Guy Wolf
Impact in
- Molecular Biology top 5%
- Single-cell and spatial transcriptomics
- Gene Regulatory Network Analysis
- Bioinformatics and Genomic Networks
- Health Informatics top 5%
Papers in
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- Topological and Geometric Data Analysis 29
-
- Neural Networks and Applications 11
- Advanced Graph Neural Networks 10
- Domain Adaptation and Few-Shot Learning 5
- Stochastic Gradient Optimization Techniques 4
- Co-authors
- Smita Krishnaswamy (32 shared papers)David van Dijk (12 shared papers)Kevin R. Moon (15 shared papers)Kristina Yim (3 shared papers)Roshan Sharma (1 shared paper)Christine Louise Chaffer (1 shared paper)Dana Pe’er (1 shared paper)Ambrose Carr (1 shared paper)
- Journals
- Applied and Computational Harmonic Analysis (8 papers)Nature Biotechnology (3 papers)IEEE Transactions on Signal Processing (2 papers)Nature Methods (2 papers)Nature Communications (2 papers)
- Partner nations
- CanadaUnited StatesIsrael
In The Last Decade
Guy Wolf
78 papers receiving 3.2k citations
Guy Wolf's Hit Papers
Peers
Comparison fields: 5 of 152
- Molecular Biology 1.7k
- Health Informatics 41
- Computational Theory and Mathematics 196
- Artificial Intelligence 344
- Oncology 197
Countries citing papers authored by Guy Wolf
This map shows the geographic impact of Guy Wolf'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 Guy Wolf with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Guy Wolf more than expected).
Fields of papers citing papers by Guy Wolf
This network shows the impact of papers produced by Guy Wolf. 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 Guy Wolf. The network helps show where Guy Wolf may publish in the future.
Co-authors
The 25 scholars most cited alongside Guy Wolf, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 82 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Recovering Gene Interactions from Single-Cell Data Using Data Diffusion Hit paper breakdown → | 2018 | 1247 |
| 2 | Visualizing structure and transitions in high-dimensional biological data Hit paper breakdown → | 2019 | 659 |
| 3 | 2019 | 222 | |
| 4 | Recipe for a General, Powerful, Scalable Graph Transformer Hit paper breakdown → | 2022 | 200 |
| 5 | 2021 | 123 | |
| 6 | 2017 | 90 | |
| 7 | 2021 | 63 | |
| 8 | 2022 | 50 | |
| 9 | 2020 | 48 | |
| 10 | 2023 | 46 | |
| 11 | 2020 | 32 | |
| 12 | 2020 | 29 | |
| 13 | 2023 | 26 | |
| 14 | 2023 | 25 | |
| 15 | 2020 | 24 | |
| 16 | Manifold Interpolating Optimal-Transport Flows for Trajectory Inference. | 2022 | 19 |
| 17 | 2024 | 18 | |
| 18 | 2019 | 14 | |
| 19 | 2015 | 13 | |
| 20 | 2020 | 13 |
About Guy Wolf
Guy Wolf is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Computer Vision and Pattern Recognition, Applied Mathematics and Molecular Biology, having authored 82 papers that have together received 3.2k indexed citations. Recurring topics across this work include Topological and Geometric Data Analysis (29 papers), Face and Expression Recognition (18 papers), Single-cell and spatial transcriptomics (15 papers), Neural Networks and Applications (11 papers), Advanced Graph Neural Networks (10 papers), Domain Adaptation and Few-Shot Learning (5 papers), Geometric Analysis and Curvature Flows (5 papers) and Stochastic Gradient Optimization Techniques (4 papers). The work is most often cited by research in Molecular Biology (1.7k citations), Health Informatics (41 citations), Computational Theory and Mathematics (196 citations), Artificial Intelligence (344 citations) and Oncology (197 citations). Guy Wolf has collaborated with scholars based in Canada, United States and Israel. Frequent co-authors include Smita Krishnaswamy, David van Dijk, Kevin R. Moon, Kristina Yim, Roshan Sharma, Christine Louise Chaffer, Dana Pe’er, Ambrose Carr, Pooja Kathail and Diwakar Ram Pattabiraman. Their work appears in journals such as Applied and Computational Harmonic Analysis, Nature Biotechnology, IEEE Transactions on Signal Processing, Nature Methods and Nature Communications.
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.