Fuhui Long

16.8k total citations · 2 hit papers
31 papers, 9.5k citations indexed

About

Fuhui Long is a scholar working on Biophysics, Molecular Biology and Aging. According to data from OpenAlex, Fuhui Long has authored 31 papers receiving a total of 9.5k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Biophysics, 12 papers in Molecular Biology and 8 papers in Aging. Recurrent topics in Fuhui Long's work include Cell Image Analysis Techniques (20 papers), Genetics, Aging, and Longevity in Model Organisms (8 papers) and Single-cell and spatial transcriptomics (6 papers). Fuhui Long is often cited by papers focused on Cell Image Analysis Techniques (20 papers), Genetics, Aging, and Longevity in Model Organisms (8 papers) and Single-cell and spatial transcriptomics (6 papers). Fuhui Long collaborates with scholars based in United States, China and Germany. Fuhui Long's co-authors include Chen Ding, Eugene W. Myers, J. Simpson, Zongcai Ruan, Gene Myers, Alessandro Bria, Giulio Iannello, Stuart K. Kim, Eugene Myers and Zhi Zhou and has published in prestigious journals such as Cell, Nature Communications and Nature Biotechnology.

In The Last Decade

Fuhui Long

31 papers receiving 9.2k citations

Hit Papers

Feature selection based on mutual information criteria of... 2005 2026 2012 2019 2005 2010 2.5k 5.0k 7.5k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fuhui Long United States 20 3.0k 2.4k 2.4k 1.3k 789 31 9.5k
Joachim M. Buhmann Switzerland 54 3.5k 1.2× 4.6k 1.9× 2.1k 0.9× 698 0.5× 1.7k 2.2× 235 12.5k
Shuiwang Ji United States 43 3.5k 1.2× 3.1k 1.3× 996 0.4× 413 0.3× 414 0.5× 134 7.4k
David Warde-Farley Canada 12 4.0k 1.3× 5.5k 2.3× 3.5k 1.5× 301 0.2× 444 0.6× 17 16.4k
Pedro Larrañaga Spain 48 5.5k 1.9× 1.6k 0.7× 3.2k 1.3× 284 0.2× 533 0.7× 231 11.9k
Wojciech Samek Germany 35 5.6k 1.9× 1.9k 0.8× 683 0.3× 389 0.3× 1.6k 2.0× 136 11.7k
Lars Kai Hansen Denmark 46 3.7k 1.2× 1.7k 0.7× 1.0k 0.4× 500 0.4× 2.9k 3.7× 332 11.8k
Gunnar Rätsch Germany 52 4.9k 1.6× 4.6k 1.9× 5.1k 2.1× 158 0.1× 554 0.7× 167 16.1k
Chen Ding China 20 3.4k 1.1× 2.4k 1.0× 1.7k 0.7× 102 0.1× 658 0.8× 125 9.0k
Loris Nanni Italy 45 1.7k 0.6× 3.0k 1.3× 1.7k 0.7× 250 0.2× 137 0.2× 260 7.3k
P. M. Durai Raj Vincent India 28 4.0k 1.3× 2.7k 1.1× 677 0.3× 169 0.1× 437 0.6× 92 10.0k

