Michele Ceccarelli

17.6k total citations · 2 hit papers
170 papers, 6.5k citations indexed

About

Michele Ceccarelli is a scholar working on Molecular Biology, Cancer Research and Oncology. According to data from OpenAlex, Michele Ceccarelli has authored 170 papers receiving a total of 6.5k indexed citations (citations by other indexed papers that have themselves been cited), including 86 papers in Molecular Biology, 41 papers in Cancer Research and 22 papers in Oncology. Recurrent topics in Michele Ceccarelli's work include Cancer Genomics and Diagnostics (22 papers), Gene expression and cancer classification (19 papers) and Cancer Immunotherapy and Biomarkers (18 papers). Michele Ceccarelli is often cited by papers focused on Cancer Genomics and Diagnostics (22 papers), Gene expression and cancer classification (19 papers) and Cancer Immunotherapy and Biomarkers (18 papers). Michele Ceccarelli collaborates with scholars based in Italy, United States and Qatar. Michele Ceccarelli's co-authors include Luciano Garofano, Stefano Maria Pagnotta, Thaís S. Sabedot, Houtan Noushmehr, Isabella Castiglioni, Tiago C. Silva, Tathiane M. Malta, Antonio Colaprico, Catharina Olsen and Claudia Cava and has published in prestigious journals such as Cell, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Michele Ceccarelli

159 papers receiving 6.4k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data

2015 2.4k citations Luciano Garofano, Stefano Maria Pagnotta et al. profile →
RNA-Seq Signatures Normalized by mRNA Abundance Allow Absolute Deconvolution of Human Immune Cell Types

2019 502 citations Michele Ceccarelli et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Michele Ceccarelli Italy	33	3.6k	1.9k	1.5k	1.2k	1.1k	170	6.5k
Zexian Zeng United States	17	2.8k 0.8×	1.3k 0.7×	1.3k 0.9×	1.7k 1.4×	1.0k 1.0×	43	4.8k
Tuan Zea Tan Singapore	41	3.6k 1.0×	1.7k 0.9×	2.2k 1.5×	740 0.6×	727 0.7×	152	6.1k
Holly K. Dressman United States	39	4.5k 1.3×	1.9k 1.0×	1.4k 0.9×	716 0.6×	421 0.4×	75	6.7k
Kevin R. Coombes United States	53	6.8k 1.9×	2.1k 1.1×	1.7k 1.1×	884 0.7×	873 0.8×	241	10.2k
Katherine Phillippy United States	11	6.5k 1.8×	2.0k 1.1×	895 0.6×	1.3k 1.1×	1000 0.9×	12	9.1k
Graham Ball United Kingdom	42	3.3k 0.9×	2.0k 1.1×	1.8k 1.2×	506 0.4×	485 0.5×	172	6.4k
Sudhir Varma United States	36	3.6k 1.0×	1.3k 0.7×	1.9k 1.2×	769 0.6×	329 0.3×	77	6.9k
Florian Markowetz United Kingdom	33	2.9k 0.8×	1.6k 0.8×	1.4k 1.0×	717 0.6×	393 0.4×	94	5.6k
Irene F. Kim United States	8	7.2k 2.0×	2.3k 1.2×	989 0.7×	1.4k 1.2×	1.1k 1.0×	8	10.1k
Sampsa Hautaniemi Finland	49	4.9k 1.4×	1.6k 0.8×	1.5k 1.0×	777 0.6×	529 0.5×	186	7.6k

Countries citing papers authored by Michele Ceccarelli

Since Specialization

Citations

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

Fields of papers citing papers by Michele Ceccarelli

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michele Ceccarelli

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

Caruso, Francesca Pia, Teresa Noviello, Roberta Mortarini, et al.. (2025). DNA methylation status classifies pleural mesothelioma cells according to their immune profile: implication for precision epigenetic therapy. Journal of Experimental & Clinical Cancer Research. 44(1). 58–58. 1 indexed citations

Telonis, Aristeidis G., Qin Yang, Limin Jiang, et al.. (2025). Genome-wide methylome modeling via generative AI incorporating long- and short-range interactions. Science Advances. 11(15). eadt4152–eadt4152. 3 indexed citations

Floudas, Charalampos S., Siranush Sarkizova, Michele Ceccarelli, & Wei Zheng. (2025). Leveraging mRNA technology for antigen based immuno-oncology therapies. Journal for ImmunoTherapy of Cancer. 13(1). e010569–e010569. 7 indexed citations

