Michael J. Wise

4.3k total citations · 1 hit paper
111 papers, 3.0k citations indexed

About

Michael J. Wise is a scholar working on Molecular Biology, Artificial Intelligence and Surgery. According to data from OpenAlex, Michael J. Wise has authored 111 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Molecular Biology, 17 papers in Artificial Intelligence and 12 papers in Surgery. Recurrent topics in Michael J. Wise's work include Genomics and Phylogenetic Studies (19 papers), RNA and protein synthesis mechanisms (11 papers) and Helicobacter pylori-related gastroenterology studies (10 papers). Michael J. Wise is often cited by papers focused on Genomics and Phylogenetic Studies (19 papers), RNA and protein synthesis mechanisms (11 papers) and Helicobacter pylori-related gastroenterology studies (10 papers). Michael J. Wise collaborates with scholars based in Australia, United Kingdom and United States. Michael J. Wise's co-authors include Alan Tunnacliffe, Liang Wang, John M. Kenney, Fritz Vollrath, David P. Knight, Amitava Datta, Sohini Chakrabortee, Simon Easteal, Tanya Golubchik and Lars S. Jermiin and has published in prestigious journals such as Nucleic Acids Research, Journal of Biological Chemistry and Bioinformatics.

In The Last Decade

Michael J. Wise

100 papers receiving 2.9k citations

Hit Papers

The continuing conundrum of the LEA proteins 2007 2026 2013 2019 2007 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael J. Wise Australia 25 1.2k 912 308 294 284 111 3.0k
Florentino Fdez‐Riverola Spain 26 940 0.8× 252 0.3× 383 1.2× 144 0.5× 730 2.6× 185 2.9k
Mark D. Wilkinson Spain 28 1.3k 1.1× 534 0.6× 652 2.1× 121 0.4× 483 1.7× 111 3.2k
Paul Horton Japan 26 6.0k 4.9× 2.6k 2.9× 133 0.4× 167 0.6× 311 1.1× 92 8.8k
Rosane Minghim Brazil 25 919 0.7× 290 0.3× 167 0.5× 58 0.2× 550 1.9× 100 3.4k
Marco Roos Netherlands 24 1.0k 0.8× 191 0.2× 487 1.6× 309 1.1× 249 0.9× 102 2.1k
Joshua W. K. Ho Australia 36 2.6k 2.1× 127 0.1× 187 0.6× 50 0.2× 357 1.3× 141 4.4k
Philip Turner United Kingdom 32 1.2k 1.0× 747 0.8× 146 0.5× 128 0.4× 34 0.1× 142 3.4k
Ulrich Bodenhofer Austria 23 993 0.8× 187 0.2× 94 0.3× 40 0.1× 555 2.0× 66 2.7k
James Heather United Kingdom 19 766 0.6× 95 0.1× 192 0.6× 25 0.1× 294 1.0× 57 1.9k
Stéphane Robin France 23 690 0.6× 567 0.6× 16 0.1× 83 0.3× 274 1.0× 84 2.2k

Countries citing papers authored by Michael J. Wise

Since Specialization
Citations

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

Fields of papers citing papers by Michael J. Wise

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael J. Wise. 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 Michael J. Wise. The network helps show where Michael J. Wise may publish in the future.

