Paul M. Watt

2.9k total citations
50 papers, 2.4k citations indexed

About

Paul M. Watt is a scholar working on Molecular Biology, Oncology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Paul M. Watt has authored 50 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Molecular Biology, 9 papers in Oncology and 5 papers in Cellular and Molecular Neuroscience. Recurrent topics in Paul M. Watt's work include Cancer-related gene regulation (7 papers), DNA Repair Mechanisms (6 papers) and RNA Interference and Gene Delivery (6 papers). Paul M. Watt is often cited by papers focused on Cancer-related gene regulation (7 papers), DNA Repair Mechanisms (6 papers) and RNA Interference and Gene Delivery (6 papers). Paul M. Watt collaborates with scholars based in Australia, United Kingdom and United States. Paul M. Watt's co-authors include Ian D. Hickson, Rhona H. Borts, Edward J. Louis, Greg White, Patrick G. Holt, Barbara J. Holt, Ursula R. Kees, Paul R. Caron, R.M. Hopkins and J C Wang and has published in prestigious journals such as Cell, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Paul M. Watt

50 papers receiving 2.3k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Paul M. Watt Australia 20 1.9k 326 245 239 235 50 2.4k
Vladimir Prassolov Russia 26 1.4k 0.8× 314 1.0× 285 1.2× 161 0.7× 230 1.0× 143 2.1k
Philip R. Gafken United States 29 2.7k 1.5× 257 0.8× 236 1.0× 219 0.9× 242 1.0× 50 3.4k
Sharona Elgavish Israel 19 934 0.5× 137 0.4× 305 1.2× 147 0.6× 225 1.0× 40 1.6k
Maria A. Kukuruzinska United States 30 1.9k 1.0× 235 0.7× 187 0.8× 161 0.7× 358 1.5× 64 2.5k
Nahum Sonenberg Canada 19 2.6k 1.4× 150 0.5× 118 0.5× 181 0.8× 239 1.0× 24 3.0k
Ping Yuan China 25 1.5k 0.8× 213 0.7× 292 1.2× 106 0.4× 131 0.6× 57 2.3k
Emma Warbrick United Kingdom 25 2.1k 1.1× 593 1.8× 179 0.7× 155 0.6× 206 0.9× 53 2.7k
Robert A. Marciniak United States 20 1.8k 1.0× 224 0.7× 226 0.9× 174 0.7× 254 1.1× 28 2.4k
Koichiro Kishi Japan 27 2.0k 1.1× 187 0.6× 169 0.7× 120 0.5× 331 1.4× 162 2.8k
Linda Sealy United States 31 2.5k 1.4× 584 1.8× 336 1.4× 212 0.9× 354 1.5× 56 3.3k

Countries citing papers authored by Paul M. Watt

Since Specialization
Citations

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

Fields of papers citing papers by Paul M. Watt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paul M. Watt. 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 Paul M. Watt. The network helps show where Paul M. Watt may publish in the future.