Noviello, Teresa, Anna Maria Di Giacomo, Francesca Pia Caruso, et al.. (2023). Guadecitabine plus ipilimumab in unresectable melanoma: five-year follow-up and integrated multi-omic analysis in the phase 1b NIBIT-M4 trial. Nature Communications. 14(1). 5914–5914. 18 indexed citations

Caruso, Francesca Pia, et al.. (2023). A variational algorithm to detect the clonal copy number substructure of tumors from scRNA-seq data. Nature Communications. 14(1). 1074–1074. 42 indexed citations

Ceccarelli, Michele, et al.. (2023). Fast, accurate, and racially unbiased pan-cancer tumor-only variant calling with tabular machine learning. npj Precision Oncology. 7(1). 4–4. 8 indexed citations

Migliozzi, Simona, Young Taek Oh, Mohammad Hasanain, et al.. (2023). Integrative multi-omics networks identify PKCδ and DNA-PK as master kinases of glioblastoma subtypes and guide targeted cancer therapy. Nature Cancer. 4(2). 181–202. 49 indexed citations

Ceccarelli, Michele, et al.. (2023). The epitranscriptome of high-grade gliomas: a promising therapeutic target with implications from the tumor microenvironment to endogenous retroviruses. Journal of Translational Medicine. 21(1). 893–893. 7 indexed citations

Bertucci, François, Alexandre de Nonneville, Pascal Finetti, et al.. (2022). Immunologic constant of rejection signature is prognostic in soft-tissue sarcoma and refines the CINSARC signature. Journal for ImmunoTherapy of Cancer. 10(1). e003687–e003687. 17 indexed citations

10.

Mair, Maximilian J., Michele Ceccarelli, Andrea Anichini, et al.. (2022). Immunotherapy for brain metastases and primary brain tumors. European Journal of Cancer. 179. 113–120. 13 indexed citations

11.

Marco, Carmela De, Pietro Zoppoli, Sandro Morganella, et al.. (2021). Genome-wide analysis of copy number alterations led to the characterisation of PDCD10 as oncogene in ovarian cancer. Translational Oncology. 14(3). 101013–101013. 16 indexed citations

12.

Dezső, Zoltán & Michele Ceccarelli. (2020). Machine learning prediction of oncology drug targets based on protein and network properties. BMC Bioinformatics. 21(1). 104–104. 35 indexed citations

13.

Caruso, Francesca Pia, Luciano Garofano, Fulvio D’Angelo, et al.. (2020). A map of tumor–host interactions in glioma at single-cell resolution. GigaScience. 9(10). 31 indexed citations

14.

Hendrickx, Wouter, Ines Simeone, Samreen Anjum, et al.. (2017). Identification of genetic determinants of breast cancer immune phenotypes by integrative genome-scale analysis. OncoImmunology. 6(2). e1253654–e1253654. 128 indexed citations

15.

Cerulo, Luigi, Pina Marotta, Pietro Zoppoli, et al.. (2014). Identification of a Novel Gene Signature of ES Cells Self-Renewal Fluctuation through System-Wide Analysis. PLoS ONE. 9(1). e83235–e83235. 21 indexed citations

16.

Silvestri, Elena, Federica Cioffi, María Moreno, et al.. (2012). Metabolic effects of the iodothyronine functional analogue TRC150094 on the liver and skeletal muscle of high-fat diet fed overweight rats: an integrated proteomic study. Molecular BioSystems. 8(7). 1987–2000. 14 indexed citations

17.

Silvestri, Elena, Federica Cioffi, Michele Ceccarelli, et al.. (2010). Pathways affected by 3,5-diiodo- l -thyronine in liver of high fat-fed rats: Evidence from two-dimensional electrophoresis, blue-native PAGE, and mass spectrometry. Molecular BioSystems. 6(11). 2256–2271. 31 indexed citations

18.

Ceccarelli, Michele, et al.. (2009). A Guideline Engine For Knowledge Management in Clinical Decision Support Systems (CDSSs).. Software Engineering and Knowledge Engineering. 252–257. 2 indexed citations

19.

Ceccarelli, Michele, et al.. (2008). A deformable grid approach for Bayesian image registration. International Conference on Signal Processing. 145–150. 1 indexed citations

20.

d’Acierno, Antonio, Michele Ceccarelli, Alfonso Farina, Alfredo Petrosino, & L. Timmoneri. (1994). Mapping QR Decomposition on Parallel Computers: A Study Case for Radar Applications. IEICE Transactions on Communications. 77(10). 1264–1271. 2 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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