Ian Sudbery
Impact in
- Cancer Research top 2%
- Cancer Genomics and Diagnostics
- Molecular Biology top 2%
- RNA modifications and cancer
- RNA Research and Splicing
- Epigenetics and DNA Methylation
- Single-cell and spatial transcriptomics
- Genomics and Phylogenetic Studies
- RNA and protein synthesis mechanisms
- Genomics and Chromatin Dynamics
Papers in
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- MicroRNA in disease regulation 4
-
- RNA modifications and cancer 6
- RNA Research and Splicing 6
- Genomics and Phylogenetic Studies 5
- Single-cell and spatial transcriptomics 3
- Epigenetics and DNA Methylation 3
- Protein Degradation and Inhibitors 3
- Co-authors
- Andreas HegerTom SmithDavid SimsChris P. PontingNicholas E. IlottAndrew J. PhillipsMark RamsdaleStuart A. Wilson
- Journals
- Scientific Reports (2 papers)Nature Communications (2 papers)Cell Reports (2 papers)Genome biology (2 papers)Blood (1 paper)
- Partner nations
- United KingdomUnited StatesSingapore
In The Last Decade
Ian Sudbery
30 papers receiving 3.7k citations
Hit Papers
Peers
Comparison fields: 5 of 143
- Cancer Research 677
- Molecular Biology 2.7k
- Genetics 535
- Infectious Diseases 289
- Immunology 291
Countries citing papers authored by Ian Sudbery
This map shows the geographic impact of Ian Sudbery'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 Ian Sudbery with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ian Sudbery more than expected).
Fields of papers citing papers by Ian Sudbery
This network shows the impact of papers produced by Ian Sudbery. 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 Ian Sudbery. The network helps show where Ian Sudbery may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ian Sudbery, 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 | 2024 | 7 | |
| 3 | 2024 | 19 | |
| 4 | 2024 | 30 | |
| 5 | 2023 | 3 | |
| 6 | 2022 | 21 | |
| 7 | 2021 | 26 | |
| 8 | 2020 | 22 | |
| 9 | 2019 | 12 | |
| 10 | 2019 | 140 | |
| 11 | 2019 | 90 | |
| 12 | 2018 | 49 | |
| 13 | 2018 | 104 | |
| 14 | UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy Hit paper breakdown → | 2017 | 1166 |
| 15 | Sequencing depth and coverage: key considerations in genomic analyses Hit paper breakdown → | 2014 | 903 |
| 16 | 2013 | 114 | |
| 17 | 2010 | 37 | |
| 18 | 2010 | 48 | |
| 19 | 2009 | 27 | |
| 20 | 2003 | 348 |
About Ian Sudbery
Ian Sudbery is a scholar working on Cancer Research, Molecular Biology, Hematology, Information Systems and Management and Cell Biology, having authored 31 papers that have together received 3.7k indexed citations. Recurring topics across this work include RNA modifications and cancer (6 papers), RNA Research and Splicing (6 papers), Genomics and Phylogenetic Studies (5 papers), MicroRNA in disease regulation (4 papers), Single-cell and spatial transcriptomics (3 papers), Multiple Myeloma Research and Treatments (3 papers), Epigenetics and DNA Methylation (3 papers) and Protein Degradation and Inhibitors (3 papers). The work is most often cited by research in Cancer Research (677 citations), Molecular Biology (2.7k citations), Genetics (535 citations), Infectious Diseases (289 citations) and Immunology (291 citations). Ian Sudbery has collaborated with scholars based in United Kingdom, United States and Singapore. Frequent co-authors include Andreas Heger, Tom Smith, David Sims, Chris P. Ponting, Nicholas E. Ilott, Andrew J. Phillips, Mark Ramsdale, Stuart A. Wilson, Nicolas Viphakone and Avi Srivastava. Their work appears in journals such as Scientific Reports, Nature Communications, Cell Reports, Genome biology and Blood.
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.