Edward J. Beard
Impact in
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- Computational Drug Discovery Methods
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- Machine Learning in Materials Science
- Quantum Dots Synthesis And Properties
- X-ray Diffraction in Crystallography
Papers in
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- Machine Learning in Materials Science 5
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- Computational Drug Discovery Methods 3
- Co-authors
- Jacqueline M. Cole (7 shared papers)Álvaro Vázquez‐Mayagoitia (4 shared papers)Venkatram Vishwanath (2 shared papers)Ganesh Sivaraman (2 shared papers)Govardhana Babu Bodedla (2 shared papers)Fernando Riveros-Mckay (1 shared paper)Rachel Moore (1 shared paper)Jingwen Jia (2 shared papers)
- Journals
- Scientific Data (2 papers)Advanced Energy Materials (2 papers)Journal of Chemical Information and Modeling (2 papers)PLoS ONE (1 paper)Bulletin of the American Physical Society (1 paper)
- Partner nations
- United KingdomUnited StatesHong Kong
In The Last Decade
Edward J. Beard
8 papers receiving 320 citations
Edward J. Beard's Hit Papers
Peers
Comparison fields: 5 of 76
- Computational Theory and Mathematics 73
- Materials Chemistry 187
- Health Informatics 5
- Structural Biology 4
- Renewable Energy, Sustainability and the Environment 35
Countries citing papers authored by Edward J. Beard
This map shows the geographic impact of Edward J. Beard'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 Edward J. Beard with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Edward J. Beard more than expected).
Fields of papers citing papers by Edward J. Beard
This network shows the impact of papers produced by Edward J. Beard. 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 Edward J. Beard. The network helps show where Edward J. Beard may publish in the future.
Co-authors
The 25 scholars most cited alongside Edward J. Beard, 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 | 2019 | 77 | |
| 2 | A systematic evaluation of the performance and properties of the UK Biobank Polygenic Risk Score (PRS) Release Hit paper breakdown → | 2024 | 62 |
| 3 | 2022 | 51 | |
| 4 | 2018 | 50 | |
| 5 | 2019 | 42 | |
| 6 | 2020 | 32 | |
| 7 | 2019 | 8 | |
| 8 | UV/vis absorption spectra database auto-generated for optical applications via the Argonne data science program | 2019 | 1 |
About Edward J. Beard
Edward J. Beard is a scholar working on Materials Chemistry, Computational Theory and Mathematics, Industrial and Manufacturing Engineering, Renewable Energy, Sustainability and the Environment and Molecular Biology, having authored 8 papers that have together received 323 indexed citations. Recurring topics across this work include Machine Learning in Materials Science (5 papers), Computational Drug Discovery Methods (3 papers), Water Quality Monitoring and Analysis (2 papers), Advanced Photocatalysis Techniques (2 papers), Chalcogenide Semiconductor Thin Films (1 paper), Mineral Processing and Grinding (1 paper), Epigenetics and DNA Methylation (1 paper) and Genetic Syndromes and Imprinting (1 paper). The work is most often cited by research in Computational Theory and Mathematics (73 citations), Materials Chemistry (187 citations), Health Informatics (5 citations), Structural Biology (4 citations) and Renewable Energy, Sustainability and the Environment (35 citations). Edward J. Beard has collaborated with scholars based in United Kingdom, United States and Hong Kong. Frequent co-authors include Jacqueline M. Cole, Álvaro Vázquez‐Mayagoitia, Venkatram Vishwanath, Ganesh Sivaraman, Govardhana Babu Bodedla, Fernando Riveros-Mckay, Rachel Moore, Jingwen Jia, Peter Donnelly and Song Xue. Their work appears in journals such as Scientific Data, Advanced Energy Materials, Journal of Chemical Information and Modeling, PLoS ONE and Bulletin of the American Physical Society.
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.