Ian Castleden

2.4k total citations
28 papers, 1.8k citations indexed

About

Ian Castleden is a scholar working on Molecular Biology, Spectroscopy and Plant Science. According to data from OpenAlex, Ian Castleden has authored 28 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 10 papers in Spectroscopy and 4 papers in Plant Science. Recurrent topics in Ian Castleden's work include Advanced Proteomics Techniques and Applications (9 papers), Genomics and Phylogenetic Studies (8 papers) and Machine Learning in Bioinformatics (7 papers). Ian Castleden is often cited by papers focused on Advanced Proteomics Techniques and Applications (9 papers), Genomics and Phylogenetic Studies (8 papers) and Machine Learning in Bioinformatics (7 papers). Ian Castleden collaborates with scholars based in Australia, United States and Denmark. Ian Castleden's co-authors include A. Harvey Millar, Sandra K. Tanz, Cornelia M. Hooper, Ian Small, Nader Aryamanesh, Michaël Vacher, Clark J. Nelson, Josua Trösch, Shaobai Huang and Lie Li and has published in prestigious journals such as Nucleic Acids Research, Bioinformatics and The Plant Cell.

In The Last Decade

Ian Castleden

28 papers receiving 1.7k citations

Peers

Ian Castleden
Sandra K. Tanz Australia
Lisa Giacomelli Italy
Hervé Degand Belgium
Philippe Giegé France
Etienne H. Meyer Germany
Monika W. Murcha Australia
Stephan Wagner Germany
Marcelo Desimone Germany
Matthias Hirsch‐Hoffmann Switzerland
Andrea Rudella United States
Sandra K. Tanz Australia
Ian Castleden
Citations per year, relative to Ian Castleden Ian Castleden (= 1×) peers Sandra K. Tanz

Countries citing papers authored by Ian Castleden

Since Specialization
Citations

This map shows the geographic impact of Ian Castleden'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 Ian Castleden with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ian Castleden more than expected).

Fields of papers citing papers by Ian Castleden

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ian Castleden. 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 Ian Castleden. The network helps show where Ian Castleden may publish in the future.

Co-authorship network of co-authors of Ian Castleden

This figure shows the co-authorship network connecting the top 25 collaborators of Ian Castleden. A scholar is included among the top collaborators of Ian Castleden 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 Ian Castleden. Ian Castleden is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
David, Rakesh, et al.. (2021). Identifying protein subcellular localisation in scientific literature using bidirectional deep recurrent neural network. Scientific Reports. 11(1). 1696–1696. 4 indexed citations
2.
Hooper, Cornelia M., et al.. (2021). Subcellular Proteomics as a Unified Approach of Experimental Localizations and Computed Prediction Data for Arabidopsis and Crop Plants. Advances in experimental medicine and biology. 1346. 67–89. 3 indexed citations
3.
Liberti, Joanito, Ryan Dosselli, Morten Schiøtt, et al.. (2019). Seminal fluid compromises visual perception in honeybee queens reducing their survival during additional mating flights. eLife. 8. 19 indexed citations
4.
Gutmann, Bernard, Mareike Schallenberg‐Rüdinger, H. Lenz, et al.. (2019). The Expansion and Diversification of Pentatricopeptide Repeat RNA-Editing Factors in Plants. Molecular Plant. 13(2). 215–230. 84 indexed citations
5.
Li, Lie, Clark J. Nelson, Josua Trösch, et al.. (2017). Protein Degradation Rate in Arabidopsis thaliana Leaf Growth and Development. The Plant Cell. 29(2). 207–228. 206 indexed citations
6.
Hooper, Cornelia M., Ian Castleden, Sandra K. Tanz, Nader Aryamanesh, & A. Harvey Millar. (2016). SUBA4: the interactive data analysis centre for Arabidopsis subcellular protein locations. Nucleic Acids Research. 45(D1). D1064–D1074. 315 indexed citations
7.
Cheng, Shifeng, Bernard Gutmann, Xiao Zhong, et al.. (2016). Redefining the structural motifs that determine RNA binding and RNA editing by pentatricopeptide repeat proteins in land plants. The Plant Journal. 85(4). 532–547. 244 indexed citations
8.
Hooper, Cornelia M., Ian Castleden, Nader Aryamanesh, Richard P. Jacoby, & A. Harvey Millar. (2015). Finding the Subcellular Location of Barley, Wheat, Rice and Maize Proteins: The Compendium of Crop Proteins with Annotated Locations (cropPAL). Plant and Cell Physiology. 57(1). e9–e9. 51 indexed citations
9.
Tanz, Sandra K., Ian Castleden, Cornelia M. Hooper, Ian Small, & A. Harvey Millar. (2014). Using the SUBcellular database for Arabidopsis proteins to localize the Deg protease family. Frontiers in Plant Science. 5. 396–396. 18 indexed citations
10.
Tanz, Sandra K., Ian Castleden, Ian Small, & A. Harvey Millar. (2013). Fluorescent protein tagging as a tool to define the subcellular distribution of proteins in plants. Frontiers in Plant Science. 4. 214–214. 61 indexed citations
11.
Tanz, Sandra K., Ian Castleden, Cornelia M. Hooper, et al.. (2012). SUBA3: a database for integrating experimentation and prediction to define the SUBcellular location of proteins in Arabidopsis. Nucleic Acids Research. 41(D1). D1185–D1191. 236 indexed citations
12.
Narsai, Reena, Ian Castleden, & James Whelan. (2010). Common and distinct organ and stress responsive transcriptomic patterns in Oryza sativa and Arabidopsis thaliana. BMC Plant Biology. 10(1). 262–262. 38 indexed citations
13.
Ito, Jun, Nicolas L. Taylor, Ian Castleden, et al.. (2009). A survey of the Arabidopsis thaliana mitochondrial phosphoproteome. PROTEOMICS. 9(17). 4229–4240. 67 indexed citations
14.
Eubel, Holger, Etienne H. Meyer, Nicolas L. Taylor, et al.. (2008). Novel Proteins, Putative Membrane Transporters, and an Integrated Metabolic Network Are Revealed by Quantitative Proteomic Analysis of Arabidopsis Cell Culture Peroxisomes  . PLANT PHYSIOLOGY. 148(4). 1809–1829. 156 indexed citations
15.
Hall, Sydney R., et al.. (2000). Relational Expressions in STAR File Dictionaries. Journal of Chemical Information and Computer Sciences. 40(6). 1289–1301. 3 indexed citations
16.
Castleden, Ian & S. Fortier. (1994). Intensity statistics. I. Acta Crystallographica Section A Foundations of Crystallography. 50(1). 9–17. 1 indexed citations
17.
18.
Fortier, S., Ian Castleden, Janice Glasgow, et al.. (1993). Molecular scene analysis: the integration of direct-methods and artificial-intelligence strategies for solving protein crystal structure. Acta Crystallographica Section D Biological Crystallography. 49(1). 168–178. 15 indexed citations
19.
Castleden, Ian. (1992). Minimizing free energy as a direct method for phase determination. Acta Crystallographica Section A Foundations of Crystallography. 48(2). 197–209. 9 indexed citations
20.
Castleden, Ian. (1987). A joint probability distribution of invariants for all space groups. Acta Crystallographica Section A Foundations of Crystallography. 43(3). 384–393. 1 indexed citations

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.

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