Co-authorship network of co-authors of Paul M. Watt

This figure shows the co-authorship network connecting the top 25 collaborators of Paul M. Watt. A scholar is included among the top collaborators of Paul M. Watt 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 Paul M. Watt. Paul M. Watt 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.
Wylie, Ben, et al.. (2021). Targeting Cross-Presentation as a Route to Improve the Efficiency of Peptide-Based Cancer Vaccines. Cancers. 13(24). 6189–6189. 10 indexed citations
2.
Watt, Paul M., Vikrant Kumar, Kavitha Bharatham, et al.. (2021). Target identification for small-molecule discovery in the FOXO3a tumor-suppressor pathway using a biodiverse peptide library. Cell chemical biology. 28(11). 1602–1615.e9. 8 indexed citations
3.
Yang, Rongchang, T. P. Armstrong, R.M. Hopkins, et al.. (2014). Target validation of the inosine monophosphate dehydrogenase (IMPDH) gene in Cryptosporidium using Phylomer® peptides. Experimental Parasitology. 148. 40–48. 17 indexed citations
4.
5.
Ngoei, Kevin R. W., et al.. (2013). A novel retro-inverso peptide is a preferential JNK substrate-competitive inhibitor. The International Journal of Biochemistry & Cell Biology. 45(8). 1939–1950. 10 indexed citations
6.
Watt, Paul M., et al.. (2012). The Construction of “Phylomer” Peptide Libraries as a Rich Source of Potent Inhibitors of Protein/Protein Interactions. Methods in molecular biology. 899. 43–60. 6 indexed citations
7.
Watt, Paul M., et al.. (2011). Lack of Neuroprotection of Inhibitory Peptides Targeting Jun/JNK after Transient Focal Cerebral Ischemia in Spontaneously Hypertensive Rats. Journal of Cerebral Blood Flow & Metabolism. 31(12). e1–e8. 13 indexed citations
8.
Meloni, Bruno P., Jane L. Cross, Anthony J. Bakker, et al.. (2009). AP‐1 inhibitory peptides are neuroprotective following acute glutamate excitotoxicity in primary cortical neuronal cultures. Journal of Neurochemistry. 112(1). 258–270. 34 indexed citations
9.
Gottardo, Nicholas G., Jette Ford, D.N. D’Souza, et al.. (2009). MEIS proteins as partners of the TLX1/HOX11 oncoprotein. Leukemia Research. 34(3). 358–363. 8 indexed citations
10.
Ryan, Una, Paul M. Watt, R.M. Hopkins, et al.. (2008). Pyrrhocoricin as a potential drug delivery vehicle for Cryptosporidium parvum. Experimental Parasitology. 119(2). 301–303. 7 indexed citations
11.
Barr, Renae K., R.M. Hopkins, Paul M. Watt, & Marie A. Bogoyevitch. (2004). Reverse Two-hybrid Screening Identifies Residues of JNK Required for Interaction with the Kinase Interaction Motif of JNK-interacting Protein-1. Journal of Biological Chemistry. 279(41). 43178–43189. 23 indexed citations
12.
Gottardo, Nicholas G., et al.. (2004). Deletion of one copy of the p16INK4A tumor suppressor gene is implicated as a predisposing factor in pediatric leukemia. Biochemical and Biophysical Research Communications. 318(4). 852–855. 4 indexed citations
13.
Watt, Paul M., Katrin Hoffmann, Wayne K. Greene, et al.. (2003). Specific alternative HOX11 transcripts are expressed in paediatric neural tumours and T-cell acute lymphoblastic leukaemia. Gene. 323. 89–99. 7 indexed citations
14.
15.
Wang, Xinwang, Paul M. Watt, Rhona H. Borts, Edward J. Louis, & Ian D. Hickson. (1999). The topoisomerase II-associated protein, Pat1p, is required for maintenance of rDNA locus stability in Saccharomyces cerevisiae. Molecular and General Genetics MGG. 261(4-5). 831–840. 14 indexed citations
16.
Watt, Paul M., et al.. (1999). Sequence of 10q24 locus surrounding the HOX11 oncogene reveals a new gene HUG1 expressed in a T-ALL cell line. Gene. 234(1). 169–176. 3 indexed citations
17.
Cockell, Moira, Hubert Renauld, Paul M. Watt, & Susan M. Gasser. (1998). Sif2p interacts with the Sir4p amino-terminal domain and antagonizes telomeric silencing in yeast. Current Biology. 8(13). 787–S2. 32 indexed citations
18.
Watt, Paul M. & Ian D. Hickson. (1996). Genome stability: Failure to unwind causes cancer. Current Biology. 6(3). 265–267. 31 indexed citations
19.
Caron, Paul R., Paul M. Watt, & James C. Wang. (1994). The C-Terminal Domain of Saccharomyces cerevisiae DNA Topoisomerase II. Molecular and Cellular Biology. 14(5). 3197–3207. 18 indexed citations
20.
Lamb, Peter, Paul M. Watt, & Nicholas Proudfoot. (1989). Negative regulation of the human embryonic globin genes zeta and epsilon.. PubMed. 316A. 269–77. 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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