Juan C. Alvarez

1.7k citations
14 papers · 1.1k indexed · 1 hit paper · h-index 11
Topics
Computational Drug Discovery Methods (6 papers)Chemical Synthesis and Analysis (4 papers)Protein Structure and Dynamics (4 papers)
Partner nations
United StatesCubaCanada

In The Last Decade

Juan C. Alvarez

14 papers receiving 1.0k citations

Hit Papers

The importance of synthetic chemistry in the pharmaceutic...20192026202120232019100200300400

Peers

Juan C. Alvarez
Comparison fields: 5 of 106
  • Molecular Biology 477
  • Organic Chemistry 395
  • Computational Theory and Mathematics 317
  • Materials Chemistry 146
  • Oncology 109
Replace Joseph B. Moon with:
Joseph B. Moon United States
Justin Bower United Kingdom
Daniel R. McMasters United States
Jean‐Louis Kraus France
Jeremy R. Duvall United States
Christophe Meyer France
Thompson N. Doman United States
Omoshile Clement United States
Youla S. Tsantrizos Canada
Olga Caamaño Spain
Juan C. Alvarez relative to Joseph B. Moon United States Joseph B. Moon's profile →
Citations per field
00.5×50×118×
Joseph B. Moon · 1×
Citations per year

Countries citing papers authored by Juan C. Alvarez

Since Specialization
Citations

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

Fields of papers citing papers by Juan C. Alvarez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Juan C. Alvarez. 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 Juan C. Alvarez. The network helps show where Juan C. Alvarez may publish in the future.

Co-authorship network of co-authors of Juan C. Alvarez

This figure shows the co-authorship network connecting the top 25 collaborators of Juan C. Alvarez. A scholar is included among the top collaborators of Juan C. Alvarez 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 Juan C. Alvarez. Juan C. Alvarez is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
#WorkIndexed citations
1 11
2 43
3 100
4
The importance of synthetic chemistry in the pharmaceutical industrybreakdown →
454
5 4
6 19
7 98
8 33
9 58
10
2
11 31
12 8
13 26
14 184

About Juan C. Alvarez

Juan C. Alvarez is a scholar working on Virology, Computational Theory and Mathematics and Molecular Biology, having authored 14 papers that have together received 1.1k indexed citations. Recurring topics across this work include Computational Drug Discovery Methods (6 papers), Chemical Synthesis and Analysis (4 papers) and Protein Structure and Dynamics (4 papers). The work is most often cited by research in Computational Theory and Mathematics (317 citations), Organic Chemistry (395 citations) and Virology (61 citations). Juan C. Alvarez has collaborated with scholars based in United States, Cuba and Canada. Frequent co-authors include Spencer D. Dreher, Richard D. Tillyer, Kevin R. Campos, Matthew D. Truppo, R. M. Garbaccio, N.K. Terrett, Emma R. Parmee, Paul J. Coleman, Diane Joseph‐McCarthy and Charles S. Craik. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Biochemistry.

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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