Daniel V. Brown

3.6k total citations
29 papers, 859 citations indexed

About

Daniel V. Brown is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Daniel V. Brown has authored 29 papers receiving a total of 859 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 9 papers in Oncology and 5 papers in Cancer Research. Recurrent topics in Daniel V. Brown's work include Cancer Cells and Metastasis (6 papers), Glioma Diagnosis and Treatment (4 papers) and Single-cell and spatial transcriptomics (3 papers). Daniel V. Brown is often cited by papers focused on Cancer Cells and Metastasis (6 papers), Glioma Diagnosis and Treatment (4 papers) and Single-cell and spatial transcriptomics (3 papers). Daniel V. Brown collaborates with scholars based in Australia, United Kingdom and United States. Daniel V. Brown's co-authors include Theo Mantamadiotis, Paul Daniel, Andrew Morokoff, Wayne Ng, Gulay Filiz, Giovanna M. D’Abaco, Frédéric Hollande, Grant A. McArthur, Andrew Gogos and Nicole Kountouri and has published in prestigious journals such as Nucleic Acids Research, Immunity and PLoS ONE.

In The Last Decade

Daniel V. Brown

27 papers receiving 835 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel V. Brown Australia 15 437 275 152 146 100 29 859
Hildegard Meissner Germany 13 384 0.9× 400 1.5× 189 1.2× 322 2.2× 201 2.0× 16 1.1k
Hongquan Yu China 16 732 1.7× 168 0.6× 454 3.0× 138 0.9× 119 1.2× 36 1.0k
Lucia Cappabianca Italy 19 570 1.3× 185 0.7× 282 1.9× 31 0.2× 114 1.1× 45 944
Josef Srovnal Czechia 16 720 1.6× 368 1.3× 520 3.4× 26 0.2× 46 0.5× 53 1.3k
Anna Danielsson Sweden 16 496 1.1× 168 0.6× 219 1.4× 68 0.5× 43 0.4× 31 853
Elias A. El-Habr France 14 267 0.6× 130 0.5× 133 0.9× 128 0.9× 47 0.5× 21 484
Ping‐Pin Zheng Netherlands 15 446 1.0× 170 0.6× 200 1.3× 241 1.7× 124 1.2× 29 921
Cathy Maass Netherlands 15 440 1.0× 186 0.7× 228 1.5× 144 1.0× 139 1.4× 24 995
Satoko Nakada Japan 13 468 1.1× 178 0.6× 158 1.0× 153 1.0× 84 0.8× 38 970

Countries citing papers authored by Daniel V. Brown

Since Specialization
Citations

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

Fields of papers citing papers by Daniel V. Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel V. Brown

