Matthew Hibbs
- Aging top 5%
- Ophthalmology top 2%
- Molecular Biology top 5%
- Bioinformatics and Genomic Networks 16
- Gene expression and cancer classification 12
- Genomics and Phylogenetic Studies 5
- Gene Regulatory Network Analysis 4
- Microbial Metabolic Engineering and Bioproduction 4
- RNA modifications and cancer 3
- RNA Research and Splicing 3
- Machine Learning in Bioinformatics 2
- Neurology top 5%
- Biophysics top 5%
- Co-authors
- Olga G. TroyanskayaChad L. MyersCurtis HuttenhowerDavid HessKai LiAlexander GoesmannAnne‐Claude GavinSéan O’Donoghue
- Cited by
- AgingOphthalmologyMolecular Biology
- Partner nations
- United StatesCanadaNorway
In The Last Decade
Matthew Hibbs
33 papers receiving 2.6k citations
Peers
Comparison fields: 5 of 139
- Aging 69
- Ophthalmology 278
- Molecular Biology 2.1k
- Neurology 154
- Biophysics 85
Countries citing papers authored by Matthew Hibbs
This map shows the geographic impact of Matthew Hibbs'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 Matthew Hibbs with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew Hibbs more than expected).
Fields of papers citing papers by Matthew Hibbs
This network shows the impact of papers produced by Matthew Hibbs. 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 Matthew Hibbs. The network helps show where Matthew Hibbs may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Matthew Hibbs, 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 | 2023 | 5 | |
| 2 | 2020 | 26 | |
| 3 | 2016 | 40 | |
| 4 | 2016 | 29 | |
| 5 | 2015 | 55 | |
| 6 | 2015 | 1 | |
| 7 | 2012 | 3 | |
| 8 | 2012 | 69 | |
| 9 | 2011 | 364 | |
| 10 | 2010 | 255 | |
| 11 | 2010 | 48 | |
| 12 | 2010 | 423 | |
| 13 | 2009 | 118 | |
| 14 | 2009 | 153 | |
| 15 | Interpreting the Basin Closure Law in Montana: The Permissibility of "Prestream Capture" -- Montana Trout Unlimited v. Montana Department of Natural Resources and Conservation | 2008 | 1 |
| 16 | 2007 | 52 | |
| 17 | 2006 | 154 | |
| 18 | 2006 | 46 | |
| 19 | 2005 | 161 | |
| 20 | 2005 | 44 |
About Matthew Hibbs
Matthew Hibbs is a scholar working on Aging, Molecular Biology and Biophysics, having authored 33 papers that have together received 2.6k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (16 papers), Gene expression and cancer classification (12 papers), Genomics and Phylogenetic Studies (5 papers), Gene Regulatory Network Analysis (4 papers), Microbial Metabolic Engineering and Bioproduction (4 papers), RNA modifications and cancer (3 papers), RNA Research and Splicing (3 papers) and Machine Learning in Bioinformatics (2 papers). The work is most often cited by research in Aging (69 citations), Ophthalmology (278 citations) and Molecular Biology (2.1k citations). Matthew Hibbs has collaborated with scholars based in United States, Canada and Norway. Frequent co-authors include Olga G. Troyanskaya, Chad L. Myers, Curtis Huttenhower, David Hess, Kai Li, Alexander Goesmann, Anne‐Claude Gavin, Séan O’Donoghue, Oliver Kohlbacher and Reinhard Schneider. Their work appears in journals such as Journal of Clinical Investigation, Bioinformatics and PLoS ONE.
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.