Leland McInnes

25.0k citations
9 papers · 9.0k indexed · 4 hit papers · h-index 7
Topics
Data-Driven Disease Surveillance (1 paper)Advanced Graph Neural Networks (1 paper)Advanced Neuroimaging Techniques and Applications (1 paper)

In The Last Decade

Leland McInnes

8 papers receiving 8.8k citations

Hit Papers

UMAP: Uniform Manifold Approximation and Projection2017202620202023201820182017202410002.0k3.0k4.0k

Peers

Leland McInnes
Comparison fields: 5 of 221
  • Molecular Biology 3.8k
  • Artificial Intelligence 1.4k
  • Immunology 1.1k
  • Cancer Research 730
  • Computer Vision and Pattern Recognition 726
Replace John Healy with:
John Healy United States
Nathaniel Saul United States
Lukas Großberger Germany
Brendan J. Frey Canada
Ron Milo Israel
Laurens van der Maaten Netherlands
Pierre Geurts Belgium
Wing Hung Wong United States
David Warde-Farley Canada
Joachim M. Buhmann Switzerland
Leland McInnes relative to John Healy United States John Healy's profile →
Citations per field
00.5×1.5×
John Healy · 1×
Citations per year

Countries citing papers authored by Leland McInnes

Since Specialization
Citations

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

Fields of papers citing papers by Leland McInnes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Leland McInnes

This figure shows the co-authorship network connecting the top 25 collaborators of Leland McInnes. A scholar is included among the top collaborators of Leland McInnes 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 Leland McInnes. Leland McInnes is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
#WorkIndexed citations
1 0
2
Uniform manifold approximation and projectionbreakdown →
70
3
Parametric UMAP: learning embeddings with deep neural networks for representation and semi-supervised learning
14
4 1
5 8
6 45
7
Dimensionality reduction for visualizing single-cell data using UMAPbreakdown →
2943
8
UMAP: Uniform Manifold Approximation and Projectionbreakdown →
4554
9
hdbscan: Hierarchical density based clusteringbreakdown →
1359

About Leland McInnes

Leland McInnes is a scholar working on Structural Biology, Computer Graphics and Computer-Aided Design and Biophysics, having authored 9 papers that have together received 9.0k indexed citations. Recurring topics across this work include Data-Driven Disease Surveillance (1 paper), Advanced Graph Neural Networks (1 paper) and Advanced Neuroimaging Techniques and Applications (1 paper). The work is most often cited by research in Biophysics (708 citations), Molecular Biology (3.8k citations) and Immunology (1.1k citations). Leland McInnes has collaborated with scholars based in United States, Singapore and Colombia. Frequent co-authors include John Healy, Nathaniel Saul, Lukas Großberger, Lai Guan Ng, Evan W. Newell, Étienne Becht, Immanuel Kwok, Charles‐Antoine Dutertre, Florent Ginhoux and Mark P. Oxley. Their work appears in journals such as Nature Biotechnology, Scientific Reports and Solar Physics.

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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