M. C. Becerra

3.2k citations
87 papers · 2.4k indexed · h-index 29

Impact in

Papers in

M. C. Becerra

86 papers receiving 2.4k citations

Peers

M. C. Becerra
Comparison fields: 5 of 136
  • Infectious Diseases 1.2k
  • Molecular Medicine 167
  • Epidemiology 946
  • Toxicology 48
  • Endocrinology 56
Replace Ewa Augustynowicz–Kopeć with:
Ewa Augustynowicz–Kopeć Poland
Maria Aparecida de Resende Brazil
Haitao Yang China
Kazuaki Matsumoto Japan
Nicholas Turner United States
Rajesh Pandey India
Fernando R. Pavan Brazil
Sun Hee Park South Korea
Avinash Sonawane India
G. K. Khuller India
M. C. Becerra relative to Ewa Augustynowicz–Kopeć Poland Ewa Augustynowicz–Kopeć's profile →
Citations per field
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Ewa Augustynowicz–Kopeć · 1×
Citations per year

Countries citing papers authored by M. C. Becerra

Since Specialization
Citations

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

Fields of papers citing papers by M. C. Becerra

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20250
2 202320
3 20237
4 202110
5 202115
6 20207
7 201913
8 201863
9 201640
10 201619
11 201515
12 20157
13 201512
14 201424
15 201327
16 201312
17 201317
18 20123
19 201146
20 2002125

About M. C. Becerra

M. C. Becerra is a scholar working on Infectious Diseases, Molecular Medicine, Epidemiology, Pharmacology and Biological Psychiatry, having authored 87 papers that have together received 2.4k indexed citations. Recurring topics across this work include Tuberculosis Research and Epidemiology (45 papers), Pneumonia and Respiratory Infections (23 papers), Pneumocystis jirovecii pneumonia detection and treatment (20 papers), Mycobacterium research and diagnosis (12 papers), Antibiotic Resistance in Bacteria (8 papers), Bacterial biofilms and quorum sensing (7 papers), Antibiotics Pharmacokinetics and Efficacy (7 papers) and Infectious Diseases and Tuberculosis (7 papers). The work is most often cited by research in Infectious Diseases (1.2k citations), Molecular Medicine (167 citations), Epidemiology (946 citations), Toxicology (48 citations) and Endocrinology (56 citations). M. C. Becerra has collaborated with scholars based in United States, Argentina and Peru. Frequent co-authors include Inés Albesa, Paulina L. Páez, Carole D. Mitnick, Jaime Bayona, Jennifer Furin, J. C. Scaiano, J Bayona, Gerardo A. Argüello, Paul E. Farmer and Virginia Aiassa. Their work appears in journals such as The International Journal of Tuberculosis and Lung Disease, Clinical Infectious Diseases, RSC Advances, Public Health Action and Carbohydrate Polymers.

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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