Claudia Cava

7.0k total citations · 2 hit papers
64 papers, 4.2k citations indexed

About

Claudia Cava is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Claudia Cava has authored 64 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 48 papers in Molecular Biology, 30 papers in Cancer Research and 10 papers in Genetics. Recurrent topics in Claudia Cava's work include MicroRNA in disease regulation (19 papers), Bioinformatics and Genomic Networks (19 papers) and Gene expression and cancer classification (13 papers). Claudia Cava is often cited by papers focused on MicroRNA in disease regulation (19 papers), Bioinformatics and Genomic Networks (19 papers) and Gene expression and cancer classification (13 papers). Claudia Cava collaborates with scholars based in Italy, Iran and United States. Claudia Cava's co-authors include Isabella Castiglioni, Gloria Bertoli, Gianluca Bontempi, Antonio Colaprico, Catharina Olsen, Tiago C. Silva, Houtan Noushmehr, Luciano Garofano, Michele Ceccarelli and Stefano Maria Pagnotta and has published in prestigious journals such as Nucleic Acids Research, Nature Communications and SHILAP Revista de lepidopterología.

In The Last Decade

Claudia Cava

59 papers receiving 4.1k citations

Hit Papers

TCGAbiolinks: an R/Bioconductor package for integrative a... 2015 2026 2018 2022 2015 2015 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Claudia Cava Italy 22 2.9k 2.0k 929 821 368 64 4.2k
Patrycja Czerwińska Poland 12 2.2k 0.8× 1.2k 0.6× 826 0.9× 593 0.7× 416 1.1× 23 3.2k
Jesse S. Boehm United States 30 2.9k 1.0× 1.5k 0.7× 949 1.0× 1.2k 1.4× 274 0.7× 51 4.3k
Shanker Kalyana‐Sundaram United States 23 3.8k 1.3× 1.6k 0.8× 1.3k 1.4× 875 1.1× 349 0.9× 30 5.1k
Katarzyna Tomczak United States 8 2.0k 0.7× 1.2k 0.6× 831 0.9× 579 0.7× 275 0.7× 10 2.9k
Patricia Greninger United States 21 3.7k 1.2× 1.4k 0.7× 1.4k 1.5× 1.6k 2.0× 425 1.2× 33 5.2k
Sandra O’Toole Australia 35 2.5k 0.8× 1.4k 0.7× 1.0k 1.1× 1.9k 2.3× 375 1.0× 105 4.3k
Fei Yang China 27 3.0k 1.0× 1.6k 0.8× 431 0.5× 1.5k 1.8× 342 0.9× 108 4.8k
Guanglei Zhuang China 34 2.6k 0.9× 1.0k 0.5× 563 0.6× 1.4k 1.8× 716 1.9× 75 4.2k
David Tamborero Spain 29 2.0k 0.7× 1.3k 0.7× 494 0.5× 511 0.6× 214 0.6× 62 4.5k
Libero Santarpia Italy 37 3.3k 1.1× 2.2k 1.1× 773 0.8× 1.8k 2.2× 447 1.2× 89 5.4k

