Jonathan J. Ward
- Molecular Biology top 2%
- Materials Chemistry top 10%
- Cell Biology top 2%
- Plant Science top 10%
- Genetics top 10%
- Co-authors
- David T. JonesLiam J. McGuffinJaspreet Singh SodhiBernard F. BuxtonKevin BrysonFrançois NédélecChuanhai FuIsabelle Loïodice
- Topics
- Protein Structure and Dynamics (6 papers)Microtubule and mitosis dynamics (5 papers)Machine Learning in Bioinformatics (4 papers)
- Partner nations
- United KingdomGermanyFrance
In The Last Decade
Jonathan J. Ward
14 papers receiving 3.5k citations
Hit Papers
Peers
Comparison fields: 5 of 121
- Molecular Biology 3.0k
- Materials Chemistry 719
- Cell Biology 528
- Plant Science 285
- Genetics 271
Countries citing papers authored by Jonathan J. Ward
This map shows the geographic impact of Jonathan J. Ward'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 Jonathan J. Ward with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan J. Ward more than expected).
Fields of papers citing papers by Jonathan J. Ward
This network shows the impact of papers produced by Jonathan J. Ward. 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 Jonathan J. Ward. The network helps show where Jonathan J. Ward may publish in the future.
Co-authorship network of co-authors of Jonathan J. Ward
This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan J. Ward. A scholar is included among the top collaborators of Jonathan J. Ward based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jonathan J. Ward. Jonathan J. Ward is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 45 | |
| 2 | 59 | |
| 3 | 13 | |
| 4 | 112 | |
| 5 | 60 | |
| 6 | 32 | |
| 7 | 61 | |
| 8 | Protein structure prediction servers at University College Londonbreakdown → | 636 |
| 9 | 2 | |
| 10 | 2 | |
| 11 | 107 | |
| 12 | Prediction and Functional Analysis of Native Disorder in Proteins from the Three Kingdoms of Lifebreakdown → | 1643 |
| 13 | The DISOPRED server for the prediction of protein disorderbreakdown → | 575 |
| 14 | 156 |
About Jonathan J. Ward
Jonathan J. Ward is a scholar working on Cell Biology, Molecular Biology and Plant Science, having authored 14 papers that have together received 3.5k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (6 papers), Microtubule and mitosis dynamics (5 papers) and Machine Learning in Bioinformatics (4 papers). The work is most often cited by research in Molecular Biology (3.0k citations), Cell Biology (528 citations) and Materials Chemistry (719 citations). Jonathan J. Ward has collaborated with scholars based in United Kingdom, Germany and France. Frequent co-authors include David T. Jones, Liam J. McGuffin, Jaspreet Singh Sodhi, Bernard F. Buxton, Kevin Bryson, François Nédélec, Chuanhai Fu, Isabelle Loïodice, Phong T. Tran and Lorenz Wernisch. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Bioinformatics.
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.