Julie Thompson

163.4k total citations · 8 hit papers
124 papers, 138.9k citations indexed

About

Julie Thompson is a scholar working on Molecular Biology, Genetics and Spectroscopy. According to data from OpenAlex, Julie Thompson has authored 124 papers receiving a total of 138.9k indexed citations (citations by other indexed papers that have themselves been cited), including 85 papers in Molecular Biology, 16 papers in Genetics and 8 papers in Spectroscopy. Recurrent topics in Julie Thompson's work include Genomics and Phylogenetic Studies (60 papers), RNA and protein synthesis mechanisms (29 papers) and Machine Learning in Bioinformatics (25 papers). Julie Thompson is often cited by papers focused on Genomics and Phylogenetic Studies (60 papers), RNA and protein synthesis mechanisms (29 papers) and Machine Learning in Bioinformatics (25 papers). Julie Thompson collaborates with scholars based in France, Germany and United States. Julie Thompson's co-authors include Toby J. Gibson, Desmond G. Higgins, Hamish McWilliam, Rodrigo López, Andreas Wilm, Gordon Blackshields, Iain M. Wallace, F. Valentin, Chenna Ramu and Paul McGettigan and has published in prestigious journals such as Nucleic Acids Research, Circulation and SHILAP Revista de lepidopterología.

In The Last Decade

Julie Thompson

120 papers receiving 134.9k citations

Hit Papers

CLUSTAL W: improving the sensitivity of progressive multi... 1994 2026 2004 2015 1994 1997 2007 2011 1998 10.0k 20.0k 30.0k 40.0k 50.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice
    1994 56.8k citations Julie Thompson, Desmond G. Higgins et al. Nucleic Acids Research profile →
  2. The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools
    1997 35.7k citations Julie Thompson Nucleic Acids Research profile →
  3. Clustal W and Clustal X version 2.0
    2007 23.8k citations Gordon Blackshields, Nigel P. Brown et al. Bioinformatics profile →
  4. Fast, scalable generation of high‐quality protein multiple sequence alignments using Clustal Omega
    2011 11.2k citations Fabian Sievers, Andreas Wilm et al. Molecular Systems Biology profile →
  5. Multiple sequence alignment with Clustal X
    1998 2.4k citations Julie Thompson, Desmond G. Higgins et al. Trends in Biochemical Sciences profile →
  6. Multiple Sequence Alignment Using ClustalW and ClustalX
    2002 2.3k citations Julie Thompson, Toby J. Gibson et al. profile →
  7. [22] Using CLUSTAL for multiple sequence alignments
    1996 1.4k citations Desmond G. Higgins, Julie Thompson et al. profile →
  8. A comprehensive comparison of multiple sequence alignment programs
    1999 554 citations Julie Thompson, Frédéric Plewniak et al. Nucleic Acids Research profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Julie Thompson France 38 74.2k 34.3k 23.6k 19.6k 11.7k 124 138.9k
Desmond G. Higgins Ireland 56 67.4k 0.9× 26.7k 0.8× 17.6k 0.7× 17.1k 0.9× 8.1k 0.7× 132 120.5k
Stephen F. Altschul United States 42 95.6k 1.3× 34.8k 1.0× 24.4k 1.0× 19.4k 1.0× 7.0k 0.6× 70 156.2k
Toby J. Gibson Germany 69 65.8k 0.9× 24.7k 0.7× 16.2k 0.7× 16.2k 0.8× 7.3k 0.6× 148 116.5k
Glen Stecher United States 12 62.4k 0.8× 47.6k 1.4× 30.8k 1.3× 22.1k 1.1× 17.9k 1.5× 14 153.5k
Steven L. Salzberg United States 96 110.2k 1.5× 46.6k 1.4× 20.8k 0.9× 24.8k 1.3× 6.7k 0.6× 244 185.4k
David J. Lipman United States 50 66.4k 0.9× 22.8k 0.7× 18.0k 0.8× 15.0k 0.8× 5.2k 0.4× 80 112.8k
Mark A. Bradford United States 72 109.9k 1.5× 57.1k 1.7× 21.1k 0.9× 14.9k 0.8× 7.7k 0.7× 229 239.7k
M Nei United States 47 67.7k 0.9× 42.3k 1.2× 31.7k 1.3× 31.5k 1.6× 16.0k 1.4× 69 152.8k
Koichiro Tamura Japan 34 82.5k 1.1× 60.9k 1.8× 41.3k 1.7× 32.5k 1.7× 23.8k 2.0× 76 206.1k
Heng Li China 59 68.3k 0.9× 27.2k 0.8× 12.9k 0.5× 35.9k 1.8× 6.3k 0.5× 289 122.6k

Countries citing papers authored by Julie Thompson

Since Specialization
Citations

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

Fields of papers citing papers by Julie Thompson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Julie Thompson

