Greg Finak
- Biophysics top 0.5%
- Cell Image Analysis Techniques 10
- Cancer Research top 2%
- Cancer Genomics and Diagnostics 3
- Immunology top 2%
- T-cell and B-cell Immunology 7
- Immune Cell Function and Interaction 5
- Molecular Biology top 2%
- Single-cell and spatial transcriptomics 20
- Gene expression and cancer classification 14
- Gene Regulatory Network Analysis 5
- Oncology top 2%
- Cancer Cells and Metastasis 3
- Co-authors
- Raphaël GottardoAndrew McDavidM. Juliana McElrathChloe K. SlichterHannah W. MillerMartin PrlicMorag ParkJingyuan Deng
- Cited by
- BiophysicsCancer ResearchImmunology
- Partner nations
- United StatesCanadaSouth Africa
In The Last Decade
Greg Finak
42 papers receiving 5.2k citations
Hit Papers
Peers
Comparison fields: 5 of 143
- Biophysics 424
- Cancer Research 1.1k
- Immunology 1.3k
- Molecular Biology 3.2k
- Oncology 1.2k
Countries citing papers authored by Greg Finak
This map shows the geographic impact of Greg Finak'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 Greg Finak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Greg Finak more than expected).
Fields of papers citing papers by Greg Finak
This network shows the impact of papers produced by Greg Finak. 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 Greg Finak. The network helps show where Greg Finak may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Greg Finak, 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 | 2024 | 2 | |
| 2 | 2023 | 3 | |
| 3 | 2021 | 21 | |
| 4 | 2020 | 6 | |
| 5 | 2019 | 40 | |
| 6 | 2017 | 17 | |
| 7 | Safety and immunogenicity of a mRNA rabies vaccine in healthy adults: an open-label, non-randomised, prospective, first-in-human phase 1 clinical trialbreakdown → | 2017 | 373 |
| 8 | 2016 | 6 | |
| 9 | 2016 | 108 | |
| 10 | MAST: a flexible statistical framework for assessing transcriptional changes and characterizing heterogeneity in single-cell RNA sequencing databreakdown → | 2015 | 1570 |
| 11 | 2014 | 41 | |
| 12 | 2014 | 135 | |
| 13 | 2013 | 389 | |
| 14 | 2013 | 33 | |
| 15 | 2010 | 65 | |
| 16 | 2010 | 19 | |
| 17 | 2009 | 160 | |
| 18 | Stromal gene expression predicts clinical outcome in breast cancerbreakdown → | 2008 | 1288 |
| 19 | 2006 | 110 | |
| 20 | 2004 | 7 |
About Greg Finak
Greg Finak is a scholar working on Biophysics, Virology and Immunology, having authored 42 papers that have together received 5.3k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (20 papers), Gene expression and cancer classification (14 papers), Cell Image Analysis Techniques (10 papers), T-cell and B-cell Immunology (7 papers), Gene Regulatory Network Analysis (5 papers), Immune Cell Function and Interaction (5 papers), Cancer Cells and Metastasis (3 papers) and Cancer Genomics and Diagnostics (3 papers). The work is most often cited by research in Biophysics (424 citations), Cancer Research (1.1k citations) and Immunology (1.3k citations). Greg Finak has collaborated with scholars based in United States, Canada and South Africa. Frequent co-authors include Raphaël Gottardo, Andrew McDavid, M. Juliana McElrath, Chloe K. Slichter, Hannah W. Miller, Martin Prlic, Morag Park, Jingyuan Deng, Masanao Yajima and Alex K. Shalek. Their work appears in journals such as Cytometry Part A, The Journal of Immunology, Nature Medicine, Bioinformatics and BMC Bioinformatics.
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.