Countries citing papers authored by Claudia Cava

Since Specialization
Citations

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

Fields of papers citing papers by Claudia Cava

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Claudia Cava

This figure shows the co-authorship network connecting the top 25 collaborators of Claudia Cava. A scholar is included among the top collaborators of Claudia Cava 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 Claudia Cava. Claudia Cava 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.
Cava, Claudia, et al.. (2024). Pan-cancer classification of multi-omics data based on machine learning models. Network Modeling Analysis in Health Informatics and Bioinformatics. 13(1). 3 indexed citations
2.
Cava, Claudia, et al.. (2023). From genetic correlations of Alzheimer’s disease to classification with artificial neural network models. Functional & Integrative Genomics. 23(4). 293–293. 1 indexed citations
3.
Pathak, Gita A., et al.. (2023). Phenome-wide genetic-correlation analysis and genetically informed causal inference of amyotrophic lateral sclerosis. Human Genetics. 142(8). 1173–1183. 3 indexed citations
4.
Castiglioni, Isabella, et al.. (2023). Computational analysis of five neurodegenerative diseases reveals shared and specific genetic loci. Computational and Structural Biotechnology Journal. 21. 5395–5407. 4 indexed citations
6.
Cava, Claudia, et al.. (2022). Diagnostic Circulating miRNAs in Sporadic Amyotrophic Lateral Sclerosis. Frontiers in Medicine. 9. 861960–861960. 16 indexed citations
7.
Cava, Claudia, Alexandros Armaos, Benjamin Lang, Gian Gaetano Tartaglia, & Isabella Castiglioni. (2022). Identification of long non-coding RNAs and RNA binding proteins in breast cancer subtypes. Scientific Reports. 12(1). 693–693. 18 indexed citations
8.
Frasca, Marco, et al.. (2022). Identification of key miRNAs in prostate cancer progression based on miRNA-mRNA network construction. Computational and Structural Biotechnology Journal. 20. 864–873. 7 indexed citations
9.
10.
Fortunato, Francesco, Claudia Cava, Francesca Gallivanone, et al.. (2021). Circulating microRNAs as Potential Novel Diagnostic Biomarkers to Predict Drug Resistance in Temporal Lobe Epilepsy: A Pilot Study. International Journal of Molecular Sciences. 22(2). 702–702. 36 indexed citations
11.
Cava, Claudia, Gloria Bertoli, & Isabella Castiglioni. (2020). A protein interaction map identifies existing drugs targeting SARS-CoV-2. BMC Pharmacology and Toxicology. 21(1). 65–65. 14 indexed citations
12.
Cava, Claudia, Chiara Novello, Cristina Martelli, et al.. (2019). Theranostic application of miR-429 in HER2+ breast cancer. Theranostics. 10(1). 50–61. 20 indexed citations
13.
Cava, Claudia & Isabella Castiglioni. (2019). In silico perturbation of drug targets in pan-cancer analysis combining multiple networks and pathways. Gene. 698. 100–106. 6 indexed citations
14.
Cava, Claudia, Ida Manna, Antonio Gambardella, Gloria Bertoli, & Isabella Castiglioni. (2018). Potential Role of miRNAs as Theranostic Biomarkers of Epilepsy. Molecular Therapy — Nucleic Acids. 13. 275–290. 35 indexed citations
15.
Bertoli, Gloria, Claudia Cava, Cecilia Diceglie, et al.. (2016). MicroRNA-567 dysregulation contributes to carcinogenesis of breast cancer, targeting tumor cell proliferation, and migration. Breast Cancer Research and Treatment. 161(3). 605–616. 31 indexed citations
16.
Bertoli, Gloria, Claudia Cava, & Isabella Castiglioni. (2016). The potential of miRNAs for diagnosis, treatment and monitoring of breast cancer. Scandinavian Journal of Clinical and Laboratory Investigation. 76(sup245). S34–S39. 24 indexed citations
17.
Cava, Claudia, Antonio Colaprico, Gloria Bertoli, et al.. (2016). How interacting pathways are regulated by miRNAs in breast cancer subtypes. BMC Bioinformatics. 17(S12). 348–348. 25 indexed citations
18.
Cava, Claudia, Gloria Bertoli, & Isabella Castiglioni. (2015). Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential. BMC Systems Biology. 9(1). 62–62. 40 indexed citations
19.
Cava, Claudia, Gloria Bertoli, Marilena Ripamonti, et al.. (2014). Integration of mRNA Expression Profile, Copy Number Alterations, and microRNA Expression Levels in Breast Cancer to Improve Grade Definition. PLoS ONE. 9(5). e97681–e97681. 51 indexed citations
20.
Cava, Claudia, Italo Zoppis, Manuela Gariboldi, et al.. (2014). Combined analysis of chromosomal instabilities and gene expression for colon cancer progression inference. PubMed. 4(1). 2–2. 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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