Maxwell W. Libbrecht
Impact in
- Health Informatics top 2%
- Biophysics top 5%
Papers in
- Co-authors
- William Stafford NobleNick DexterWyeth W. WassermanSara MostafaviGherman NovakovskyJeffrey A. BilmesMichael M. HoffmanKenneth G. Libbrecht
- Journals
- Bioinformatics (5 papers)Nature Communications (2 papers)Nature Reviews Genetics (2 papers)Genome biology (2 papers)Genome Research (2 papers)
- Partner nations
- CanadaUnited StatesUnited Kingdom
In The Last Decade
Maxwell W. Libbrecht
28 papers receiving 1.7k citations
Hit Papers
Peers
Comparison fields: 5 of 181
- Health Informatics 66
- Biophysics 79
- Molecular Biology 905
- Computational Mathematics 7
- Health Information Management 52
Countries citing papers authored by Maxwell W. Libbrecht
This map shows the geographic impact of Maxwell W. Libbrecht'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 Maxwell W. Libbrecht with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maxwell W. Libbrecht more than expected).
Fields of papers citing papers by Maxwell W. Libbrecht
This network shows the impact of papers produced by Maxwell W. Libbrecht. 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 Maxwell W. Libbrecht. The network helps show where Maxwell W. Libbrecht may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Maxwell W. Libbrecht, 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 | 3 | |
| 2 | 2022 | 0 | |
| 3 | 2022 | 8 | |
| 4 | 2022 | 7 | |
| 5 | Obtaining genetics insights from deep learning via explainable artificial intelligence Hit paper breakdown → | 2022 | 185 |
| 6 | 2021 | 13 | |
| 7 | 2021 | 1 | |
| 8 | 2021 | 3 | |
| 9 | 2021 | 7 | |
| 10 | 2021 | 4 | |
| 11 | 2021 | 14 | |
| 12 | 2020 | 1 | |
| 13 | 2019 | 29 | |
| 14 | 2019 | 1 | |
| 15 | 2018 | 51 | |
| 16 | 2017 | 26 | |
| 17 | 2016 | 11 | |
| 18 | 2016 | 45 | |
| 19 | Machine learning applications in genetics and genomics Hit paper breakdown → | 2015 | 1238 |
| 20 | 2015 | 55 |
About Maxwell W. Libbrecht
Maxwell W. Libbrecht is a scholar working on Computational Mathematics, Biophysics, Media Technology, Molecular Biology and Infectious Diseases, having authored 29 papers that have together received 1.7k indexed citations. Recurring topics across this work include Genomics and Chromatin Dynamics (13 papers), Genomics and Phylogenetic Studies (11 papers), Epigenetics and DNA Methylation (7 papers), Gene expression and cancer classification (6 papers), Tuberculosis Research and Epidemiology (4 papers), Bioinformatics and Genomic Networks (4 papers), RNA and protein synthesis mechanisms (4 papers) and Machine Learning in Bioinformatics (3 papers). The work is most often cited by research in Health Informatics (66 citations), Biophysics (79 citations), Molecular Biology (905 citations), Computational Mathematics (7 citations) and Health Information Management (52 citations). Maxwell W. Libbrecht has collaborated with scholars based in Canada, United States and United Kingdom. Frequent co-authors include William Stafford Noble, Nick Dexter, Wyeth W. Wasserman, Sara Mostafavi, Gherman Novakovsky, Jeffrey A. Bilmes, Michael M. Hoffman, Kenneth G. Libbrecht, Timothy Durham and James Jeffry Howbert. Their work appears in journals such as Bioinformatics, Nature Communications, Nature Reviews Genetics, Genome biology and Genome Research.
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.