Fiona Browne

769 total citations
39 papers, 508 citations indexed

About

Fiona Browne is a scholar working on Molecular Biology, Computational Theory and Mathematics and Artificial Intelligence. According to data from OpenAlex, Fiona Browne has authored 39 papers receiving a total of 508 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Molecular Biology, 10 papers in Computational Theory and Mathematics and 8 papers in Artificial Intelligence. Recurrent topics in Fiona Browne's work include Bioinformatics and Genomic Networks (15 papers), Computational Drug Discovery Methods (9 papers) and Microbial Metabolic Engineering and Bioproduction (7 papers). Fiona Browne is often cited by papers focused on Bioinformatics and Genomic Networks (15 papers), Computational Drug Discovery Methods (9 papers) and Microbial Metabolic Engineering and Bioproduction (7 papers). Fiona Browne collaborates with scholars based in United Kingdom, Ireland and New Zealand. Fiona Browne's co-authors include Huiru Zheng, Haiying Wang, Gaye Lightbody, Francisco Azuaje, Valeriia Haberland, Jaine K. Blayney, Laura E. Taggart, Eileen E. Parkes, Hui Wang and Niall Rooney and has published in prestigious journals such as BMC Genomics, Knowledge-Based Systems and Pattern Recognition Letters.

In The Last Decade

Fiona Browne

39 papers receiving 490 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fiona Browne United Kingdom 13 266 76 76 56 34 39 508
Lars Ailo Bongo Norway 12 313 1.2× 67 0.9× 26 0.3× 50 0.9× 47 1.4× 40 855
Yuli Gao China 19 298 1.1× 228 3.0× 53 0.7× 44 0.8× 19 0.6× 50 1.2k
Stefan Grüner Germany 17 286 1.1× 66 0.9× 33 0.4× 95 1.7× 18 0.5× 103 916
Daniel Karlsson Sweden 14 361 1.4× 146 1.9× 93 1.2× 57 1.0× 23 0.7× 54 741
Deli Zhang China 13 162 0.6× 44 0.6× 92 1.2× 72 1.3× 43 1.3× 39 487
Awais Athar United Kingdom 10 479 1.8× 214 2.8× 32 0.4× 89 1.6× 51 1.5× 22 853
Bin Shao China 10 163 0.6× 76 1.0× 13 0.2× 43 0.8× 51 1.5× 32 342
Charalampos Moschopoulos Greece 8 377 1.4× 80 1.1× 113 1.5× 30 0.5× 25 0.7× 15 692
Dexter Pratt United States 17 659 2.5× 241 3.2× 147 1.9× 74 1.3× 52 1.5× 31 1.1k
Hugo López-Fernández Spain 13 235 0.9× 119 1.6× 13 0.2× 51 0.9× 26 0.8× 57 727

