Jemma Wu

980 total citations
26 papers, 626 citations indexed

About

Jemma Wu is a scholar working on Molecular Biology, Spectroscopy and Artificial Intelligence. According to data from OpenAlex, Jemma Wu has authored 26 papers receiving a total of 626 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 11 papers in Spectroscopy and 7 papers in Artificial Intelligence. Recurrent topics in Jemma Wu's work include Advanced Proteomics Techniques and Applications (11 papers), Metabolomics and Mass Spectrometry Studies (7 papers) and Mass Spectrometry Techniques and Applications (7 papers). Jemma Wu is often cited by papers focused on Advanced Proteomics Techniques and Applications (11 papers), Metabolomics and Mass Spectrometry Studies (7 papers) and Mass Spectrometry Techniques and Applications (7 papers). Jemma Wu collaborates with scholars based in Australia, United States and Iran. Jemma Wu's co-authors include Dana Pascovici, Paul A. Haynes, Mark P. Molloy, Thiri Zaw, Mehdi Mirzaei, Yunqi Wu, Christoph Krisp, Karthik Shantharam Kamath, Xiaomin Song and Vivek Gupta and has published in prestigious journals such as Nature Communications, Bioinformatics and International Journal of Molecular Sciences.

In The Last Decade

Jemma Wu

26 papers receiving 621 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jemma Wu Australia 12 308 132 69 61 58 26 626
Trung Nghia Vu Sweden 16 579 1.9× 70 0.5× 44 0.6× 45 0.7× 185 3.2× 49 899
Paolo Romano Italy 16 398 1.3× 61 0.5× 12 0.2× 45 0.7× 76 1.3× 65 796
Yashu Liu China 12 306 1.0× 88 0.7× 26 0.4× 16 0.3× 51 0.9× 30 494
Julian Uszkoreit Germany 20 833 2.7× 470 3.6× 70 1.0× 38 0.6× 33 0.6× 38 1.1k
Andra Waagmeester Netherlands 13 862 2.8× 42 0.3× 62 0.9× 47 0.8× 140 2.4× 30 1.2k
Marco Brandizi United Kingdom 8 797 2.6× 49 0.4× 20 0.3× 96 1.6× 91 1.6× 18 1.1k
Robert Petryszak United Kingdom 9 973 3.2× 48 0.4× 32 0.5× 26 0.4× 176 3.0× 11 1.3k
Marta Iannuccelli Italy 12 1.2k 3.8× 102 0.8× 55 0.8× 10 0.2× 99 1.7× 20 1.4k
Dong Yue Canada 4 462 1.5× 23 0.2× 28 0.4× 22 0.4× 74 1.3× 6 695
Betsy Gregory United States 19 557 1.8× 307 2.3× 40 0.6× 11 0.2× 154 2.7× 30 1.4k

