Andrew Lonie

5.2k total citations
41 papers, 1.0k citations indexed

About

Andrew Lonie is a scholar working on Information Systems, Molecular Biology and Information Systems and Management. According to data from OpenAlex, Andrew Lonie has authored 41 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Information Systems, 17 papers in Molecular Biology and 15 papers in Information Systems and Management. Recurrent topics in Andrew Lonie's work include Scientific Computing and Data Management (15 papers), Distributed and Parallel Computing Systems (8 papers) and Research Data Management Practices (8 papers). Andrew Lonie is often cited by papers focused on Scientific Computing and Data Management (15 papers), Distributed and Parallel Computing Systems (8 papers) and Research Data Management Practices (8 papers). Andrew Lonie collaborates with scholars based in Australia, United States and United Kingdom. Andrew Lonie's co-authors include Richard J. D’Andrea, Renato Paro, Robert Saint, Richard Sinnott, Martin J. Pearse, Peter L. Wigley, Trixie A. Shinkel, Mark B. Nottle, Sean B. Maynard and Anthony J.F. d’Apice and has published in prestigious journals such as PLoS ONE, Development and PLoS Pathogens.

In The Last Decade

Andrew Lonie

40 papers receiving 993 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Andrew Lonie Australia 16 486 285 271 171 104 41 1.0k
Mohamed Abouelhoda Saudi Arabia 20 822 1.7× 388 1.4× 110 0.4× 90 0.5× 91 0.9× 72 1.6k
George S. Davidson United States 20 780 1.6× 121 0.4× 122 0.5× 70 0.4× 28 0.3× 49 1.6k
Geir Kjetil Sandve Norway 23 1.1k 2.3× 200 0.7× 53 0.2× 171 1.0× 226 2.2× 82 2.0k
Scott Christley United States 23 712 1.5× 98 0.3× 169 0.6× 118 0.7× 23 0.2× 57 1.5k
G. Christian Overton United States 20 910 1.9× 163 0.6× 34 0.1× 42 0.2× 62 0.6× 34 1.4k
Petra Fey United States 19 1.0k 2.1× 94 0.3× 28 0.1× 88 0.5× 81 0.8× 40 1.9k
Maria Emília M. T. Walter Brazil 13 374 0.8× 153 0.5× 18 0.1× 65 0.4× 45 0.4× 78 789
Yannick Pouliot United States 16 1.1k 2.2× 117 0.4× 120 0.4× 57 0.3× 84 0.8× 28 1.5k
Xosé M. Fernández United Kingdom 19 637 1.3× 203 0.7× 105 0.4× 23 0.1× 54 0.5× 41 1.0k
Pamela Greenwell United Kingdom 19 749 1.5× 132 0.5× 85 0.3× 54 0.3× 34 0.3× 66 1.2k

Countries citing papers authored by Andrew Lonie

Since Specialization
Citations

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

Fields of papers citing papers by Andrew Lonie

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Andrew Lonie

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Lonie. A scholar is included among the top collaborators of Andrew Lonie 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 Andrew Lonie. Andrew Lonie 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.
Griffin, Philippa C., et al.. (2021). Application of a bioinformatics training delivery method for reaching dispersed and distant trainees. PLoS Computational Biology. 17(3). e1008715–e1008715.
2.
Baker, Dannon, Marius van den Beek, Daniel Blankenberg, et al.. (2020). No more business as usual: Agile and effective responses to emerging pathogen threats require open data and open analytics. PLoS Pathogens. 16(8). e1008643–e1008643. 17 indexed citations
3.
Soiland‐Reyes, Stian, et al.. (2019). Sharing interoperable workflow provenance: A review of best practices and their practical application in CWLProv. GigaScience. 8(11). 41 indexed citations
4.
Soiland‐Reyes, Stian, et al.. (2018). Sharing interoperable workflow provenance: A review of best practices and their practical application in CWLProv. Research Explorer (The University of Manchester). 6 indexed citations
5.
Soiland‐Reyes, Stian, et al.. (2018). Cwlprov: Interoperable Retrospective Provenance Capture And Computational Analysis Sharing. Zenodo (CERN European Organization for Nuclear Research). 1 indexed citations
6.
Soiland‐Reyes, Stian, et al.. (2018). Cwlprov - Interoperable Retrospective Provenance Capture And Its Challenges. Zenodo (CERN European Organization for Nuclear Research). 7. 3 indexed citations
7.
Soiland‐Reyes, Stian, et al.. (2018). Capturing interoperable reproducible workflows with Common Workflow Language. Research Explorer (The University of Manchester). 1 indexed citations
8.
Nguyen‐Dumont, Tú, Zhi L. Teo, Fleur Hammet, et al.. (2018). Is RNASEL:p.Glu265* a modifier of early-onset breast cancer risk for carriers of high-risk mutations?. BMC Cancer. 18(1). 165–165. 7 indexed citations
9.
Lonie, Andrew, et al.. (2017). Investigating reproducibility and tracking provenance – A genomic workflow case study. BMC Bioinformatics. 18(1). 337–337. 42 indexed citations
10.
Young, Neil D., Pasi K. Korhonen, Ross S. Hall, et al.. (2016). Pipeline for the identification and classification of ion channels in parasitic flatworms. Parasites & Vectors. 9(1). 155–155. 4 indexed citations
11.
Sadedin, Simon, Harriet Dashnow, Paul A. James, et al.. (2015). Cpipe: a shared variant detection pipeline designed for diagnostic settings. Genome Medicine. 7(1). 54 indexed citations
12.
Afgan, Enis, Clare Sloggett, Nuwan Goonasekera, et al.. (2015). Genomics Virtual Laboratory: A Practical Bioinformatics Workbench for the Cloud. PLoS ONE. 10(10). e0140829–e0140829. 81 indexed citations
13.
Campos, Túlio de Lima, Neil D. Young, Pasi K. Korhonen, et al.. (2014). Identification of G protein-coupled receptors in Schistosoma haematobium and S. mansoni by comparative genomics. Parasites & Vectors. 7(1). 242–242. 34 indexed citations
14.
Pope, Bernard J., Tú Nguyen‐Dumont, Fabrice Odefrey, et al.. (2013). FAVR (Filtering and Annotation of Variants that are Rare): methods to facilitate the analysis of rare germline genetic variants from massively parallel sequencing datasets. BMC Bioinformatics. 14(1). 65–65. 6 indexed citations
15.
Miller, H. R., Sandy Clarke, Stephen E. Lane, et al.. (2009). Predicting customer behaviour: The University of Melbourne's KDD Cup report. Knowledge Discovery and Data Mining. 7. 45–55. 5 indexed citations
16.
Nath, Baikunth, et al.. (2009). A data clustering approach to discriminating impersonating devices in Wi‐Fi networks. Security and Communication Networks. 3(1). 44–57. 2 indexed citations
17.
Nath, Baikunth, et al.. (2008). An Optimal Sensor Architecture for Wi-Fi Intrusion Detection. 8(2). 2 indexed citations
18.
Cowan, Peter J., Trixie A. Shinkel, Nella Fisicaro, et al.. (2003). Targeting gene expression to endothelium in transgenic animals: a comparison of the human ICAM‐2, PECAM‐1 and endoglin promoters. Xenotransplantation. 10(3). 223–231. 25 indexed citations
19.
20.
Katerelos, Marina, Trixie A. Shinkel, Bryce J. W. van Denderen, et al.. (1996). THE ??-1,3-GALACTOSYLTRANSFERASE KNOCKOUT MOUSE. Transplantation. 61(1). 13–19. 250 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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