E. Parada

488 citations
22 papers · 342 · h-index 9

Impact in

Papers in

E. Parada

19 papers receiving 334 citations

Peers

E. Parada
Comparison fields: 5 of 73
  • Infectious Diseases 165
  • Biological Psychiatry 12
  • Hepatology 25
  • Animal Science and Zoology 26
  • Obstetrics and Gynecology 17
Replace Yan Qiu with:
Yan Qiu China
Anna Martin Germany
Thiago Pinheiro Arrais Aloia Brazil
Hugo Caire de Castro Faria Neto Brazil
Qimin Wang China
Kazuyuki Narimatsu Japan
Jingjing Rao China
Melany Ríos-Morales Netherlands
Yuexia Liao China
Jianxin Li China
E. Parada relative to Yan Qiu China Yan Qiu's profile →
Citations per field
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Citations per year

Countries citing papers authored by E. Parada

Since Specialization
Citations

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

Fields of papers citing papers by E. Parada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200483
2 202047
3 201145
4 200536
5 201335
6 201527
7 201411
8 20229
9 20209
10 20228
11 20218
12 20077
13 20226
14 20163
15 20143
16 20212
17 20221
18 20151
19 20071
20 20230

About E. Parada

E. Parada is a scholar working on Infectious Diseases, Molecular Biology, Cellular and Molecular Neuroscience, Pediatrics, Perinatology and Child Health and Pulmonary and Respiratory Medicine, having authored 22 papers that have together received 342 indexed citations. Recurring topics across this work include Viral gastroenteritis research and epidemiology (4 papers), Diabetes and associated disorders (2 papers), Kidney Stones and Urolithiasis Treatments (2 papers), COVID-19 diagnosis using AI (2 papers), SARS-CoV-2 detection and testing (2 papers), COVID-19 Clinical Research Studies (2 papers), Health, Environment, Cognitive Aging (2 papers) and Birth, Development, and Health (2 papers). The work is most often cited by research in Infectious Diseases (165 citations), Biological Psychiatry (12 citations), Hepatology (25 citations), Animal Science and Zoology (26 citations) and Obstetrics and Gynecology (17 citations). E. Parada has collaborated with scholars based in Spain, Brazil and United States. Frequent co-authors include Javier Egea, Manuela G. López, Parvin H. Azimi, David O. Matson, Mary Allen Staat, Tamás Berke, Alejandro Romero, Laura del Barrio, María Dolores Martin‐de‐Saavedra and Xi Jiang. Their work appears in journals such as Neuroscience, The Pediatric Infectious Disease Journal, Molecular Neurobiology, Neurochemical Research and Pediatric Nephrology.

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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