Daniele Campa

11.3k total citations
73 papers, 2.0k citations indexed

About

Daniele Campa is a scholar working on Molecular Biology, Oncology and Cancer Research. According to data from OpenAlex, Daniele Campa has authored 73 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 27 papers in Oncology and 14 papers in Cancer Research. Recurrent topics in Daniele Campa's work include Pancreatic and Hepatic Oncology Research (18 papers), Epigenetics and DNA Methylation (14 papers) and Cancer Genomics and Diagnostics (9 papers). Daniele Campa is often cited by papers focused on Pancreatic and Hepatic Oncology Research (18 papers), Epigenetics and DNA Methylation (14 papers) and Cancer Genomics and Diagnostics (9 papers). Daniele Campa collaborates with scholars based in Italy, Germany and Spain. Daniele Campa's co-authors include Federico Canzian, Roberto Barale, Aage Haugen, Shanbeh Zienolddiny, Vidar Skaug, David Ryberg, Helge Lind, A Gioia, Paolo Fusar‐Poli and Lodve Stangeland and has published in prestigious journals such as Blood, PLoS ONE and Cancer.

In The Last Decade

Daniele Campa

71 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniele Campa Italy 23 811 515 374 242 211 73 2.0k
Huijuan Liu China 28 1.1k 1.3× 398 0.8× 260 0.7× 146 0.6× 193 0.9× 112 2.1k
Eva Lundin Sweden 30 929 1.1× 857 1.7× 334 0.9× 471 1.9× 134 0.6× 79 2.9k
Sudha Ananth United States 23 1.3k 1.6× 443 0.9× 217 0.6× 178 0.7× 235 1.1× 36 2.3k
Xiuyan Yang China 29 970 1.2× 302 0.6× 324 0.9× 109 0.5× 211 1.0× 133 2.7k
Leandro Fernández‐Pérez Spain 28 856 1.1× 488 0.9× 269 0.7× 336 1.4× 199 0.9× 95 2.2k
Lijun Tan China 24 1.2k 1.5× 347 0.7× 331 0.9× 335 1.4× 144 0.7× 87 2.3k
Jianmin Huang United States 27 1.2k 1.5× 158 0.3× 177 0.5× 233 1.0× 148 0.7× 86 2.1k
Stefania Marsico Italy 22 628 0.8× 554 1.1× 316 0.8× 469 1.9× 62 0.3× 55 2.0k

Countries citing papers authored by Daniele Campa

Since Specialization
Citations

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

Fields of papers citing papers by Daniele Campa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniele Campa

This figure shows the co-authorship network connecting the top 25 collaborators of Daniele Campa. A scholar is included among the top collaborators of Daniele Campa 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 Daniele Campa. Daniele Campa 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.
Tacelli, Matteo, Manuel Gentiluomo, Justo P. Castaño, et al.. (2025). Pancreatic neuroendocrine neoplasms (pNENs): Genetic and environmental biomarkers for risk of occurrence and prognosis. Seminars in Cancer Biology. 112. 112–125. 3 indexed citations
2.
Campa, Daniele, et al.. (2025). Artificial intelligence to predict cancer risk, are we there yet? A comprehensive review across cancer types. European Journal of Cancer. 222. 115440–115440. 1 indexed citations
3.
4.
Comandatore, Annalisa, Gregorio Di Franco, Ingrid Garajová, et al.. (2025). Long-term recurrence of PDAC after resection for IPMN: A narrative review of the literature on clinical and biologic predictors. Seminars in Cancer Biology. 114. 1–14.
5.
Real, Carla, Manuel Gentiluomo, Andrea Čumová, et al.. (2025). Genomic instability, DNA damage response and telomere homeostasis in pancreatic cancer. Seminars in Cancer Biology. 113. 59–73. 1 indexed citations
6.
Tost, Jörg, Daniele Campa, Alejandro Ibáñez‐Costa, et al.. (2025). Leveraging epigenetic alterations in pancreatic ductal adenocarcinoma for clinical applications. Seminars in Cancer Biology. 109. 101–124. 3 indexed citations
7.
Rizzato, Cosmeri, et al.. (2025). The relationship of the microbiome, associated metabolites and the gut barrier with pancreatic cancer. Seminars in Cancer Biology. 112. 43–57. 4 indexed citations
8.
Campa, Daniele, et al.. (2024). Explainable machine learning identifies a polygenic risk score as a key predictor of pancreatic cancer risk in the UK Biobank. Digestive and Liver Disease. 57(4). 915–922. 4 indexed citations
9.
Stocker, Hannah, Manuel Gentiluomo, Kira Trares, et al.. (2024). Mitochondrial DNA abundance in blood is associated with Alzheimer’s disease- and dementia-risk. Molecular Psychiatry. 30(1). 131–139. 8 indexed citations
10.
Corradi, Chiara, Manuel Gentiluomo, Volkan Adsay, et al.. (2024). Multi-omic markers of intraductal papillary mucinous neoplasms progression into pancreatic cancer. Seminars in Cancer Biology. 109. 25–43. 1 indexed citations
11.
Gentiluomo, Manuel, Gabriele Capurso, Anna Monreale, et al.. (2023). Analysis of exposome and genetic variability suggests stress as a major contributor for development of pancreatic ductal adenocarcinoma. Digestive and Liver Disease. 56(6). 1054–1063. 8 indexed citations
12.
Calderisi, Marco, et al.. (2023). The local environment and germline genetic variation predict cancer risk in the UK Biobank prospective cohort. Environmental Research. 241. 117562–117562. 8 indexed citations
13.
Campa, Daniele, et al.. (2023). Long or short? Telomere length and pancreatic cancer and its precursor lesions, a narrative review. Mutagenesis. 40(1). 39–47. 5 indexed citations
14.
Rizzato, Cosmeri, Daria Bottai, Federica Gemignani, et al.. (2022). Maternal anthropometric variables and clinical factors shape neonatal microbiome. Scientific Reports. 12(1). 2875–2875. 4 indexed citations
15.
Ciantelli, Massimiliano, Manuel Gentiluomo, Cosmeri Rizzato, et al.. (2020). Role of OPRM1, clinical and anthropometric variants in neonatal pain reduction. Scientific Reports. 10(1). 7091–7091. 4 indexed citations
16.
Buda, Gabriele, Giovanni Carulli, Enrico Orciuolo, et al.. (2014). CD69, a New Potential Clinical Marker in Multiple Myeloma. Blood. 124(21). 2027–2027. 2 indexed citations
17.
Campa, Daniele, Lutz Edler, Roberto Barale, et al.. (2012). A comprehensive study of polymorphisms inABCB1, ABCC2andABCG2and lung cancer chemotherapy response and prognosis. International Journal of Cancer. 131(12). 2920–2928. 58 indexed citations
18.
Rizzato, Cosmeri, Dominique Scherer, Péter Rudnai, et al.. (2011). POMC and TP53 genetic variability and risk of basal cell carcinoma of skin: Interaction between host and genetic factors. Journal of Dermatological Science. 63(1). 47–54. 16 indexed citations
19.
Rizzato, Cosmeri, Federico Canzian, Péter Rudnai, et al.. (2011). Interaction between functional polymorphic variants in cytokine genes, established risk factors and susceptibility to basal cell carcinoma of skin. Carcinogenesis. 32(12). 1849–1854. 18 indexed citations
20.
Campa, Daniele, Rayjean J. Hung, Dana Mateș, et al.. (2005). Lack of Association between Polymorphisms in Inflammatory Genes and Lung Cancer Risk. Cancer Epidemiology Biomarkers & Prevention. 14(2). 538–539. 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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