Mark W. Hurd

3.8k total citations
40 papers, 1.1k citations indexed

About

Mark W. Hurd is a scholar working on Oncology, Endocrine and Autonomic Systems and Cancer Research. According to data from OpenAlex, Mark W. Hurd has authored 40 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Oncology, 12 papers in Endocrine and Autonomic Systems and 10 papers in Cancer Research. Recurrent topics in Mark W. Hurd's work include Pancreatic and Hepatic Oncology Research (13 papers), Circadian rhythm and melatonin (12 papers) and Cancer Genomics and Diagnostics (6 papers). Mark W. Hurd is often cited by papers focused on Pancreatic and Hepatic Oncology Research (13 papers), Circadian rhythm and melatonin (12 papers) and Cancer Genomics and Diagnostics (6 papers). Mark W. Hurd collaborates with scholars based in United States, Canada and Netherlands. Mark W. Hurd's co-authors include Martin R. Ralph, Gregory M. Cahill, Evelyn Satinoff, Stephen Kent, Jason P. DeBruyne, Martin Straume, Anirban Maitra, Diana J. Vincent, Ed Wirth and Virginia L. Winder and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Cancer Research.

In The Last Decade

Mark W. Hurd

38 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark W. Hurd United States 17 466 244 205 170 162 40 1.1k
Gad D. Vatine Israel 19 421 0.9× 237 1.0× 456 2.2× 711 4.2× 135 0.8× 37 2.1k
Koyomi Miyazaki Japan 24 823 1.8× 380 1.6× 194 0.9× 415 2.4× 170 1.0× 49 1.6k
Fu‐Chia Yang United States 15 477 1.0× 252 1.0× 413 2.0× 467 2.7× 193 1.2× 16 1.3k
Thomas Dickmeis Germany 24 680 1.5× 379 1.6× 230 1.1× 791 4.7× 92 0.6× 46 2.0k
Joel Greenwood United States 9 192 0.4× 120 0.5× 218 1.1× 233 1.4× 127 0.8× 13 722
Elena Frigato Italy 20 389 0.8× 149 0.6× 214 1.0× 171 1.0× 58 0.4× 38 923
Shogo Haraguchi Japan 19 484 1.0× 202 0.8× 359 1.8× 405 2.4× 40 0.2× 68 1.7k
Sofia I.H. Godinho United Kingdom 13 927 2.0× 310 1.3× 305 1.5× 322 1.9× 210 1.3× 13 1.4k
Douglas J. Guarnieri United States 20 641 1.4× 266 1.1× 450 2.2× 419 2.5× 364 2.2× 22 1.5k
Dong Won Kim United States 22 267 0.6× 175 0.7× 215 1.0× 577 3.4× 178 1.1× 72 1.5k

Countries citing papers authored by Mark W. Hurd

Since Specialization
Citations

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

Fields of papers citing papers by Mark W. Hurd

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark W. Hurd. 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 Mark W. Hurd. The network helps show where Mark W. Hurd may publish in the future.