This figure shows the co-authorship network connecting the top 25 collaborators of Julie Thompson. A scholar is included among the top collaborators of Julie Thompson 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 Julie Thompson. Julie Thompson 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.
Chennen, Kirsley, et al.. (2024). Graph-based machine learning model for weight prediction in protein–protein networks. BMC Bioinformatics. 25(1). 349–349. 1 indexed citations
2.
Mayer, Claudine, et al.. (2023). CeGAL: Redefining a Widespread Fungal-Specific Transcription Factor Family Using an In Silico Error-Tracking Approach. Journal of Fungi. 9(4). 424–424. 4 indexed citations
3.
Kress, Arnaud, Olivier Poch, Odile Lecompte, & Julie Thompson. (2023). Real or fake? Measuring the impact of protein annotation errors on estimates of domain gain and loss events. SHILAP Revista de lepidopterología. 3. 1178926–1178926. 8 indexed citations
4.
Reiss, David J., Christine Kretz, Wolfgang Raffelsberger, et al.. (2021). Multi-omics comparisons of different forms of centronuclear myopathies and the effects of several therapeutic strategies. Molecular Therapy. 29(8). 2514–2534. 13 indexed citations
5.
Hall, Jonathan, et al.. (2021). Environmental Justice and the Mississippi Poultry Farming Industry. Environmental Justice. 15(4). 235–245. 1 indexed citations
6.
Chennen, Kirsley, Xavière Lornage, Arnaud Kress, et al.. (2020). MISTIC: A prediction tool to reveal disease-relevant deleterious missense variants. PLoS ONE. 15(7). e0236962–e0236962. 23 indexed citations
7.
Allot, Alexis, Kirsley Chennen, Yannis Nevers, et al.. (2017). MyGeneFriends: A Social Network Linking Genes, Genetic Diseases, and Researchers. Journal of Medical Internet Research. 19(6). e212–e212. 5 indexed citations
8.
Lornage, Xavière, Edoardo Malfatti, Raphaël Schneider, et al.. (2017). Recessive MYPN mutations cause cap myopathy with occasional nemaline rods. Annals of Neurology. 81(3). 467–473. 22 indexed citations
9.
Poch, Olivier, et al.. (2014). SIBIS: a Bayesian model for inconsistent protein sequence estimation. Bioinformatics. 30(17). 2432–2439. 6 indexed citations
10.
Thompson, Julie, et al.. (2013). How Long Is Too Long? Recovery Time of Outpatients With Sleep Apnea After Procedural Sedation. Gastroenterology Nursing. 36(4). 260–264. 3 indexed citations
11.
Goetze, Stephan, Pier D. Lambiase, Richard J. Schilling, et al.. (2012). Abstract 9309: Daily Respiratory Rate Trends are Significantly Elevated Prior to HF Admissions. Circulation. 126(suppl_21). 1 indexed citations
12.
Linard, Benjamin, Xavier Brochet, Raymond Ripp, et al.. (2012). Functional insights into the core-TFIIH from a comparative survey. Genomics. 101(3). 178–186. 14 indexed citations
13.
Sievers, Fabian, Andreas Wilm, Toby J. Gibson, et al.. (2011). Fast, scalable generation of high‐quality protein multiple sequence alignments using Clustal Omega. Molecular Systems Biology. 7(1). 539–539. 11202 indexed citations breakdown →
14.
Poch, Olivier, et al.. (2010). Issues in bioinformatics benchmarking: the case study of multiple sequence alignment. Nucleic Acids Research. 38(21). 7353–7363. 49 indexed citations
15.
Thompson, Julie, Christine Schaeffer‐Reiss, & Marius Ueffing. (2008). Functional Proteomics. Methods in molecular biology. 484. v–vii. 13 indexed citations
16.
Blackshields, Gordon, Nigel P. Brown, Chenna Ramu, et al.. (2007). Clustal W and Clustal X version 2.0. Bioinformatics. 23(21). 2947–2948. 23845 indexed citations breakdown →
17.
Chalmel, Frédéric, Aurélie Lardenois, Julie Thompson, et al.. (2005). GOAnno: GO annotation based on multiple alignment. Computer applications in the biosciences. 21(9). 2095–2096. 26 indexed citations
18.
Thompson, Julie, Frédéric Plewniak, & Olivier Poch. (1999). A comprehensive comparison of multiple sequence alignment programs. Nucleic Acids Research. 27(13). 2682–2690. 554 indexed citations breakdown →
19.
Thompson, Julie, Desmond G. Higgins, & Toby J. Gibson. (1994). CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Research. 22(22). 4673–4680. 56835 indexed citations breakdown →
20.
Gibson, Toby J., Peter M. Rice, Julie Thompson, & Jaap Heringa. (1993). KH domains within the FMR1 sequence suggest that fragile X syndrome stems from a defect in RNA metabolism. Trends in Biochemical Sciences. 18(9). 331–333. 63 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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