Laura Riva

2.4k total citations
33 papers, 1.0k citations indexed

About

Laura Riva is a scholar working on Molecular Biology, Cancer Research and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Laura Riva has authored 33 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Molecular Biology, 14 papers in Cancer Research and 9 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Laura Riva's work include Cancer Genomics and Diagnostics (13 papers), Lung Cancer Treatments and Mutations (4 papers) and Epigenetics and DNA Methylation (4 papers). Laura Riva is often cited by papers focused on Cancer Genomics and Diagnostics (13 papers), Lung Cancer Treatments and Mutations (4 papers) and Epigenetics and DNA Methylation (4 papers). Laura Riva collaborates with scholars based in Italy, United Kingdom and United States. Laura Riva's co-authors include Ernest Fraenkel, Pier Giuseppe Pelicci, Vivek Iyer, David J. Adams, Ross C. Hardison, Yocheved L. Schindler, Stuart H. Orkin, Alan Cantor, Ming Yu and B Bernstein and has published in prestigious journals such as Nature Communications, Nature Genetics and SHILAP Revista de lepidopterología.

In The Last Decade

Laura Riva

30 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Laura Riva Italy 14 789 188 108 95 91 33 1.0k
Shichong Liu United States 13 1.1k 1.4× 125 0.7× 125 1.2× 107 1.1× 58 0.6× 17 1.3k
Amit Sharma Germany 19 674 0.9× 183 1.0× 148 1.4× 233 2.5× 40 0.4× 87 1.2k
Christine R. Klaus Germany 15 1.6k 2.1× 122 0.6× 94 0.9× 188 2.0× 252 2.8× 35 1.9k
Arwa S. Kathiria United States 13 901 1.1× 247 1.3× 111 1.0× 112 1.2× 46 0.5× 14 1.2k
Claudia Wing United States 11 342 0.4× 146 0.8× 110 1.0× 144 1.5× 56 0.6× 21 691
Enyuan Shang United States 17 921 1.2× 201 1.1× 190 1.8× 99 1.0× 112 1.2× 27 1.2k
John Anagli United States 21 603 0.8× 157 0.8× 108 1.0× 72 0.8× 56 0.6× 31 1.0k
Jongbum Kwon South Korea 22 1.2k 1.6× 168 0.9× 89 0.8× 259 2.7× 61 0.7× 35 1.7k
Matsuyuki Shirota Japan 16 586 0.7× 94 0.5× 172 1.6× 123 1.3× 21 0.2× 49 899

Countries citing papers authored by Laura Riva

Since Specialization
Citations

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

Fields of papers citing papers by Laura Riva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laura Riva

