Lee T. Bacheler

4.9k citations
82 papers · 3.8k indexed · 1 hit paper · h-index 31
Topics
HIV Research and Treatment (67 papers)HIV/AIDS drug development and treatment (67 papers)HIV/AIDS Research and Interventions (26 papers)

In The Last Decade

Lee T. Bacheler

81 papers receiving 3.6k citations

Hit Papers

Rational Design of Potent, Bioavailable, Nonpeptide Cycli...19942026200420151994200400600

Peers

Lee T. Bacheler
Comparison fields: 5 of 111
  • Infectious Diseases 2.1k
  • Virology 2.1k
  • Molecular Biology 1.2k
  • Organic Chemistry 1.0k
  • Epidemiology 336
Replace Daniel W. Norbeck with:
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Lee T. Bacheler relative to Daniel W. Norbeck United States Daniel W. Norbeck's profile →
Citations per field
00.5×3.7×
Daniel W. Norbeck · 1×
Citations per year

Countries citing papers authored by Lee T. Bacheler

Since Specialization
Citations

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

Fields of papers citing papers by Lee T. Bacheler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Lee T. Bacheler

This figure shows the co-authorship network connecting the top 25 collaborators of Lee T. Bacheler. A scholar is included among the top collaborators of Lee T. Bacheler 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 Lee T. Bacheler. Lee T. Bacheler 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 12
2 25
3 8
4 14
5 4
6
NRTI resistance associated with the RT mutation K70E in HIV-1
3
7
Protease mutation M89I/V is linked to therapy failure in patients infected with the HIV-1 non-B subtypes C, F or G (vol 20, pg 1789, 2006)
1
8 34
9
Application of multiple linear regression modelling to the quantitative prediction of HIV-1 drug susceptibility phenotype from viral genotype
2
10 28
11
Quantitative prediction of HIV drug susceptibility from viral genotype through linear regression modelling
2
12 67
13 81
14 1
15 19
16 34
17 16
18 11
19 8
20 40

About Lee T. Bacheler

Lee T. Bacheler is a scholar working on Virology, Infectious Diseases and Hepatology, having authored 82 papers that have together received 3.8k indexed citations. Recurring topics across this work include HIV Research and Treatment (67 papers), HIV/AIDS drug development and treatment (67 papers) and HIV/AIDS Research and Interventions (26 papers). The work is most often cited by research in Virology (2.1k citations), Infectious Diseases (2.1k citations) and Organic Chemistry (1.0k citations). Lee T. Bacheler has collaborated with scholars based in United States, United Kingdom and Canada. Frequent co-authors include Susan Erickson‐Viitanen, Ronald M. Klabe, Beverly C. Cordova, Chong‐Hwan Chang, Marlene M. Rayner, Prabhakar K. Jadhav, Michaël Otto, James L. Meek, H Fan and Sena Garber. Their work appears in journals such as Science, Cell and Proceedings of the National Academy of Sciences.

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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