Paul Daniel

1.9k total citations
34 papers, 1.3k citations indexed

About

Paul Daniel is a scholar working on Genetics, Molecular Biology and Oncology. According to data from OpenAlex, Paul Daniel has authored 34 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Genetics, 9 papers in Molecular Biology and 9 papers in Oncology. Recurrent topics in Paul Daniel's work include Glioma Diagnosis and Treatment (14 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and MicroRNA in disease regulation (3 papers). Paul Daniel is often cited by papers focused on Glioma Diagnosis and Treatment (14 papers), Radiomics and Machine Learning in Medical Imaging (5 papers) and MicroRNA in disease regulation (3 papers). Paul Daniel collaborates with scholars based in Canada, Australia and United States. Paul Daniel's co-authors include Bassam Abdulkarim, Ahmad Chaddad, Siham Sabri, Theo Mantamadiotis, Bertrand J. Jean‐Claude, Gulay Filiz, Tamim Niazi, Janusz Rak, Brian Meehan and Daniel V. Brown and has published in prestigious journals such as PLoS ONE, Clinical Cancer Research and International Journal of Radiation Oncology*Biology*Physics.

In The Last Decade

Paul Daniel

29 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Paul Daniel Canada 19 409 394 308 283 254 34 1.3k
McKinsey L. Goodenberger United States 7 245 0.6× 354 0.9× 111 0.4× 221 0.8× 107 0.4× 11 834
Carsten Hagemann Germany 26 320 0.8× 1.1k 2.8× 59 0.2× 419 1.5× 404 1.6× 74 2.0k
Cholpon S. Djuzenova Germany 20 75 0.2× 657 1.7× 197 0.6× 262 0.9× 182 0.7× 41 1.1k
Sung Choe United States 20 183 0.4× 1.1k 2.8× 94 0.3× 345 1.2× 243 1.0× 48 1.8k
Janet L. Gross United States 21 112 0.3× 874 2.2× 233 0.8× 327 1.2× 325 1.3× 39 1.6k
Hitesh Patel United Kingdom 22 333 0.8× 1.1k 2.8× 45 0.1× 169 0.6× 367 1.4× 44 2.3k
Christopher H. Lowrey United States 24 556 1.4× 1.1k 2.8× 99 0.3× 204 0.7× 308 1.2× 59 1.9k
Min Lu United States 14 171 0.4× 669 1.7× 51 0.2× 340 1.2× 368 1.4× 32 1.4k
Anna D. Barker United States 13 86 0.2× 407 1.0× 62 0.2× 277 1.0× 188 0.7× 31 899
Tali Mazor United States 15 312 0.8× 563 1.4× 41 0.1× 293 1.0× 221 0.9× 30 1.1k

Countries citing papers authored by Paul Daniel

Since Specialization
Citations

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

Fields of papers citing papers by Paul Daniel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Paul Daniel

This figure shows the co-authorship network connecting the top 25 collaborators of Paul Daniel. A scholar is included among the top collaborators of Paul Daniel 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 Paul Daniel. Paul Daniel 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.
Daniel, Paul, et al.. (2024). Synergistic Dual Targeting of Thioredoxin and Glutathione Systems Irrespective of p53 in Glioblastoma Stem Cells. Antioxidants. 13(10). 1201–1201. 5 indexed citations
2.
Liang, Yuqing, et al.. (2024). Emerging and Biological Concepts in Pediatric High-Grade Gliomas. Cells. 13(17). 1492–1492. 3 indexed citations
3.
Voon, Hsiao P. J., Linda Hii, Maheshi Udugama, et al.. (2023). Pediatric glioma histone H3.3 K27M/G34R mutations drive abnormalities in PML nuclear bodies. Genome biology. 24(1). 284–284. 12 indexed citations
4.
Firestein, Ron, et al.. (2023). A protocol to establish cell line models from rare pediatric solid tumors. STAR Protocols. 4(3). 102537–102537. 3 indexed citations
5.
Abdulkarim, Bassam, Brian Meehan, Janusz Rak, et al.. (2019). Mechanisms and Antitumor Activity of a Binary EGFR/DNA–Targeting Strategy Overcomes Resistance of Glioblastoma Stem Cells to Temozolomide. Clinical Cancer Research. 25(24). 7594–7608. 30 indexed citations
6.
Chaddad, Ahmad, Paul Daniel, Siham Sabri, Christian Desrosiers, & Bassam Abdulkarim. (2019). Integration of Radiomic and Multi-omic Analyses Predicts Survival of Newly Diagnosed IDH1 Wild-Type Glioblastoma. Cancers. 11(8). 1148–1148. 48 indexed citations
7.
Daniel, Paul, Siham Sabri, Ahmad Chaddad, et al.. (2019). Temozolomide Induced Hypermutation in Glioma: Evolutionary Mechanisms and Therapeutic Opportunities. Frontiers in Oncology. 9. 41–41. 118 indexed citations
8.
Chaddad, Ahmad, Michael Jonathan Kucharczyk, Paul Daniel, et al.. (2019). Radiomics in Glioblastoma: Current Status and Challenges Facing Clinical Implementation. Frontiers in Oncology. 9. 374–374. 132 indexed citations
9.
Nguyen, Hong, Paul Daniel, Gulay Filiz, & Theo Mantamadiotis. (2018). Investigating Neural Stem Cell and Glioma Stem Cell Self-renewal Potential Using Extreme Limiting Dilution Analysis (ELDA). BIO-PROTOCOL. 8(17). e2991–e2991. 13 indexed citations
10.
Chaddad, Ahmad, Paul Daniel, & Tamim Niazi. (2018). Radiomics Evaluation of Histological Heterogeneity Using Multiscale Textures Derived From 3D Wavelet Transformation of Multispectral Images. Frontiers in Oncology. 8. 96–96. 40 indexed citations
11.
Daniel, Paul, Gulay Filiz, Martin J. Tymms, et al.. (2018). Intratumor MAPK and PI3K signaling pathway heterogeneity in glioblastoma tissue correlates with CREB signaling and distinct target gene signatures. Experimental and Molecular Pathology. 105(1). 23–31. 23 indexed citations
12.
Daniel, Paul, et al.. (2017). A study on analysing customer preferences and buying patterns towards organised retailing with reference to Spencer’s retail outlet, Guntur district. International Journal of Academic Research and Development. 2(6). 1156–1159. 1 indexed citations
13.
Garnier, Delphine, Brian Meehan, Thomas Kislinger, et al.. (2017). Divergent evolution of temozolomide resistance in glioblastoma stem cells is reflected in extracellular vesicles and coupled with radiosensitization. Neuro-Oncology. 20(2). 236–248. 107 indexed citations
14.
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
15.
Daniel, Paul, Gulay Filiz, & Theo Mantamadiotis. (2016). Sensitivity of GBM cells to cAMP agonist-mediated apoptosis correlates with CD44 expression and agonist resistance with MAPK signaling. Cell Death and Disease. 7(12). e2494–e2494. 28 indexed citations
16.
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
17.
18.
Marples, Brian, et al.. (1998). DNA Damage in Human and Mouse Spermatozoa after In Vitro-Irradiation Assessed by the Comet Assay. Advances in experimental medicine and biology. 444. 79–93. 101 indexed citations
19.
Daniel, Paul & John J. Wheeler. (1989). Social Work and Local Politics. 8 indexed citations
20.
Daniel, Paul & Tim Dexter. (1989). The role of growth factors in haemopoietic development: Clinical and biological implications. Cancer and Metastasis Reviews. 8(3). 253–262. 3 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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