Frank M. Schabel

1.6k citations
32 papers · 1.2k indexed · h-index 17
Topics
Computational Drug Discovery Methods (5 papers)HIV/AIDS drug development and treatment (5 papers)Cancer therapeutics and mechanisms (4 papers)
Partner nations
United States

In The Last Decade

Frank M. Schabel

31 papers receiving 1.0k citations

Peers

Frank M. Schabel
Comparison fields: 5 of 94
  • Molecular Biology 474
  • Oncology 350
  • Organic Chemistry 196
  • Epidemiology 162
  • Infectious Diseases 148
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Citations per field
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Countries citing papers authored by Frank M. Schabel

Since Specialization
Citations

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

Fields of papers citing papers by Frank M. Schabel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Frank M. Schabel

This figure shows the co-authorship network connecting the top 25 collaborators of Frank M. Schabel. A scholar is included among the top collaborators of Frank M. Schabel 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 Frank M. Schabel. Frank M. Schabel 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
#WorkIndexed citations
1 66
2 13
3 35
4 65
5 61
6 5
7 17
8 143
9 23
10 10
11 6
12 70
13
Experimental evaluation of potential anticancer agents XV. On the relative rates of growth and host kill of "single" leukemia cells that survive in vivo cytoxan therapy.
8
14 4
15 69
16
Experimental Evaluation of Potential Anticancer Agents: XII. Quantitative Drug Response of the SA180, CA755, and Leukemia L1210 Systems to a “Standard List” of “Active” and “Inactive” Agents
10
17
Experimental evaluation of potential anticancer agents. IX. The ribonucleosides and ribonucleotides of two purine antagonists.
16
18
Experimental evaluation of potential anticancer agents. IV. Host weight loss as it relates to false positives in drug evaluation.
8
19 32
20 10

About Frank M. Schabel

Frank M. Schabel is a scholar working on Virology, Infectious Diseases and Statistics and Probability, having authored 32 papers that have together received 1.2k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (5 papers), HIV/AIDS drug development and treatment (5 papers) and Cancer therapeutics and mechanisms (4 papers). The work is most often cited by research in Physiology (70 citations), Oncology (350 citations) and Cancer Research (141 citations). Frank M. Schabel has collaborated with scholars based in United States. Frequent co-authors include Glen J. Dixon, R W Brockman, John A. Montgomery, Stephen K. Carter, Thomas P. Johnston, Lawrence E. Broder, Robert W. Sidwell, Daniel P. Griswold, William M. Shannon and Thomas H. Corbett. Their work appears in journals such as Nature, Science and JNCI Journal of the National Cancer Institute.

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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