John Healy

18.3k citations
6 papers · 9.5k · 4 hit papers · h-index 5

Impact in

  • Biophysics top 0.2%
    • Cell Image Analysis Techniques
    • Single-cell and spatial transcriptomics
    • Gene expression and cancer classification

Papers in

John Healy

6 papers receiving 9.4k citations

John Healy's Hit Papers

Uniform manifold approximation and projection 2024 · 102 citations
1020+3+6Years since publication10002.0k3.0k4.0k

Peers

John Healy
Comparison fields: 5 of 220
  • Biophysics 670
  • Molecular Biology 3.7k
  • Immunology 1.0k
  • Cancer Research 632
  • Structural Biology 62
Replace Leland McInnes with:
Leland McInnes United States
Nathaniel Saul United States
Lukas Großberger Netherlands
Brendan J. Frey Canada
Laurens van der Maaten Netherlands
Ron Milo Israel
Pierre Geurts Belgium
David Warde-Farley Canada
Joachim M. Buhmann Switzerland
Wing Hung Wong United States
John Healy relative to Leland McInnes United States Leland McInnes's profile →
Citations per field
00.5×1.5×
Leland McInnes · 1×
Citations per year

Countries citing papers authored by John Healy

Since Specialization
Citations

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

Fields of papers citing papers by John Healy

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside John Healy, 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 John Healy Line = papers co-authored together John Healy links everyone, so they are left out of the graph.

All Works

6 of 6 papers shown
#Work
1
UMAP: Uniform Manifold Approximation and Projection
Hit paper breakdown →
20184838
2
Dimensionality reduction for visualizing single-cell data using UMAP
Hit paper breakdown →
20183083
3
hdbscan: Hierarchical density based clustering
Hit paper breakdown →
20171466
4
Uniform manifold approximation and projection
Hit paper breakdown →
2024102
5 201846
6 20201

About John Healy

John Healy is a scholar working on Molecular Biology, Structural Biology, Computer Vision and Pattern Recognition, Atomic and Molecular Physics, and Optics and Computational Mechanics, having authored 6 papers that have together received 9.5k indexed citations. Recurring topics across this work include Anomaly Detection Techniques and Applications (1 paper), Advanced Clustering Algorithms Research (1 paper), Gene expression and cancer classification (1 paper), Data-Driven Disease Surveillance (1 paper), Advanced Electron Microscopy Techniques and Applications (1 paper), Advanced Vision and Imaging (1 paper), Surface and Thin Film Phenomena (1 paper) and Computer Graphics and Visualization Techniques (1 paper). The work is most often cited by research in Biophysics (670 citations), Molecular Biology (3.7k citations), Immunology (1.0k citations), Cancer Research (632 citations) and Structural Biology (62 citations). John Healy has collaborated with scholars based in United States, Netherlands and Singapore. Frequent co-authors include Leland McInnes, Lukas Großberger, Nathaniel Saul, Immanuel Kwok, Charles‐Antoine Dutertre, Florent Ginhoux, Evan W. Newell, Étienne Becht, Lai Guan Ng and Ondrej Dyck. Their work appears in journals such as npj Computational Materials, Nature Biotechnology, Nature Reviews Methods Primers and The Journal of Open Source Software.

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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