Mark Chaisson
- Cancer Research top 0.1%
- Molecular Biology top 0.05%
- Genomics and Phylogenetic Studies 23
- RNA and protein synthesis mechanisms 15
- Advanced biosensing and bioanalysis techniques 3
- Machine Learning in Bioinformatics 2
- Aging top 0.5%
- Immunology top 0.2%
- Genetics top 0.2%
- Genomics and Rare Diseases 4
- Genetic Associations and Epidemiology 2
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- Chromosomal and Genetic Variations 10
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- Algorithms and Data Compression 3
- Co-authors
- Alexander DobinFelix SchlesingerJörg DrenkowSonali JhaPhilippe BatutT GingerasChris ZaleskiCarrie Davis
- Partner nations
- United StatesItalyTürkiye
In The Last Decade
Mark Chaisson
29 papers receiving 32.1k citations
Hit Papers
Peers
Comparison fields: 5 of 187
- Cancer Research 4.6k
- Molecular Biology 20.3k
- Aging 488
- Immunology 4.4k
- Genetics 4.3k
Countries citing papers authored by Mark Chaisson
This map shows the geographic impact of Mark Chaisson'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 Mark Chaisson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mark Chaisson more than expected).
Fields of papers citing papers by Mark Chaisson
This network shows the impact of papers produced by Mark Chaisson. 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 Mark Chaisson. The network helps show where Mark Chaisson may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mark Chaisson, 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 | 24 | |
| 2 | 2023 | 16 | |
| 3 | 2023 | 2 | |
| 4 | 2023 | 19 | |
| 5 | 2022 | 8 | |
| 6 | 2021 | 27 | |
| 7 | 2018 | 29 | |
| 8 | 2018 | 95 | |
| 9 | 2017 | 16 | |
| 10 | 2017 | 16 | |
| 11 | 2016 | 209 | |
| 12 | 2016 | 218 | |
| 13 | 2016 | 235 | |
| 14 | 2014 | 179 | |
| 15 | Resolving the complexity of the human genome using single-molecule sequencingbreakdown → | 2014 | 499 |
| 16 | Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): application and theorybreakdown → | 2012 | 827 |
| 17 | 2011 | 37 | |
| 18 | 2008 | 174 | |
| 19 | 2007 | 297 | |
| 20 | 2004 | 126 |
About Mark Chaisson
Mark Chaisson is a scholar working on Molecular Biology, Genetics and Plant Science, having authored 30 papers that have together received 32.3k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (23 papers), RNA and protein synthesis mechanisms (15 papers), Chromosomal and Genetic Variations (10 papers), Genomics and Rare Diseases (4 papers), Algorithms and Data Compression (3 papers), Advanced biosensing and bioanalysis techniques (3 papers), Machine Learning in Bioinformatics (2 papers) and Genetic Associations and Epidemiology (2 papers). The work is most often cited by research in Cancer Research (4.6k citations), Molecular Biology (20.3k citations) and Aging (488 citations). Mark Chaisson has collaborated with scholars based in United States, Italy and Türkiye. Frequent co-authors include Alexander Dobin, Felix Schlesinger, Jörg Drenkow, Sonali Jha, Philippe Batut, T Gingeras, Chris Zaleski, Carrie Davis, Glenn Tesler and Pavel A. Pevzner. Their work appears in journals such as Genome Research, Bioinformatics, Genome biology, Proceedings of the National Academy of Sciences and Nature Methods.
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.