Chris Mungall
Impact in
- Molecular Biology top 0.2%
- Biomedical Text Mining and Ontologies
- Bioinformatics and Genomic Networks
- Genomics and Phylogenetic Studies
- Gene expression and cancer classification
- RNA and protein synthesis mechanisms
- Genetics top 0.5%
- Genomics and Rare Diseases
Papers in
-
- Semantic Web and Ontologies 62
-
- Biomedical Text Mining and Ontologies 114
- Bioinformatics and Genomic Networks 70
- Genomics and Phylogenetic Studies 38
- Gene expression and cancer classification 12
- Co-authors
- Suzanna LewisShengqiang ShuAmelia IrelandMichael AshburnerMelissa HaendelLincoln SteinBarry SmithSeth Carbon
- Journals
- Journal of Biomedical Semantics (14 papers)Genome biology (10 papers)BMC Bioinformatics (10 papers)Bioinformatics (9 papers)Nucleic Acids Research (6 papers)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Chris Mungall
161 papers receiving 13.5k citations
Hit Papers
Peers
Comparison fields: 5 of 197
- Molecular Biology 10.6k
- Genetics 2.8k
- Artificial Intelligence 3.1k
- Aging 150
- Information Systems and Management 504
Countries citing papers authored by Chris Mungall
This map shows the geographic impact of Chris Mungall'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 Chris Mungall with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris Mungall more than expected).
Fields of papers citing papers by Chris Mungall
This network shows the impact of papers produced by Chris Mungall. 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 Chris Mungall. The network helps show where Chris Mungall may publish in the future.
Co-authors
The 25 scholars most cited alongside Chris Mungall, 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 | 1 | |
| 2 | 2025 | 4 | |
| 3 | 2024 | 3 | |
| 4 | 2024 | 2 | |
| 5 | 2024 | 1 | |
| 6 | 2024 | 31 | |
| 7 | 2024 | 0 | |
| 8 | 2021 | 4 | |
| 9 | 2019 | 11 | |
| 10 | 2019 | 67 | |
| 11 | Standardizing Ontology Workflows Using ROBOT. | 2018 | 1 |
| 12 | 2017 | 4 | |
| 13 | Tailoring the NCI Thesaurus for Use in The OBO Library. | 2017 | 1 |
| 14 | 2013 | 40 | |
| 15 | Mapping of glossary terms from the Flora of North America to the Plant Ontology enhances both resources. | 2012 | 0 |
| 16 | Revising the Cell Ontology. | 2011 | 1 |
| 17 | Processing OWL2 ontologies using thea: an application of logic programming | 2009 | 30 |
| 18 | A Call for an Abductive Reasoning Feature in OWL-Reasoning Tools toward Ontology Quality Control. | 2008 | 6 |
| 19 | Representing Phenotypes in OWL. | 2007 | 22 |
| 20 | The National Center for Biomedical Ontology: Advancing Biomedicine through Structured \nOrganization of Scientific Knowledge | 2006 | 110 |
About Chris Mungall
Chris Mungall is a scholar working on Artificial Intelligence, Molecular Biology, Genetics, Biophysics and Ecological Modeling, having authored 165 papers that have together received 14.0k indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (114 papers), Bioinformatics and Genomic Networks (70 papers), Semantic Web and Ontologies (62 papers), Genomics and Phylogenetic Studies (38 papers), Genomics and Rare Diseases (33 papers), Gene expression and cancer classification (12 papers), Genomic variations and chromosomal abnormalities (8 papers) and Research Data Management Practices (6 papers). The work is most often cited by research in Molecular Biology (10.6k citations), Genetics (2.8k citations), Artificial Intelligence (3.1k citations), Aging (150 citations) and Information Systems and Management (504 citations). Chris Mungall has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Suzanna Lewis, Shengqiang Shu, Amelia Ireland, Michael Ashburner, Melissa Haendel, Lincoln Stein, Barry Smith, Seth Carbon, Karen Eilbeck and Brad Marshall. Their work appears in journals such as Journal of Biomedical Semantics, Genome biology, BMC Bioinformatics, Bioinformatics and Nucleic Acids 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.