This figure shows the co-authorship network connecting the top 25 collaborators of Laura Riva. A scholar is included among the top collaborators of Laura Riva 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 Laura Riva. Laura Riva 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.
Xu, Miaofei, Jianying Li, Yun-Chung Hsiao, et al.. (2025). Environmental carcinogens often exacerbate endogenous mutagenic processes to enhance tumor promotion. Cell Reports. 44(7). 115978–115978.
2.
Novoa, Nuria, Laura Riva, Sara Ricciardi, et al.. (2025). Mediastinal staging of nonsmall cell lung cancer: what's new?. Breathe. 21(3). 230191–230191.
3.
Kandyba, Eve, Kyle Halliwill, Reyno Delrosario, et al.. (2025). Long-Term Latency of Highly Mutated Cells in Normal Mouse Skin Is Reversed by Exposure to Tumor Promoters and Chronic Tissue Damage. Cancer Discovery. 15(6). 1115–1128. 2 indexed citations
4.
Savino, Aurora, Pedro Beltrão, Isidro Cortés‐Ciriano, et al.. (2023). Highlights from the 1st European cancer dependency map symposium and workshop. FEBS Letters. 597(15). 1921–1927. 3 indexed citations
5.
6.
Riva, Laura, Arun R. Pandiri, Alastair Droop, et al.. (2020). The mutational signature profile of known and suspected human carcinogens in mice. Nature Genetics. 52(11). 1189–1197. 84 indexed citations
7.
Riva, Laura, Roberto Perra, Sonia Nemolato, et al.. (2020). Retrospective outcomes analysis of 99 consecutive uniportal awake lung biopsies: a real standard of care?. Journal of Thoracic Disease. 12(9). 4717–4730. 7 indexed citations
8.
Halliwill, Kyle, Cassandra Adams, Vivek Iyer, et al.. (2020). Mutational signatures in tumours induced by high and low energy radiation in Trp53 deficient mice. Nature Communications. 11(1). 394–394. 56 indexed citations
9.
Iyer, Vivek, Katharina Boroviak, Mark Thomas, et al.. (2018). No unexpected CRISPR-Cas9 off-target activity revealed by trio sequencing of gene-edited mice. PLoS Genetics. 14(7). e1007503–e1007503. 87 indexed citations
10.
Melloni, Giorgio, Stefano de Pretis, Laura Riva, et al.. (2016). LowMACA: exploiting protein family analysis for the identification of rare driver mutations in cancer. BMC Bioinformatics. 17(1). 80–80. 14 indexed citations
11.
Ronchini, Chiara, Laura Riva, Lucilla Luzi, et al.. (2016). PML-RARA-associated cooperating mutations belong to a transcriptional network that is deregulated in myeloid leukemias. Leukemia. 31(9). 1975–1986. 6 indexed citations
12.
Cremona, Marzia A., Laura M. Sangalli, Simone Vantini, et al.. (2015). Peak shape clustering reveals biological insights. BMC Bioinformatics. 16(1). 349–349. 14 indexed citations
13.
Melloni, Giorgio, Stefano de Pretis, Luca Mazzarella, et al.. (2014). DOTS-Finder: a comprehensive tool for assessing driver genes in cancer genomes. Genome Medicine. 6(6). 44–44. 21 indexed citations
14.
Mazzarella, Luca, Laura Riva, Lucilla Luzi, Chiara Ronchini, & Pier Giuseppe Pelicci. (2014). The Genomic and Epigenomic Landscapes of AML. Seminars in Hematology. 51(4). 259–272. 9 indexed citations
15.
Riva, Laura, Martina Koeva, Ferah Yildirim, et al.. (2012). Polyglutamine Expanded Huntingtin Dramatically Alters the Genome-Wide Binding of HSF1. Journal of Huntington s Disease. 1(1). 33–45.
16.
Yu, Ming, Laura Riva, Huafeng Xie, et al.. (2009). Insights into GATA-1-Mediated Gene Activation versus Repression via Genome-wide Chromatin Occupancy Analysis. Molecular Cell. 36(4). 682–695. 250 indexed citations
17.
Yeger‐Lotem, Esti, Laura Riva, Linhui Julie Su, et al.. (2009). Bridging high-throughput genetic and transcriptional data reveals cellular responses to alpha-synuclein toxicity. Nature Genetics. 41(3). 316–323. 218 indexed citations
18.
Pozzoli, Uberto, Laura Riva, Giorgia Menozzi, et al.. (2004). Over-representation of exonic splicing enhancers in human intronless genes suggests multiple functions in mRNA processing. Biochemical and Biophysical Research Communications. 322(2). 470–476. 12 indexed citations
19.
Pozzoli, Uberto, Greg Elgar, Rachele Cagliani, et al.. (2003). Comparative Analysis of Vertebrate Dystrophin Loci Indicate Intron Gigantism as a Common Feature. Genome Research. 13(5). 764–772. 18 indexed citations
20.
Carruba, Michele O., Massimo Cuzzolaro, Laura Riva, et al.. (2001). Efficacy and tolerability of moclobemide in bulimia nervosa: a placebo-controlled trial. International Clinical Psychopharmacology. 16(1). 27–32. 18 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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