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel V. Brown. A scholar is included among the top collaborators of Daniel V. Brown 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 V. Brown. Daniel V. Brown 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.
Theunis, Koen, Sebastiaan Vanuytven, Florian Rambow, et al.. (2025). Single-cell genome and transcriptome sequencing without upfront whole-genome amplification reveals cell state plasticity of melanoma subclones. Nucleic Acids Research. 53(6). 1 indexed citations
2.
Amarasinghe, Shanika L., Chaowei Yang, Mei R. M. Du, et al.. (2023). scPipe: an extended preprocessing pipeline for comprehensive single-cell ATAC-Seq data integration in R/Bioconductor. NAR Genomics and Bioinformatics. 5(4). lqad105–lqad105.
3.
Duffy, Ken R., Daniel V. Brown, Shalin H. Naik, et al.. (2022). Lineage tracing reveals B cell antibody class switching is stochastic, cell-autonomous, and tuneable. Immunity. 55(10). 1843–1855.e6. 8 indexed citations
4.
Zhang, Shengbo, Hannah D. Coughlan, Simona Seizova, et al.. (2021). Type 1 conventional dendritic cell fate and function are controlled by DC-SCRIPT. Science Immunology. 6(58). 27 indexed citations
5.
Trávníčková, Jana, Ava Khamseh, Philippe Gautier, et al.. (2019). Zebrafish MITF-Low Melanoma Subtype Models Reveal Transcriptional Subclusters and MITF-Independent Residual Disease. Cancer Research. 79(22). 5769–5784. 28 indexed citations
6.
Lynch, Matthew, Mei Tran, Kenneth M. Ralto, et al.. (2019). TFEB-driven lysosomal biogenesis is pivotal for PGC1α-dependent renal stress resistance. JCI Insight. 4(8). 45 indexed citations
7.
Brown, Daniel V., Stanley S. Stylli, Andrew H. Kaye, & Theo Mantamadiotis. (2019). Multilayered Heterogeneity of Glioblastoma Stem Cells: Biological and Clinical Significance. Advances in experimental medicine and biology. 1139. 1–21. 12 indexed citations
8.
Sifrim, Alejandro, Marco Fioramonti, Shigeru Matsumura, et al.. (2018). Publisher Correction: Early lineage segregation of multipotent embryonic mammary gland progenitors. Nature Cell Biology. 20(9). 1099–1099. 3 indexed citations
9.
Stylli, Stanley S., Natalie J. Kurganovs, Stefano Mangiola, et al.. (2018). Cell quiescence correlates with enhanced glioblastoma cell invasion and cytotoxic resistance. Experimental Cell Research. 374(2). 353–364. 28 indexed citations
10.
Sifrim, Alejandro, Marco Fioramonti, Shigeru Matsumura, et al.. (2018). Early lineage segregation of multipotent embryonic mammary gland progenitors. Nature Cell Biology. 20(6). 666–676. 109 indexed citations
11.
Brown, Daniel V., Gulay Filiz, Paul Daniel, et al.. (2017). Expression of CD133 and CD44 in glioblastoma stem cells correlates with cell proliferation, phenotype stability and intra-tumor heterogeneity. PLoS ONE. 12(2). e0172791–e0172791. 107 indexed citations
12.
Daniel, Paul, Gulay Filiz, Daniel V. Brown, et al.. (2014). Selective CREB-dependent cyclin expression mediated by the PI3K and MAPK pathways supports glioma cell proliferation. Oncogenesis. 3(6). e108–e108. 83 indexed citations
13.
Kinross, Kathryn M., Daniel V. Brown, Margarete Kleinschmidt, et al.. (2011). In Vivo Activity of Combined PI3K/mTOR and MEK Inhibition in a KrasG12D ; Pten Deletion Mouse Model of Ovarian Cancer. Molecular Cancer Therapeutics. 10(8). 1440–1449. 62 indexed citations
14.
Poortinga, Gretchen, Meaghan Wall, Elaine Sanij, et al.. (2010). c-MYC coordinately regulates ribosomal gene chromatin remodeling and Pol I availability during granulocyte differentiation. Nucleic Acids Research. 39(8). 3267–3281. 76 indexed citations
15.
Kinross, Kathryn M., Daniel V. Brown, Carleen Cullinane, et al.. (2010). Abstract 3484: In vivo activity of combined PI3k/mTOR and MEK-inhibition in a K-RASG12D; PTEN deletion mouse model of ovarian cancer. Cancer Research. 70(8_Supplement). 3484–3484. 1 indexed citations
16.
Mongeau, Luc, et al.. (1997). Analysis of the interior pressure oscillations induced by flow over vehicle openings. Noise Control Engineering Journal. 45(6). 223–223. 44 indexed citations
17.
18.
Brown, Daniel V., et al.. (1970). DEEP-MOORED INSTRUMENT STATION DESIGN AND PERFORMANCE 1967 - 1970,. Defense Technical Information Center (DTIC). 2 indexed citations
19.
Brown, Daniel V.. (1965). Results of Current Measurements with Drogues, 1963-1964.. Defense Technical Information Center (DTIC). 5 indexed citations
20.
Brown, Daniel V., et al.. (1957). Der Abbau von Glucose‐3‐Phosphat Durch Alkali. Chemische Berichte. 90(6). 936–941. 11 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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