Countries citing papers authored by Fuhui Long

Since Specialization
Citations

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

Fields of papers citing papers by Fuhui Long

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fuhui Long

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

All Works

20 of 20 papers shown
1.
Waters, Jack, Eric Lee, Nathalie Gaudreault, et al.. (2019). Biological variation in the sizes, shapes and locations of visual cortical areas in the mouse. PLoS ONE. 14(5). e0213924–e0213924. 13 indexed citations
2.
Zhou, Zhi, et al.. (2018). DeepNeuron: an open deep learning toolbox for neuron tracing. Brain Informatics. 5(2). 3–3. 43 indexed citations
3.
Wan, Yinan, Fuhui Long, Lei Qu, et al.. (2015). BlastNeuron for Automated Comparison, Retrieval and Clustering of 3D Neuron Morphologies. Neuroinformatics. 13(4). 487–499. 45 indexed citations
4.
Puchalski, Ralph B., Nameeta Shah, Jeremy A. Miller, et al.. (2015). GENO-32AN ANATOMIC TRANSCRIPTIONAL ATLAS OF GLIOBLASTOMA. Neuro-Oncology. 17(suppl 5). v99.1–v99. 1 indexed citations
5.
Bria, Alessandro, et al.. (2014). Extensible visualization and analysis for multidimensional images using Vaa3D. Nature Protocols. 9(1). 193–208. 212 indexed citations
6.
Heckscher, Ellie S., Fuhui Long, Michael J. Layden, et al.. (2014). Atlas-builder software and the eNeuro atlas: resources for developmental biology and neuroscience. Development. 141(12). 2524–2532. 25 indexed citations
7.
Yu, Hung–Hsiang, Takeshi Awasaki, Mark Schroeder, et al.. (2013). Clonal Development and Organization of the Adult Drosophila Central Brain. Current Biology. 23(8). 633–643. 115 indexed citations
8.
Liu, Xiao, Samuel S. Gross, Andy Nguyễn, et al.. (2013). Automated cellular annotation for high-resolution images of adult Caenorhabditis elegans. Bioinformatics. 29(13). i18–i26. 5 indexed citations
9.
Zhao, Ting, Jun Xie, Fernando Amat, et al.. (2011). Automated Reconstruction of Neuronal Morphology Based on Local Geometrical and Global Structural Models. Neuroinformatics. 9(2-3). 247–261. 89 indexed citations
10.
Chung, Phuong, Fuhui Long, Lei Qu, et al.. (2011). BrainAligner: 3D registration atlases of Drosophila brains. Nature Methods. 8(6). 493–498. 105 indexed citations
11.
Qu, Lei, et al.. (2011). Simultaneous recognition and segmentation of cells: application in C.elegans. Bioinformatics. 27(20). 2895–2902. 24 indexed citations
12.
Long, Fuhui, et al.. (2011). Automatic 3D neuron tracing using all-path pruning. Bioinformatics. 27(13). i239–i247. 114 indexed citations
13.
Ruan, Zongcai, et al.. (2010). V3D enables real-time 3D visualization and quantitative analysis of large-scale biological image data sets. Nature Biotechnology. 28(4). 348–353. 507 indexed citations breakdown →
14.
Liu, Xiao, Fuhui Long, Min Jiang, et al.. (2009). Analysis of Cell Fate from Single-Cell Gene Expression Profiles in C. elegans. Cell. 139(3). 623–633. 109 indexed citations
15.
Long, Fuhui, et al.. (2009). A 3D digital atlas of C. elegans and its application to single-cell analyses. Nature Methods. 6(9). 667–672. 140 indexed citations
16.
Long, Fuhui, et al.. (2007). Automatic image analysis for gene expression patterns of fly embryos. BMC Cell Biology. 8(S1). S7–S7. 55 indexed citations
17.
Long, Fuhui, et al.. (2007). Phenotype clustering of breast epithelial cells in confocal images based on nuclear protein distribution analysis. BMC Cell Biology. 8(S1). S3–S3. 11 indexed citations
18.
Long, Fuhui, et al.. (2007). AUTOMATIC SEGMENTATION OF NUCLEI IN 3D MICROSCOPY IMAGES OF C.ELEGANS. 12. 536–539. 22 indexed citations
19.
Forman, George, Huan Liu, Edward R. Dougherty, et al.. (2005). Feature selection: We've barely scratched the surface. IEEE Intelligent Systems. 20(6). 74–76. 14 indexed citations
20.
Long, Fuhui, et al.. (2005). Feature selection based on mutual information criteria of max-dependency, max-relevance, and min-redundancy. IEEE Transactions on Pattern Analysis and Machine Intelligence. 27(8). 1226–1238. 7517 indexed citations breakdown →

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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