Graham Su
Impact in
- Biophysics top 2%
- Cell Image Analysis Techniques
- Cancer Research top 10%
- Cancer Genomics and Diagnostics
Papers in
-
- Single-cell and spatial transcriptomics 10
- Gene expression and cancer classification 2
- Genomics and Chromatin Dynamics 2
- Epigenetics and DNA Methylation 1
- RNA Research and Splicing 1
-
- Immune cells in cancer 2
- Co-authors
- Rong Fan (10 shared papers)Yanxiang Deng (7 shared papers)Yang Liu (7 shared papers)Archibald Enninful (6 shared papers)Di Zhang (4 shared papers)Zhiliang Bai (7 shared papers)Stephanie Halene (3 shared papers)Yang Xiao (6 shared papers)
- Journals
- Cell (2 papers)Nature Methods (1 paper)Science (1 paper)Frontiers in Immunology (1 paper)Nature Communications (1 paper)
- Partner nations
- United StatesSwedenChina
In The Last Decade
Graham Su
9 papers receiving 1.2k citations
Graham Su's Hit Papers
Peers
Comparison fields: 5 of 90
- Biophysics 162
- Cancer Research 249
- Molecular Biology 1.1k
- Immunology 215
- Neurology 54
Countries citing papers authored by Graham Su
This map shows the geographic impact of Graham Su'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 Graham Su with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Graham Su more than expected).
Fields of papers citing papers by Graham Su
This network shows the impact of papers produced by Graham Su. 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 Graham Su. The network helps show where Graham Su may publish in the future.
Co-authors
The 25 scholars most cited alongside Graham Su, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue Hit paper breakdown → | 2020 | 540 |
| 2 | Spatial-CUT&Tag: Spatially resolved chromatin modification profiling at the cellular level Hit paper breakdown → | 2022 | 207 |
| 3 | Spatial profiling of chromatin accessibility in mouse and human tissues Hit paper breakdown → | 2022 | 199 |
| 4 | High-plex protein and whole transcriptome co-mapping at cellular resolution with spatial CITE-seq Hit paper breakdown → | 2023 | 184 |
| 5 | 2022 | 45 | |
| 6 | 2021 | 35 | |
| 7 | 2024 | 34 | |
| 8 | 2019 | 9 | |
| 9 | 2021 | 7 | |
| 10 | 2026 | 0 | |
| 11 | 2025 | 0 |
About Graham Su
Graham Su is a scholar working on Molecular Biology, Immunology, Cancer Research, Genetics and Oncology, having authored 11 papers that have together received 1.3k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (10 papers), Cancer Genomics and Diagnostics (2 papers), Gene expression and cancer classification (2 papers), Immune cells in cancer (2 papers), Genomics and Chromatin Dynamics (2 papers), Epigenetics and DNA Methylation (1 paper), RNA Research and Splicing (1 paper) and Cell Image Analysis Techniques (1 paper). The work is most often cited by research in Biophysics (162 citations), Cancer Research (249 citations), Molecular Biology (1.1k citations), Immunology (215 citations) and Neurology (54 citations). Graham Su has collaborated with scholars based in United States, Sweden and China. Frequent co-authors include Rong Fan, Yanxiang Deng, Yang Liu, Archibald Enninful, Di Zhang, Zhiliang Bai, Stephanie Halene, Yang Xiao, Mingyu Yang and Dongjoo Kim. Their work appears in journals such as Cell, Nature Methods, Science, Frontiers in Immunology 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.