Veronica Biga

493 citations
17 papers · 305 · h-index 8

Impact in

Papers in

    • Pluripotent Stem Cells Research 6
    • Single-cell and spatial transcriptomics 4
    • Gene Regulatory Network Analysis 3
    • Developmental Biology and Gene Regulation 3
    • Cell Image Analysis Techniques 4

Veronica Biga

14 papers receiving 301 citations

Peers

Veronica Biga
Comparison fields: 5 of 60
  • Developmental Neuroscience 22
  • Biophysics 24
  • Molecular Biology 218
  • Cell Biology 41
  • Aging 4
Replace Michael Strasser with:
Michael Strasser Germany
Peter Berube United States
Arnaud Gelas United States
Edgar Cardenas De La Hoz Belgium
Mark R. Verardo United States
Luan Jiang China
Cindy M. Nguyen United States
Xiaoguang Li China
Linjing Fang United States
Cara R. Schiavon United States
Veronica Biga relative to Michael Strasser Germany Michael Strasser's profile →
Citations per field
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Citations per year

Countries citing papers authored by Veronica Biga

Since Specialization
Citations

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

Fields of papers citing papers by Veronica Biga

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Veronica Biga, 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 Veronica Biga Line = papers co-authored together Veronica Biga links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 201467
2 201947
3 200847
4 201635
5 202025
6 201823
7 202122
8 202120
9 20227
10 20155
11 20242
12 20252
13 20252
14 20251
15 20260
16 20170
17 20170

About Veronica Biga

Veronica Biga is a scholar working on Molecular Biology, Biophysics, Cell Biology, Computer Vision and Pattern Recognition and Statistical and Nonlinear Physics, having authored 17 papers that have together received 305 indexed citations. Recurring topics across this work include Pluripotent Stem Cells Research (6 papers), Cell Image Analysis Techniques (4 papers), Single-cell and spatial transcriptomics (4 papers), Gene Regulatory Network Analysis (3 papers), Developmental Biology and Gene Regulation (3 papers), Image Processing Techniques and Applications (2 papers), Medical Image Segmentation Techniques (2 papers) and Microtubule and mitosis dynamics (2 papers). The work is most often cited by research in Developmental Neuroscience (22 citations), Biophysics (24 citations), Molecular Biology (218 citations), Cell Biology (41 citations) and Aging (4 citations). Veronica Biga has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include Daniel Coca, Nancy Papalopulu, Tudor Barbu, Viorel Barbu, Cerys Manning, Peter W. Andrews, Ivana Barbaric, Mark Jones, Dylan Stavish and Jochen Kursawe. Their work appears in journals such as Development, Stem Cell Reports, Molecular Systems Biology, Biology Open and The EMBO Journal.

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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