Oliver Stegle
Impact in
- Biophysics top 0.1%
- Cell Image Analysis Techniques
- Molecular Biology top 0.2%
- Single-cell and spatial transcriptomics
- Gene expression and cancer classification
- Epigenetics and DNA Methylation
- Bioinformatics and Genomic Networks
- Gene Regulatory Network Analysis
Papers in
-
- Single-cell and spatial transcriptomics 38
- Gene expression and cancer classification 23
- Bioinformatics and Genomic Networks 18
- Epigenetics and DNA Methylation 12
- Genetics 43
- Genetic Mapping and Diversity in Plants and Animals 23
- Genetic Associations and Epidemiology 15
- Genetic and phenotypic traits in livestock 10
- Co-authors
- John C. Marioni (11 shared papers)Sarah A. Teichmann (6 shared papers)Leopold Parts (7 shared papers)Christof Angermueller (5 shared papers)Wolf Reik (11 shared papers)Karsten Borgwardt (15 shared papers)Gavin Kelsey (5 shared papers)Tanel Pärnamaa (1 shared paper)
- Journals
- Genome biology (16 papers)Nature Communications (15 papers)Nature Methods (9 papers)PLoS Genetics (7 papers)Bioinformatics (6 papers)
- Partner nations
- United KingdomGermanyUnited States
In The Last Decade
Oliver Stegle
121 papers receiving 14.5k citations
Oliver Stegle's Hit Papers
Peers
Comparison fields: 5 of 214
- Biophysics 1.1k
- Molecular Biology 10.4k
- Cancer Research 2.0k
- Aging 181
- Genetics 2.7k
Countries citing papers authored by Oliver Stegle
This map shows the geographic impact of Oliver Stegle'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 Oliver Stegle with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Oliver Stegle more than expected).
Fields of papers citing papers by Oliver Stegle
This network shows the impact of papers produced by Oliver Stegle. 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 Oliver Stegle. The network helps show where Oliver Stegle may publish in the future.
Co-authors
The 25 scholars most cited alongside Oliver Stegle, 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 126 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Deep learning for computational biology Hit paper breakdown → | 2016 | 958 |
| 2 | Computational and analytical challenges in single-cell transcriptomics Hit paper breakdown → | 2015 | 816 |
| 3 | Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity Hit paper breakdown → | 2014 | 790 |
| 4 | Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells Hit paper breakdown → | 2015 | 775 |
| 5 | Whole-genome sequencing of multiple Arabidopsis thaliana populations Hit paper breakdown → | 2011 | 689 |
| 6 | Multi‐Omics Factor Analysis—a framework for unsupervised integration of multi‐omics data sets Hit paper breakdown → | 2018 | 664 |
| 7 | Spontaneous epigenetic variation in the Arabidopsis thaliana methylome Hit paper breakdown → | 2011 | 526 |
| 8 | Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity Hit paper breakdown → | 2016 | 510 |
| 9 | Cell2location maps fine-grained cell types in spatial transcriptomics Hit paper breakdown → | 2022 | 494 |
| 10 | Using probabilistic estimation of expression residuals (PEER) to obtain increased power and interpretability of gene expression analyses Hit paper breakdown → | 2012 | 486 |
| 11 | scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells Hit paper breakdown → | 2018 | 437 |
| 12 | MOFA+: a statistical framework for comprehensive integration of multi-modal single-cell data Hit paper breakdown → | 2020 | 432 |
| 13 | DNA methylation in Arabidopsis has a genetic basis and shows evidence of local adaptation Hit paper breakdown → | 2015 | 367 |
| 14 | SpatialDE: identification of spatially variable genes Hit paper breakdown → | 2018 | 349 |
| 15 | 2017 | 314 | |
| 16 | 2012 | 306 | |
| 17 | 2010 | 273 | |
| 18 | 2017 | 271 | |
| 19 | An introduction to Gaussian processes | 2010 | 266 |
| 20 | 2017 | 255 |
About Oliver Stegle
Oliver Stegle is a scholar working on Molecular Biology, Genetics, Cancer Research, Plant Science and Artificial Intelligence, having authored 126 papers that have together received 14.7k indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (38 papers), Genetic Mapping and Diversity in Plants and Animals (23 papers), Gene expression and cancer classification (23 papers), Bioinformatics and Genomic Networks (18 papers), Genetic Associations and Epidemiology (15 papers), Cancer Genomics and Diagnostics (14 papers), Epigenetics and DNA Methylation (12 papers) and Genetic and phenotypic traits in livestock (10 papers). The work is most often cited by research in Biophysics (1.1k citations), Molecular Biology (10.4k citations), Cancer Research (2.0k citations), Aging (181 citations) and Genetics (2.7k citations). Oliver Stegle has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include John C. Marioni, Sarah A. Teichmann, Leopold Parts, Christof Angermueller, Wolf Reik, Karsten Borgwardt, Gavin Kelsey, Tanel Pärnamaa, Ricard Argelaguet and Heather Lee. Their work appears in journals such as Genome biology, Nature Communications, Nature Methods, PLoS Genetics and 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.