Co-authorship network of co-authors of Michael J. Wise

This figure shows the co-authorship network connecting the top 25 collaborators of Michael J. Wise. A scholar is included among the top collaborators of Michael J. Wise 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 Michael J. Wise. Michael J. Wise 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.
Wise, Michael J., et al.. (2022). Deep learning models for RNA secondary structure prediction (probably) do not generalize across families. Bioinformatics. 38(16). 3892–3899. 40 indexed citations
2.
Akhtar, Naveed, et al.. (2021). Annotation Tool and Urban Dataset for 3D Point Cloud Semantic Segmentation. IEEE Access. 9. 35984–35996. 15 indexed citations
3.
Tay, Chin Yen, Michael J. Wise, & Barry J. Marshall. (2021). Helicobacteriology update. Microbiology Australia. 42(2). 92–95. 1 indexed citations
4.
Ghori, Noor-Ul-Huda, Michael J. Wise, & Andrew S. Whiteley. (2021). Temporal Microbial Community Dynamics Within a Unique Acid Saline Lake. Frontiers in Microbiology. 12. 649594–649594. 4 indexed citations
5.
Speers, David, et al.. (2020). Meningococcal Disease-Associated Prophage-Like Elements Are Present in Neisseria gonorrhoeae and Some Commensal Neisseria Species. Genome Biology and Evolution. 12(2). 3938–3950. 11 indexed citations
6.
Wang, Liang, et al.. (2019). Systematic Analysis of Metabolic Pathway Distributions of Bacterial Energy Reserves. G3 Genes Genomes Genetics. 9(8). 2489–2496. 9 indexed citations
7.
Wise, Michael J., Binit Lamichhane, & K. Mary Webberley. (2019). A Longitudinal, Population-Level, Big-Data Study of Helicobacter pylori-Related Disease across Western Australia. Journal of Clinical Medicine. 8(11). 1821–1821. 8 indexed citations
8.
Wang, Liang, Qinghua Liu, Xinle Tan, et al.. (2019). Molecular Structure of Glycogen in Escherichia coli. Biomacromolecules. 20(7). 2821–2829. 39 indexed citations
9.
Marshall, Barry J., et al.. (2019). <p>Structural, biomechanical and hemodynamic assessment of the bladder wall in healthy subjects</p>. Research and Reports in Urology. Volume 11. 233–245. 10 indexed citations
10.
Wise, Michael J., et al.. (2015). Novel Moraxella catarrhalis prophages display hyperconserved non-structural genes despite their genomic diversity. BMC Genomics. 16(1). 860–860. 14 indexed citations
11.
Wise, Michael J.. (2013). Mean Protein Evolutionary Distance: A Method for Comparative Protein Evolution and Its Application. PLoS ONE. 8(4). e61276–e61276. 4 indexed citations
12.
Chakrabortee, Sohini, Rashmi Tripathi, Matthew Watson, et al.. (2011). Intrinsically disordered proteins as molecular shields. Molecular BioSystems. 8(1). 210–219. 157 indexed citations
13.
Higa, Arisa, A. Mulot, Frédéric Delom, et al.. (2011). Role of Pro-oncogenic Protein Disulfide Isomerase (PDI) Family Member Anterior Gradient 2 (AGR2) in the Control of Endoplasmic Reticulum Homeostasis. Journal of Biological Chemistry. 286(52). 44855–44868. 101 indexed citations
14.
Sperschneider, Jana, Amitava Datta, & Michael J. Wise. (2010). Heuristic RNA pseudoknot prediction including intramolecular kissing hairpins. RNA. 17(1). 27–38. 38 indexed citations
15.
Wise, Michael J., et al.. (2007). Herbivory as an agent of natural selection for floral-sex ratio in horsenettle (Solanum carolinense). Evolutionary ecology research. 9(8). 1319–1328. 12 indexed citations
16.
Benita, Yair, Michael J. Wise, M.C. Lok, Ian Humphery‐Smith, & Ronald S. Oosting. (2006). Analysis of High Throughput Protein Expression in Escherichia coli. Molecular & Cellular Proteomics. 5(9). 1567–1580. 11 indexed citations
17.
Wise, Michael J.. (1996). YAP3. ACM SIGCSE Bulletin. 28(1). 130–134. 41 indexed citations
18.
Wise, Michael J.. (1996). YAP3. 130–134. 220 indexed citations
19.
Wise, Michael J.. (1986). Prolog Multiprocessors. Prentice-Hall, Inc eBooks. 14 indexed citations
20.
Wise, Michael J. & David Powers. (1984). Indexing Prolog Clauses via Superimposed Code Words and Filed Encoded Words.. 203–210. 3 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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