Countries citing papers authored by Jemma Wu

Since Specialization
Citations

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

Fields of papers citing papers by Jemma Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jemma Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Jemma Wu. A scholar is included among the top collaborators of Jemma Wu 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 Jemma Wu. Jemma Wu 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.
Borgel, Delphine, Dominique Lasne, Sylvain Renolleau, et al.. (2022). Pathophysiological pathway differences in children who present with COVID-19 ARDS compared to COVID -19 induced MIS-C. Nature Communications. 13(1). 2391–2391. 10 indexed citations
2.
Wu, Yunqi, Jemma Wu, Sara Hamzelou, et al.. (2022). Multiple Abiotic Stresses Applied Simultaneously Elicit Distinct Responses in Two Contrasting Rice Cultivars. International Journal of Molecular Sciences. 23(3). 1739–1739. 14 indexed citations
3.
Ahn, Seong Beom, Karthik Shantharam Kamath, Abidali Mohamedali, et al.. (2021). Use of a Recombinant Biomarker Protein DDA Library Increases DIA Coverage of Low Abundance Plasma Proteins. Journal of Proteome Research. 20(5). 2374–2389. 10 indexed citations
4.
Wu, Jemma, Dana Pascovici, Yunqi Wu, Adam K. Walker, & Mehdi Mirzaei. (2021). Application of WGCNA and PloGO2 in the Analysis of Complex Proteomic Data. Methods in molecular biology. 2426. 375–390. 2 indexed citations
5.
Wu, Jemma, et al.. (2020). OmixLitMiner: A Bioinformatics Tool for Prioritizing Biological Leads from ‘Omics Data Using Literature Retrieval and Data Mining. International Journal of Molecular Sciences. 21(4). 1374–1374. 5 indexed citations
6.
Wu, Jemma, Dana Pascovici, Yunqi Wu, Adam K. Walker, & Mehdi Mirzaei. (2020). Workflow for Rapidly Extracting Biological Insights from Complex, Multicondition Proteomics Experiments with WGCNA and PloGO2. Journal of Proteome Research. 19(7). 2898–2906. 11 indexed citations
7.
Deng, Liting, Chitra Joseph, Veer Bala Gupta, et al.. (2019). Amyloid β Induces Early Changes in the Ribosomal Machinery, Cytoskeletal Organization and Oxidative Phosphorylation in Retinal Photoreceptor Cells. Frontiers in Molecular Neuroscience. 12. 24–24. 27 indexed citations
8.
Mirzaei, Mehdi, Liting Deng, Nitin Chitranshi, et al.. (2019). Upregulation of Proteolytic Pathways and Altered Protein Biosynthesis Underlie Retinal Pathology in a Mouse Model of Alzheimer’s Disease. Molecular Neurobiology. 56(9). 6017–6034. 46 indexed citations
9.
Pascovici, Dana, Xiaomin Song, Jemma Wu, Thiri Zaw, & Mark P. Molloy. (2019). Practical Integration of Multi-Run iTRAQ Data. Methods in molecular biology. 1977. 199–215. 2 indexed citations
10.
Ahn, Seong Beom, Samridhi Sharma, Abidali Mohamedali, et al.. (2019). Potential early clinical stage colorectal cancer diagnosis using a proteomics blood test panel. Clinical Proteomics. 16(1). 34–34. 59 indexed citations
11.
Pascovici, Dana, Jemma Wu, Matthew J. McKay, et al.. (2018). Clinically Relevant Post-Translational Modification Analyses—Maturing Workflows and Bioinformatics Tools. International Journal of Molecular Sciences. 20(1). 16–16. 63 indexed citations
12.
Wu, Jemma, Dana Pascovici, Vera Ignjatović, et al.. (2017). Improving Protein Detection Confidence Using SWATH‐Mass Spectrometry with Large Peptide Reference Libraries. PROTEOMICS. 17(19). 6 indexed citations
13.
Wu, Jemma, Xiaomin Song, Dana Pascovici, et al.. (2016). SWATH Mass Spectrometry Performance Using Extended Peptide MS/MS Assay Libraries. Molecular & Cellular Proteomics. 15(7). 2501–2514. 84 indexed citations
14.
Mirzaei, Mehdi, Dana Pascovici, Jemma Wu, et al.. (2016). TMT One-Stop Shop: From Reliable Sample Preparation to Computational Analysis Platform. Methods in molecular biology. 1549. 45–66. 29 indexed citations
15.
Song, Xiaomin, Ardeshir Amirkhani, Jemma Wu, et al.. (2016). Analytical performance of nano‐LC‐SRM using nondepleted human plasma over an 18‐month period. PROTEOMICS. 16(15-16). 2118–2127. 6 indexed citations
16.
Liu, Xumin, et al.. (2011). Ev-LCS: A System for the Evolution of Long-Term Composed Services. IEEE Transactions on Services Computing. 6(1). 102–115. 27 indexed citations
17.
Wu, Jemma. (2011). A Framework for Learning Comprehensible Theories in XML Document Classification. IEEE Transactions on Knowledge and Data Engineering. 24(1). 1–14. 16 indexed citations
18.
Shu, Yanfeng, et al.. (2010). Semantic water data translation. 52–60. 1 indexed citations
19.
Tran, Nguyen Khoi, Michael Compton, Jemma Wu, & Rajeev Goré. (2010). Short paper: semantic sensor composition. 87–102. 4 indexed citations
20.
Wang, Hongbing, Li Li, Chen Wang, et al.. (2009). Logic-based verification for Web services composition with TLA. RMIT Research Repository (RMIT University Library). 1. 1–8. 4 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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