Simone G. Riva

622 citations
18 papers · 271 · h-index 6

Impact in

Papers in

    • Single-cell and spatial transcriptomics 10
    • Gene expression and cancer classification 5
    • Gene Regulatory Network Analysis 4
    • Genomics and Chromatin Dynamics 3
    • Protein Degradation and Inhibitors 1
    • Reservoir Engineering and Simulation Methods 2
    • Drilling and Well Engineering 1

Simone G. Riva

13 papers receiving 264 citations

Peers

Simone G. Riva
Comparison fields: 5 of 50
  • Hematology 35
  • Biophysics 18
  • Immunology 58
  • Molecular Biology 182
  • Cancer Research 37
Replace Avinash Waghray with:
Avinash Waghray United States
Tobias Krammer Germany
Jurrian K. de Kanter Netherlands
Jack Bibby United States
Cecilia Domínguez Conde Austria
Priya Choudhry United States
Maria Herberg Germany
Nouraiz Ahmed Switzerland
Ankita Gupte Australia
Susana Temiño Spain
Simone G. Riva relative to Avinash Waghray United States Avinash Waghray's profile →
Citations per field
00.5×1.5×2.5×
Avinash Waghray · 1×
Citations per year

Countries citing papers authored by Simone G. Riva

Since Specialization
Citations

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

Fields of papers citing papers by Simone G. Riva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Simone G. Riva, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Simone G. Riva Line = papers co-authored together Simone G. Riva links everyone, so they are left out of the graph.

All Works

18 of 18 papers shown
#Work
1 2020203
2 202217
3 20258
4 20208
5 20238
6 20227
7 20084
8 20214
9 20214
10 20233
11 20232
12 20222
13 20221
14 20230
15 20260
16 20210
17 20250
18 20220

About Simone G. Riva

Simone G. Riva is a scholar working on Molecular Biology, Ocean Engineering, Cancer Research, Computational Theory and Mathematics and Plant Science, having authored 18 papers that have together received 271 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (10 papers), Gene expression and cancer classification (5 papers), Gene Regulatory Network Analysis (4 papers), Genomics and Chromatin Dynamics (3 papers), Cancer Genomics and Diagnostics (2 papers), Reservoir Engineering and Simulation Methods (2 papers), Drilling and Well Engineering (1 paper) and Protein Degradation and Inhibitors (1 paper). The work is most often cited by research in Hematology (35 citations), Biophysics (18 citations), Immunology (58 citations), Molecular Biology (182 citations) and Cancer Research (37 citations). Simone G. Riva has collaborated with scholars based in United Kingdom, Italy and Netherlands. Frequent co-authors include Ana Cvejic, Andrea Tangherloni, Brynelle Myers, Elisa Panada, Anna Maria Ranzoni, Irina Mohorianu, Paulina M. Strzelecka, Ivan Berest, Judith B. Zaugg and Paolo Cazzaniga. Their work appears in journals such as Cell stem cell, BMC Bioinformatics, Journal of Biomedical Informatics, Symmetry and Journal of Visualized Experiments.

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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