Robert Pollack

142 papers receiving 4.7k citations

Robert Pollack's Hit Papers

Tumorigenicity of virus-transformed cells in nude mice is correlated specifically with anchorage independent growth in vitro. 1975 · 678 citations
6780+17+34Years since publication200400600

Peers

Robert Pollack
Comparison fields: 5 of 166
  • Cell Biology 986
  • Algebra and Number Theory 240
  • Oncology 1.1k
  • Genetics 1.2k
  • Geometry and Topology 394
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Nicholas Proudfoot United Kingdom
Akira Hattori Japan
Hidetoshi Tahara Japan
Hironobu Kimura Japan
Toshihiro Yamaguchi Japan
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Citations per year

Countries citing papers authored by Robert Pollack

Since Specialization
Citations

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

Fields of papers citing papers by Robert Pollack

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Robert Pollack, 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 Robert Pollack Line = papers co-authored together Robert Pollack links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 155 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Tumorigenicity of virus-transformed cells in nude mice is correlated specifically with anchorage independent growth in vitro.
Hit paper breakdown →
1975678
2 1975399
3 1974245
4 1968225
5 1975213
6 1975206
7 1980165
8 1980147
9 1975144
10 1974142
11 1979131
12 1978121
13 1969115
14 197089
15 197388
16 199982
17 200578
18 197774
19 199274
20 197473

About Robert Pollack

Robert Pollack is a scholar working on Molecular Biology, Genetics, Oncology, Geometry and Topology and Mathematical Physics, having authored 155 papers that have together received 5.5k indexed citations. Recurring topics across this work include Virus-based gene therapy research (25 papers), Algebraic Geometry and Number Theory (21 papers), Advanced Algebra and Geometry (17 papers), Polyomavirus and related diseases (15 papers), Logic, programming, and type systems (12 papers), Logic, Reasoning, and Knowledge (11 papers), Bacteriophages and microbial interactions (9 papers) and RNA Interference and Gene Delivery (8 papers). The work is most often cited by research in Cell Biology (986 citations), Algebra and Number Theory (240 citations), Oncology (1.1k citations), Genetics (1.2k citations) and Geometry and Topology (394 citations). Robert Pollack has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include R Risser, K. Weber, S. Shin, Victoria H. Freedman, Daniel B. Rifkin, Arthur Vogel, Robert D. Goldman, Mary Osborn, Bettie M. Steinberg and H Green. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of Virology, Molecular and Cellular Biology, Journal of Cellular Physiology and Science.

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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