Julia Olivieri

1.9k citations
6 papers · 355 · h-index 6

Impact in

Papers in

    • Single-cell and spatial transcriptomics 2
    • RNA Research and Splicing 2
    • Molecular Biology Techniques and Applications 2
    • Genomics and Phylogenetic Studies 2
    • Genetic diversity and population structure 2
    • Genetic Associations and Epidemiology 1
    • Genomics and Rare Diseases 1

Julia Olivieri

6 papers receiving 353 citations

Peers

Julia Olivieri
Comparison fields: 5 of 72
  • Cellular and Molecular Neuroscience 86
  • Ecology, Evolution, Behavior and Systematics 76
  • Molecular Biology 269
  • Genetics 62
  • Plant Science 64
Replace Kahn Rhrissorrakrai with:
Kahn Rhrissorrakrai United States
Matthias Ziehm Germany
Silvie Fexová United Kingdom
Laurence Röder France
Mark Woodbridge United Kingdom
Cihan Erkut Germany
Axel Schmidt Germany
Yonathan Sonntag Sweden
Laura Lee United States
Colleen Davis United States
Julia Olivieri relative to Kahn Rhrissorrakrai United States Kahn Rhrissorrakrai's profile →
Citations per field
00.5×3.8×
Kahn Rhrissorrakrai · 1×
Citations per year

Countries citing papers authored by Julia Olivieri

Since Specialization
Citations

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

Fields of papers citing papers by Julia Olivieri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

6 of 6 papers shown
#Work
1 2018146
2 201772
3 201856
4 201844
5 202130
6 20217

About Julia Olivieri

Julia Olivieri is a scholar working on Molecular Biology, Genetics, Cellular and Molecular Neuroscience, Ecology, Evolution, Behavior and Systematics and Computational Theory and Mathematics, having authored 6 papers that have together received 355 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (2 papers), RNA Research and Splicing (2 papers), Molecular Biology Techniques and Applications (2 papers), Genomics and Phylogenetic Studies (2 papers), Genetic diversity and population structure (2 papers), Cancer Genomics and Diagnostics (1 paper), Genetic Associations and Epidemiology (1 paper) and Genomics and Rare Diseases (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (86 citations), Ecology, Evolution, Behavior and Systematics (76 citations), Molecular Biology (269 citations), Genetics (62 citations) and Plant Science (64 citations). Julia Olivieri has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include H. Eric Xu, Naomi R. Latorraca, Raphael J.L. Townshend, Jason K. Wang, Scott A. Hollingsworth, M. Sommer, Ron O. Dror, Michael J. Moore, Ya Yang and Joseph F. Walker. Their work appears in journals such as Genome biology, eLife, Nature, New Phytologist and Molecular Biology and Evolution.

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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