Ted Liefeld
Impact in
-
- Scientific Computing and Data Management
Papers in
-
- Gene expression and cancer classification 4
- Single-cell and spatial transcriptomics 4
- Genomics and Phylogenetic Studies 2
- Bioinformatics and Genomic Networks 2
- Genetics, Bioinformatics, and Biomedical Research 2
-
- Scientific Computing and Data Management 3
- Co-authors
- Seán Martin (2 shared papers)Tim W. Clark (1 shared paper)Jill P. Mesirov (9 shared papers)Michael Reich (9 shared papers)Moses M. Hohman (1 shared paper)Pablo Tamayo (3 shared papers)Barbara Hill (3 shared papers)Peili Zhang (1 shared paper)
- Journals
- Briefings in Bioinformatics (1 paper)Drug Discovery Today (1 paper)Nature Protocols (1 paper)JCO Clinical Cancer Informatics (1 paper)Cell Systems (1 paper)
- Partner nations
- United StatesPortugalCanada
In The Last Decade
Ted Liefeld
10 papers receiving 193 citations
Peers
Comparison fields: 5 of 40
- Information Systems and Management 50
- Ecological Modeling 14
- Biophysics 12
- Molecular Biology 125
- Information Systems 32
Countries citing papers authored by Ted Liefeld
This map shows the geographic impact of Ted Liefeld'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 Ted Liefeld with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ted Liefeld more than expected).
Fields of papers citing papers by Ted Liefeld
This network shows the impact of papers produced by Ted Liefeld. 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 Ted Liefeld. The network helps show where Ted Liefeld may publish in the future.
Co-authors
The 25 scholars most cited alongside Ted Liefeld, 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 | 2004 | 107 | |
| 2 | 2017 | 21 | |
| 3 | 2005 | 20 | |
| 4 | 2005 | 20 | |
| 5 | 2013 | 13 | |
| 6 | 2023 | 10 | |
| 7 | 2020 | 9 | |
| 8 | 2023 | 2 | |
| 9 | 2013 | 2 | |
| 10 | 2021 | 1 | |
| 11 | 2024 | 0 |
About Ted Liefeld
Ted Liefeld is a scholar working on Molecular Biology, Information Systems and Management, Information Systems, Oncology and Biophysics, having authored 11 papers that have together received 205 indexed citations. Recurring topics across this work include Gene expression and cancer classification (4 papers), Single-cell and spatial transcriptomics (4 papers), Scientific Computing and Data Management (3 papers), Genomics and Phylogenetic Studies (2 papers), Research Data Management Practices (2 papers), Bioinformatics and Genomic Networks (2 papers), Genetics, Bioinformatics, and Biomedical Research (2 papers) and Cancer Genomics and Diagnostics (1 paper). The work is most often cited by research in Information Systems and Management (50 citations), Ecological Modeling (14 citations), Biophysics (12 citations), Molecular Biology (125 citations) and Information Systems (32 citations). Ted Liefeld has collaborated with scholars based in United States, Portugal and Canada. Frequent co-authors include Seán Martin, Tim W. Clark, Jill P. Mesirov, Michael Reich, Moses M. Hohman, Pablo Tamayo, Barbara Hill, Peili Zhang, Joshua Gould and Helga Thorvaldsdóttir. Their work appears in journals such as Briefings in Bioinformatics, Drug Discovery Today, Nature Protocols, JCO Clinical Cancer Informatics and Cell Systems.
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.