Ben Langmead
- Molecular Biology top 0.01%
- Genomics and Phylogenetic Studies 47
- Gene expression and cancer classification 17
- RNA modifications and cancer 15
- RNA and protein synthesis mechanisms 14
- Molecular Biology Techniques and Applications 6
- Epigenetics and DNA Methylation 6
- Cancer Research top 0.05%
- Cancer-related molecular mechanisms research 7
- Plant Science top 0.01%
- Endocrinology top 0.1%
- Aging top 0.2%
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- Algorithms and Data Compression 23
- Co-authors
- Steven L. SalzbergDaehwan KimMihai PopCole TrapnellJennifer LuDerrick E. WoodRafael A. IrizarryKasper D. Hansen
- Partner nations
- United StatesCanadaItaly
In The Last Decade
Ben Langmead
73 papers receiving 78.4k citations
Hit Papers
Peers
Comparison fields: 5 of 213
- Molecular Biology 49.5k
- Cancer Research 8.7k
- Plant Science 18.4k
- Endocrinology 2.1k
- Aging 708
Countries citing papers authored by Ben Langmead
This map shows the geographic impact of Ben Langmead'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 Ben Langmead with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ben Langmead more than expected).
Fields of papers citing papers by Ben Langmead
This network shows the impact of papers produced by Ben Langmead. 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 Ben Langmead. The network helps show where Ben Langmead may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ben Langmead, 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 | 2025 | 2 | |
| 2 | 2025 | 5 | |
| 3 | 2025 | 1 | |
| 4 | 2024 | 6 | |
| 5 | 2023 | 5 | |
| 6 | 2022 | 1 | |
| 7 | 2022 | 3 | |
| 8 | 2022 | 1 | |
| 9 | 2022 | 27 | |
| 10 | 2021 | 8 | |
| 11 | 2021 | 6 | |
| 12 | 2021 | 14 | |
| 13 | 2020 | 15 | |
| 14 | 2020 | 32 | |
| 15 | 2019 | 18 | |
| 16 | Scaling read aligners to hundreds of threads on general-purpose processorsbreakdown → | 2018 | 492 |
| 17 | 2017 | 24 | |
| 18 | 2016 | 3 | |
| 19 | 2016 | 38 | |
| 20 | 2014 | 157 |
About Ben Langmead
Ben Langmead is a scholar working on Molecular Biology, Artificial Intelligence and Cancer Research, having authored 79 papers that have together received 79.0k indexed citations. Recurring topics across this work include Genomics and Phylogenetic Studies (47 papers), Algorithms and Data Compression (23 papers), Gene expression and cancer classification (17 papers), RNA modifications and cancer (15 papers), RNA and protein synthesis mechanisms (14 papers), Cancer-related molecular mechanisms research (7 papers), Molecular Biology Techniques and Applications (6 papers) and Epigenetics and DNA Methylation (6 papers). The work is most often cited by research in Molecular Biology (49.5k citations), Cancer Research (8.7k citations) and Plant Science (18.4k citations). Ben Langmead has collaborated with scholars based in United States, Canada and Italy. Frequent co-authors include Steven L. Salzberg, Daehwan Kim, Mihai Pop, Cole Trapnell, Jennifer Lu, Derrick E. Wood, Rafael A. Irizarry, Kasper D. Hansen, Jeffrey T. Leek and Héctor Corrada Bravo. Their work appears in journals such as Genome biology, Bioinformatics, iScience, Genome Research and Nature Communications.
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.