance. Oncotarget. 8(66). 110166–110175. 19 indexed citations

15.

Weber, Claudia E.M., Marcus Oswald, Volker Ast, et al.. (2016). SOX5 is involved in balanced MITF regulation in human melanoma cells. BMC Medical Genomics. 9(1). 10–10. 25 indexed citations

16.

Novak, Daniel, et al.. (2016). Loss of tumorigenic potential upon transdifferentiation from keratinocytic into melanocytic lineage. Scientific Reports. 6(1). 28891–28891. 9 indexed citations

17.

Novak, Daniel, Kasia Weina, Maike Reith, et al.. (2016). Directed Dedifferentiation Using Partial Reprogramming Induces Invasive Phenotype in Melanoma Cells. Stem Cells. 34(4). 832–846. 24 indexed citations

18.

Utikal, Jochen, Mohammed Abba, Daniel Novak, Marcin Moniuszko, & Heike Allgayer. (2015). Function and significance of MicroRNAs in benign and malignant human stem cells. Seminars in Cancer Biology. 35. 200–211. 18 indexed citations

19.

Wezel, Felix, et al.. (2015). 1006 Directed differentiation of human induced pluripotent stem cells (hiPS) for urothelial cell-based tissue-engineering therapies. European Urology Supplements. 14(2). e1006–e1006. 1 indexed citations

20.

Novak, Daniel, et al.. (2012). Mediators of induced pluripotency and their role in cancer cells – current scientific knowledge and future perspectives. Biotechnology Journal. 7(6). 810–821. 38 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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