David Wild
- Computational Theory and Mathematics top 0.5%
- Computational Drug Discovery Methods 35
- Molecular Biology top 10%
- Bioinformatics and Genomic Networks 27
- Biomedical Text Mining and Ontologies 17
- Genetics, Bioinformatics, and Biomedical Research 10
- Metabolomics and Mass Spectrometry Studies 5
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- Scientific Computing and Data Management 7
- Animal Science and Zoology top 5%
- Meat and Animal Product Quality 6
- Artificial Intelligence top 5%
- Semantic Web and Ontologies 8
- Co-authors
- Ying DingBin ChenR.H. LockerRajarshi GuhaPeter WillettXiao DongQian ZhuDazhi Jiao
- Journals
- Journal of Cheminformatics (11 papers)Journal of Chemical Information and Modeling (8 papers)Meat Science (7 papers)
- Partner nations
- United StatesUnited KingdomNew Zealand
In The Last Decade
David Wild
87 papers receiving 1.9k citations
Peers
Comparison fields: 5 of 159
- Computational Theory and Mathematics 896
- Molecular Biology 1.2k
- Information Systems and Management 110
- Animal Science and Zoology 125
- Artificial Intelligence 358
Countries citing papers authored by David Wild
This map shows the geographic impact of David Wild'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 David Wild with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Wild more than expected).
Fields of papers citing papers by David Wild
This network shows the impact of papers produced by David Wild. 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 David Wild. The network helps show where David Wild may publish in the future.
Co-authorship network
The 25 scholars most cited alongside David Wild, 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 | 0 | |
| 2 | 2023 | 3 | |
| 3 | 2022 | 12 | |
| 4 | 2021 | 8 | |
| 5 | 2018 | 9 | |
| 6 | Exploring Project Management Methodologies Used Within Data Science Teams | 2018 | 21 |
| 7 | 2016 | 0 | |
| 8 | 2015 | 50 | |
| 9 | 2013 | 29 | |
| 10 | 2013 | 5 | |
| 11 | 2013 | 78 | |
| 12 | 2013 | 16 | |
| 13 | 2012 | 7 | |
| 14 | 2012 | 23 | |
| 15 | 2009 | 14 | |
| 16 | 2001 | 2 | |
| 17 | 1999 | 11 | |
| 18 | 1994 | 23 | |
| 19 | 1988 | 14 | |
| 20 | 1984 | 8 |
About David Wild
David Wild is a scholar working on Computational Theory and Mathematics, Information Systems and Management and Molecular Biology, having authored 93 papers that have together received 2.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (35 papers), Bioinformatics and Genomic Networks (27 papers), Biomedical Text Mining and Ontologies (17 papers), Genetics, Bioinformatics, and Biomedical Research (10 papers), Semantic Web and Ontologies (8 papers), Scientific Computing and Data Management (7 papers), Meat and Animal Product Quality (6 papers) and Metabolomics and Mass Spectrometry Studies (5 papers). The work is most often cited by research in Computational Theory and Mathematics (896 citations), Molecular Biology (1.2k citations) and Information Systems and Management (110 citations). David Wild has collaborated with scholars based in United States, United Kingdom and New Zealand. Frequent co-authors include Ying Ding, Bin Chen, R.H. Locker, Rajarshi Guha, Peter Willett, Xiao Dong, Qian Zhu, Dazhi Jiao, Abhik Seal and Huijun Wang. Their work appears in journals such as Journal of Cheminformatics, Journal of Chemical Information and Modeling, Meat Science, BMC 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.