Sergio Vaca

36 papers receiving 634 citations

Peers

Sergio Vaca
Comparison fields: 5 of 85
  • Endocrinology 163
  • Microbiology 150
  • Molecular Medicine 102
  • Infectious Diseases 172
  • Periodontics 40
Replace Neil Doherty with:
Neil Doherty United Kingdom
André P. Burnens Switzerland
Hasan Nazik Türkiye
Mark Reuter United Kingdom
Carlos Hidalgo‐Grass Israel
Claire Hennequin France
Steven D. Mahlen United States
Marta Lamata Spain
Mamata Gurung South Korea
Hélène Réglier‐Poupet France
Sergio Vaca relative to Neil Doherty United Kingdom Neil Doherty's profile →
Citations per field
00.5×3.7×
Neil Doherty · 1×
Citations per year

Countries citing papers authored by Sergio Vaca

Since Specialization
Citations

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

Fields of papers citing papers by Sergio Vaca

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201576
2 200760
3 200944
4 201637
5 201931
6 201730
7 201830
8 201628
9 201225
10 200324
11 201424
12 201223
13 200521
14 201820
15 201117
16 202017
17 201316
18 201214
19 201913
20 200613

About Sergio Vaca

Sergio Vaca is a scholar working on Infectious Diseases, Molecular Biology, Microbiology, Molecular Medicine and Endocrinology, having authored 39 papers that have together received 658 indexed citations. Recurring topics across this work include Antibiotic Resistance in Bacteria (8 papers), Microbial infections and disease research (7 papers), Escherichia coli research studies (7 papers), Antimicrobial Resistance in Staphylococcus (6 papers), Bacterial biofilms and quorum sensing (6 papers), Antifungal resistance and susceptibility (5 papers), Bacteriophages and microbial interactions (4 papers) and Streptococcal Infections and Treatments (3 papers). The work is most often cited by research in Endocrinology (163 citations), Microbiology (150 citations), Molecular Medicine (102 citations), Infectious Diseases (172 citations) and Periodontics (40 citations). Sergio Vaca has collaborated with scholars based in Mexico, Australia and Ecuador. Frequent co-authors include Eric Monroy‐Pérez, Gloria Luz Paniagua‐Contreras, Erasmo Negrete‐Abascal, Felipe Vaca‐Paniagua, Edgar Zenteno, Patricia Sánchez Alonso, Jaime Bustos‐Martínez, Mireya de la Garza, P. J. Blackall and C. Rodríguez. Their work appears in journals such as Annals of Clinical Microbiology and Antimicrobials, Journal of Microbiology Immunology and Infection, Antonie van Leeuwenhoek, Canadian Journal of Microbiology and Mycoses.

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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