Countries citing papers authored by Fiona Browne

Since Specialization
Citations

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

Fields of papers citing papers by Fiona Browne

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fiona Browne

This figure shows the co-authorship network connecting the top 25 collaborators of Fiona Browne. A scholar is included among the top collaborators of Fiona Browne 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 Fiona Browne. Fiona Browne 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.
Bond, Raymond, et al.. (2022). Data-driven versus a domain-led approach to k-means clustering on an open heart failure dataset. International Journal of Data Science and Analytics. 15(1). 49–66. 12 indexed citations
2.
Browne, Fiona, et al.. (2021). Prediction of chemical compounds properties using a deep learning model. Neural Computing and Applications. 33(20). 13345–13366. 25 indexed citations
3.
Bi, Yaxin, et al.. (2019). Data mining and machine learning approaches for prediction modelling of schistosomiasis disease vectors. International Journal of Machine Learning and Cybernetics. 11(6). 1159–1178. 6 indexed citations
4.
Lightbody, Gaye, Valeriia Haberland, Fiona Browne, et al.. (2018). Review of applications of high-throughput sequencing in personalized medicine: barriers and facilitators of future progress in research and clinical application. Briefings in Bioinformatics. 20(5). 1795–1811. 108 indexed citations
5.
Wang, Haiying, et al.. (2018). PAAM-ML: A novel Phylogeny and Abundance aware Machine Learning Modelling Approach for Microbiome Classification. Ulster University Research Portal (Ulster University). 44–49. 6 indexed citations
6.
Palomares, Iván, Fiona Browne, & Peadar Davis. (2017). Multi-view fuzzy information fusion in collaborative filtering recommender systems: Application to the urban resilience domain. Data & Knowledge Engineering. 113. 64–80. 13 indexed citations
7.
Wang, Haiying, Huiru Zheng, Fiona Browne, et al.. (2017). Integrated metagenomic analysis of the rumen microbiome of cattle reveals key biological mechanisms associated with methane traits. Methods. 124. 108–119. 19 indexed citations
8.
Pantisano, Francesco, et al.. (2016). An Integrated Semantic Approach to Content Management in the Urban Resilience Domain. Ulster University Research Portal (Ulster University). 9. 323–333. 1 indexed citations
9.
Lightbody, Gaye, Fiona Browne, Huiru Zheng, Valeriia Haberland, & Jaine K. Blayney. (2016). The role of high performance, grid and cloud computing in high-throughput sequencing. Ulster University Research Portal (Ulster University). 51. 890–895. 1 indexed citations
10.
Browne, Fiona, Haiying Wang, Huiru Zheng, et al.. (2016). A network analysis of methane and feed conversion genes in the rumen microbial community. Ulster University Research Portal (Ulster University). 12. 1477–1484. 4 indexed citations
11.
Blayney, Jaine K., Valeriia Haberland, Gaye Lightbody, & Fiona Browne. (2015). Biomarker discovery, high performance and cloud computing: A comprehensive review. Research Portal (Queen's University Belfast). 26. 1514–1519. 3 indexed citations
12.
Wang, Haiying, Huiru Zheng, Fiona Browne, & Chaoyang Wang. (2014). Minimum dominating sets in cell cycle specific protein interaction networks. 7. 25–30. 5 indexed citations
13.
Browne, Fiona, Niall Rooney, Weiru Liu, et al.. (2013). Integrating textual analysis and evidential reasoning for decision making in Engineering design. Knowledge-Based Systems. 52. 165–175. 15 indexed citations
14.
Rooney, Niall, Hui Wang, & Fiona Browne. (2012). Applying Kernel Methods to Argumentation Mining.. Research Portal (Queen's University Belfast). 272–275. 28 indexed citations
15.
Browne, Fiona, Haiying Wang, Huiru Zheng, & Francisco Azuaje. (2010). A knowledge-driven probabilistic framework for the prediction of protein–protein interaction networks. Computers in Biology and Medicine. 40(3). 306–317. 12 indexed citations
16.
Wang, Haiying, Huiru Zheng, Fiona Browne, David H. Glass, & Francisco Azuaje. (2010). Integration of Gene Ontology-based similarities for supporting analysis of protein–protein interaction networks. Pattern Recognition Letters. 31(14). 2073–2082. 9 indexed citations
17.
Browne, Fiona, Haiying Wang, Huiru Zheng, & Francisco Azuaje. (2009). GRIP: A web-based system for constructing Gold Standard datasets for protein-protein interaction prediction. PubMed. 4(1). 2–2. 21 indexed citations
18.
Browne, Fiona, Huiru Zheng, Haiying Wang, & Francisco Azuaje. (2009). An Integrative Bayesian Approach To Supporting The Prediction Of Protein-Protein Interactions: A Case Study In Human Heart Failure. Zenodo (CERN European Organization for Nuclear Research). 3(5). 313–319. 3 indexed citations
19.
Browne, Fiona, Haiying Wang, Huiru Zheng, & Francisco Azuaje. (2008). Reassessing the limit of data integration for the prediction of protein-protein interactions in Saccharomyces cerevisiae. 14. 128–135. 2 indexed citations
20.
Browne, Fiona, Haiying Wang, Huiru Zheng, & Francisco Azuaje. (2006). An assessment of machine and statistical learning approaches to inferring networks of protein-protein interactions. Berichte aus der medizinischen Informatik und Bioinformatik/Journal of integrative bioinformatics. 3(2). 230–246. 5 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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