Co-authorship network of co-authors of Mark W. Hurd

This figure shows the co-authorship network connecting the top 25 collaborators of Mark W. Hurd. A scholar is included among the top collaborators of Mark W. Hurd 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 Mark W. Hurd. Mark W. Hurd 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.
Chen, Yihui, Rongzhang Dou, Ehsan Irajizad, et al.. (2025). Integrated Metabolomics and Spatial Transcriptomics of Cystic Pancreatic Cancer Precursors Reveals Dysregulated Polyamine Metabolism as a Biomarker of Progression. Clinical Cancer Research. 31(12). 2454–2465.
2.
Treekitkarnmongkol, Warapen, Jianliang Dai, Suyu Liu, et al.. (2025). An integrated multi‐omics biomarker approach using molecular profiling and microRNAs for evaluation of pancreatic cyst fluid. Cancer Cytopathology. 133(4). e70008–e70008. 2 indexed citations
3.
Yousef, Abdelrahman, Mark W. Hurd, Huamin Wang, et al.. (2024). Molecular and clinical features of pancreatic acinar cell carcinoma: A single institutional experience.. Journal of Clinical Oncology. 42(16_suppl). e16335–e16335.
4.
Bahrambeigi, Vahid, Jaewon J. Lee, Vittorio Branchi, et al.. (2024). Transcriptomic Profiling of Plasma Extracellular Vesicles Enables Reliable Annotation of the Cancer-Specific Transcriptome and Molecular Subtype. Cancer Research. 84(10). 1719–1732. 6 indexed citations
5.
Treekitkarnmongkol, Warapen, Jianliang Dai, Suyu Liu, et al.. (2024). Blood-Based microRNA Biomarker Signature of Early-Stage Pancreatic Ductal Adenocarcinoma With Lead-Time Trajectory in Prediagnostic Samples. SHILAP Revista de lepidopterología. 3(8). 1098–1115. 4 indexed citations
6.
Haab, Brian B., Qian Lu, Ben Staal, et al.. (2024). A rigorous multi-laboratory study of known PDAC biomarkers identifies increased sensitivity and specificity over CA19-9 alone. Cancer Letters. 604. 217245–217245. 5 indexed citations
7.
Hurd, Mark W., Abdelrahman Yousef, Ethan B. Ludmir, et al.. (2024). Clinical and molecular characteristics of patients with brain metastasis secondary to pancreatic ductal adenocarcinoma. The Oncologist. 30(1). 1 indexed citations
8.
9.
Schalck, Aislyn, Donastas Sakellariou-Thompson, Marie‐Andrée Forget, et al.. (2022). Single-Cell Sequencing Reveals Trajectory of Tumor-Infiltrating Lymphocyte States in Pancreatic Cancer. Cancer Discovery. 12(10). 2330–2349. 44 indexed citations
10.
Dittmar, Rachel L., Suyu Liu, Mei-Chee Tai, et al.. (2021). Plasma miRNA Biomarkers in Limited Volume Samples for Detection of Early-stage Pancreatic Cancer. Cancer Prevention Research. 14(7). 729–740. 27 indexed citations
11.
Zaid, Mohamed, Baishali Chaudhury, J. Zhang, et al.. (2020). Pancreatic Ductal Adenocarcinoma Immune and Stromal Elements Differ in Spatial Distribution Based on Response to Chemoradiation. International Journal of Radiation Oncology*Biology*Physics. 108(3). e606–e606. 1 indexed citations
12.
Staal, Ben, Ying Liu, Zonglin He, et al.. (2019). The sTRA Plasma Biomarker: Blinded Validation of Improved Accuracy Over CA19-9 in Pancreatic Cancer Diagnosis. Clinical Cancer Research. 25(9). 2745–2754. 34 indexed citations
13.
Vicente, Diego, Andrew Lee, Carolyn Hall, et al.. (2019). Circulating Tumor Cells and Transforming Growth Factor Beta in Resected Pancreatic Adenocarcinoma. Journal of Surgical Research. 243. 90–99. 10 indexed citations
14.
Bonilha, Leonardo, Diana J. Vincent, Chris Rorden, et al.. (2007). Structural white matter abnormalities in patients with idiopathic dystonia. Movement Disorders. 22(8). 1110–1116. 53 indexed citations
15.
16.
Hurd, Mark W. & Lars Nyberg. (2004). Value Factor : How Global Leaders Use Information for Growth and Competitive Advantage. 5 indexed citations
17.
Hurd, Mark W., Jason P. DeBruyne, Martin Straume, & Gregory M. Cahill. (1998). Circadian Rhythms of Locomotor Activity in Zebrafish. Physiology & Behavior. 65(3). 465–472. 121 indexed citations
18.
Cahill, Gregory M., et al.. (1998). Circadian rhythmicity in the locomotor activity of larval zebrafish. Neuroreport. 9(15). 3445–3449. 87 indexed citations
19.
Ralph, Martin R., et al.. (1996). Chapter 13 Regulation and integration in the mammalian circadian system. Progress in brain research. 111. 191–203. 7 indexed citations
20.
Kent, Stephen, Mark W. Hurd, & Evelyn Satinoff. (1991). Phentolamine and thermoregulation in rats. Pharmacology Biochemistry and Behavior. 40(4). 709–716. 43 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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