Rasko Leinonen
Impact in
- Molecular Biology top 5%
- Genomics and Phylogenetic Studies
- RNA modifications and cancer
- RNA and protein synthesis mechanisms
- Bioinformatics and Genomic Networks
- Gene expression and cancer classification
- RNA Research and Splicing
- Cancer Research top 5%
- Cancer-related molecular mechanisms research
Papers in
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- Genomics and Phylogenetic Studies 8
- RNA and protein synthesis mechanisms 3
- Machine Learning in Bioinformatics 2
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- Advanced Proteomics Techniques and Applications 3
- Co-authors
- Martin Shumway (3 shared papers)Hideaki Sugawara (1 shared paper)Yuichi Kodama (1 shared paper)Guy Cochrane (2 shared papers)Ewan Birney (1 shared paper)Markus Hsi-Yang Fritz (1 shared paper)Rolf Apweiler (3 shared papers)Richard Smith (1 shared paper)
- Journals
- Bioinformatics (4 papers)Nucleic Acids Research (3 papers)Nature Methods (1 paper)PLoS ONE (1 paper)BMC Bioinformatics (1 paper)
- Partner nations
- United KingdomUnited StatesJapan
In The Last Decade
Rasko Leinonen
11 papers receiving 3.3k citations
Rasko Leinonen's Hit Papers
Peers
Comparison fields: 5 of 151
- Molecular Biology 2.2k
- Cancer Research 369
- Genetics 440
- Endocrinology 65
- Plant Science 434
Countries citing papers authored by Rasko Leinonen
This map shows the geographic impact of Rasko Leinonen'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 Rasko Leinonen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rasko Leinonen more than expected).
Fields of papers citing papers by Rasko Leinonen
This network shows the impact of papers produced by Rasko Leinonen. 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 Rasko Leinonen. The network helps show where Rasko Leinonen may publish in the future.
Co-authors
The 25 scholars most cited alongside Rasko Leinonen, 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 | The Sequence Read Archive Hit paper breakdown → | 2010 | 1871 |
| 2 | The sequence read archive: explosive growth of sequencing data Hit paper breakdown → | 2011 | 652 |
| 3 | 2012 | 294 | |
| 4 | 2011 | 246 | |
| 5 | 2004 | 136 | |
| 6 | 2007 | 101 | |
| 7 | 2015 | 31 | |
| 8 | 2006 | 18 | |
| 9 | 2003 | 11 | |
| 10 | 2013 | 11 | |
| 11 | 2021 | 6 |
About Rasko Leinonen
Rasko Leinonen is a scholar working on Molecular Biology, Spectroscopy, Ecology, Artificial Intelligence and Genetics, having authored 11 papers that have together received 3.4k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (8 papers), Advanced Proteomics Techniques and Applications (3 papers), RNA and protein synthesis mechanisms (3 papers), Genomics and Rare Diseases (2 papers), Microbial Community Ecology and Physiology (2 papers), Algorithms and Data Compression (2 papers), Machine Learning in Bioinformatics (2 papers) and Streptococcal Infections and Treatments (1 paper). The work is most often cited by research in Molecular Biology (2.2k citations), Cancer Research (369 citations), Genetics (440 citations), Endocrinology (65 citations) and Plant Science (434 citations). Rasko Leinonen has collaborated with scholars based in United Kingdom, United States and Japan. Frequent co-authors include Martin Shumway, Hideaki Sugawara, Yuichi Kodama, Guy Cochrane, Ewan Birney, Markus Hsi-Yang Fritz, Rolf Apweiler, Richard Smith, Brendan Vaughan and Paul Flicek. Their work appears in journals such as Bioinformatics, Nucleic Acids Research, Nature Methods, PLoS ONE 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.