P T Mora

960 citations
33 papers · 802 · h-index 15

Impact in

  • Cell Biology top 10%
    • Proteoglycans and glycosaminoglycans research
  • Oncology top 10%
    • Polyomavirus and related diseases
    • Cancer-related Molecular Pathways

Papers in

    • RNA Interference and Gene Delivery 6
    • Glycosylation and Glycoproteins Research 5
    • Polyomavirus and related diseases 7

P T Mora

32 papers receiving 696 citations

Peers

P T Mora
Comparison fields: 5 of 83
  • Cell Biology 187
  • Oncology 262
  • Immunology and Allergy 43
  • Genetics 205
  • Biotechnology 58
Replace T Patschinsky with:
T Patschinsky Germany
Maureen O. Weeks United States
A R Goldberg United States
Kinichiro Oda Japan
K Segawa Japan
Timothy M. Harrison United Kingdom
Simone Grandchamp France
Edward G. Bernstine United States
Chantal Crémisi France
Gerd Zettlmeißl Germany
P T Mora relative to T Patschinsky Germany T Patschinsky's profile →
Citations per field
00.5×1.5×2.3×
T Patschinsky · 1×
Citations per year

Countries citing papers authored by P T Mora

Since Specialization
Citations

This map shows the geographic impact of P T Mora'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 P T Mora with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites P T Mora more than expected).

Fields of papers citing papers by P T Mora

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P T Mora. 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 P T Mora. The network helps show where P T Mora may publish in the future.

Co-authors

The 25 scholars most cited alongside P T Mora, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with P T Mora Line = papers co-authored together P T Mora links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1979119
2 1981113
3 197976
4 197871
5 198241
6 198138
7 197332
8 197731
9 197728
10 197526
11 196623
12 197020
13 195919
14 196318
15 198214
16 195814
17 196614
18 195712
19 197412
20 196112

About P T Mora

P T Mora is a scholar working on Molecular Biology, Oncology, Ecology, Genetics and Immunology, having authored 33 papers that have together received 802 indexed citations. Recurring topics across this work include Polyomavirus and related diseases (7 papers), RNA Interference and Gene Delivery (6 papers), Bacteriophages and microbial interactions (6 papers), Virus-based gene therapy research (6 papers), Glycosylation and Glycoproteins Research (5 papers), Monoclonal and Polyclonal Antibodies Research (4 papers), Immunotherapy and Immune Responses (4 papers) and Proteoglycans and glycosaminoglycans research (4 papers). The work is most often cited by research in Cell Biology (187 citations), Oncology (262 citations), Immunology and Allergy (43 citations), Genetics (205 citations) and Biotechnology (58 citations). P T Mora has collaborated with scholars based in United States, Taiwan and India. Frequent co-authors include David J. Winterbourne, Vivian W. McFarland, Chung-Ming Chang, Daniel T. Simmons, Miguel Martı́n, Samuel W. Luborsky, R G Martin, Krish Chandrasekaran, M. J. Shear and David M. Livingston. Their work appears in journals such as Journal of Virology, Nature, Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Molecular and Cellular Biology.

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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