Trevor Manz

1.1k total citations
10 papers, 251 citations indexed

About

Trevor Manz is a scholar working on Computer Vision and Pattern Recognition, Molecular Biology and Artificial Intelligence. According to data from OpenAlex, Trevor Manz has authored 10 papers receiving a total of 251 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Computer Vision and Pattern Recognition, 4 papers in Molecular Biology and 3 papers in Artificial Intelligence. Recurrent topics in Trevor Manz's work include Data Visualization and Analytics (3 papers), Video Analysis and Summarization (3 papers) and Single-cell and spatial transcriptomics (2 papers). Trevor Manz is often cited by papers focused on Data Visualization and Analytics (3 papers), Video Analysis and Summarization (3 papers) and Single-cell and spatial transcriptomics (2 papers). Trevor Manz collaborates with scholars based in United States, Germany and United Kingdom. Trevor Manz's co-authors include Tiffany Chen, Ming Y. Lu, Richard J. Chen, Faisal Mahmood, Maha Shady, Wei‐Hung Weng, Drew F. K. Williamson, Nils Gehlenborg, Christian Tischer and Erin E. Diel and has published in prestigious journals such as Bioinformatics, Nature Methods and IEEE Transactions on Visualization and Computer Graphics.

In The Last Decade

Trevor Manz

9 papers receiving 249 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Trevor Manz United States	4	140	92	73	62	62	10	251
Jesper Molin Sweden	8	242 1.7×	123 1.3×	27 0.4×	68 1.1×	63 1.0×	18	318
Ivy Liang United States	2	228 1.6×	161 1.8×	52 0.7×	72 1.2×	33 0.5×	3	385
Leslie Solorzano Sweden	7	137 1.0×	122 1.3×	111 1.5×	58 0.9×	114 1.8×	12	343
Pattanasak Mongkolwat United States	9	110 0.8×	136 1.5×	92 1.3×	63 1.0×	11 0.2×	34	313
Kai Saeger Germany	5	171 1.2×	49 0.5×	37 0.5×	127 2.0×	105 1.7×	9	278
Jake Cobb United States	7	99 0.7×	56 0.6×	40 0.5×	34 0.5×	20 0.3×	9	279
Håkan Wieslander Sweden	6	74 0.5×	39 0.4×	65 0.9×	41 0.7×	98 1.6×	9	247
Liang-Bo Wang United States	5	231 1.6×	175 1.9×	76 1.0×	116 1.9×	32 0.5×	9	368
Shazia Akbar United Kingdom	8	150 1.1×	116 1.3×	39 0.5×	104 1.7×	50 0.8×	20	269
Igor Odintsov United States	5	143 1.0×	98 1.1×	40 0.5×	52 0.8×	24 0.4×	15	260

Countries citing papers authored by Trevor Manz

Since Specialization

Citations

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

Fields of papers citing papers by Trevor Manz

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Trevor Manz

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

All Works

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10 of 10 papers shown

Manz, Trevor, et al.. (2025). Design Space and Declarative Grammar for 3D Genomic Data Visualization. IEEE Transactions on Visualization and Computer Graphics. 32(1). 890–900.

Martens, Laura D., Alexander Karollus, Trevor Manz, et al.. (2025). scooby: modeling multimodal genomic profiles from DNA sequence at single-cell resolution. Nature Methods. 22(11). 2275–2285. 1 indexed citations

Lekschas, Fritz & Trevor Manz. (2024). Jupyter Scatter: Interactive Exploration of Large-ScaleDatasets. The Journal of Open Source Software. 9(101). 7059–7059. 3 indexed citations

Manz, Trevor, Nils Gehlenborg, & Nezar Abdennur. (2024). Any notebook served: authoring and sharing reusable interactive widgets. Proceedings of the Python in Science Conferences. 247–255. 1 indexed citations

Manz, Trevor, et al.. (2024). A General Framework for Comparing Embedding Visualizations Across Class-Label Hierarchies. IEEE Transactions on Visualization and Computer Graphics. 31(1). 283–293. 2 indexed citations

Keller, Mark S., Ilan Gold, Chuck McCallum, et al.. (2024). Vitessce: integrative visualization of multimodal and spatially resolved single-cell data. Nature Methods. 22(1). 63–67. 15 indexed citations

Manz, Trevor, Nezar Abdennur, & Nils Gehlenborg. (2024). anywidget: reusable widgets for interactive analysis and visualization in computational notebooks. The Journal of Open Source Software. 9(102). 6939–6939. 1 indexed citations

Manz, Trevor, Sehi L’Yi, & Nils Gehlenborg. (2023). Gos: a declarative library for interactive genomics visualization in Python. Bioinformatics. 39(1). 10 indexed citations

Moore, Josh, Chris Allan, Sébastien Besson, et al.. (2021). OME-NGFF: a next-generation file format for expanding bioimaging data-access strategies. Nature Methods. 18(12). 1496–1498. 66 indexed citations

10.

Chen, Richard J., Ming Y. Lu, Wei‐Hung Weng, et al.. (2021). Multimodal Co-Attention Transformer for Survival Prediction in Gigapixel Whole Slide Images. 2021 IEEE/CVF International Conference on Computer Vision (ICCV). 3995–4005. 152 indexed citations

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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