J. Barbero

1.8k citations
12 papers · 1.1k · 1 hit paper · h-index 8

Impact in

Papers in

J. Barbero

12 papers receiving 1.0k citations

J. Barbero's Hit Papers

Predicting protein structures with a multiplayer online game 2010 · 877 citations
8770+5+10Years since publication250500750

Peers

J. Barbero
Comparison fields: 5 of 137
  • Computer Science Applications 422
  • Ecological Modeling 90
  • Human-Computer Interaction 80
  • Information Systems and Management 87
  • Developmental and Educational Psychology 128
Replace Jeehyung Lee with:
Jeehyung Lee United States
Foldit Players United States
Firas Khatib United States
Christothea Herodotou United Kingdom
Daniel Schneider Brazil
Kobi Gal Israel
Ramine Tinati United Kingdom
Markus Luczak–Roesch New Zealand
Christopher Collins Canada
Wayne G. Lutters United States
J. Barbero relative to Jeehyung Lee United States Jeehyung Lee's profile →
Citations per field
00.5×1.5×
Jeehyung Lee · 1×
Citations per year

Countries citing papers authored by J. Barbero

Since Specialization
Citations

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

Fields of papers citing papers by J. Barbero

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

12 of 12 papers shown
#Work
1
Predicting protein structures with a multiplayer online game
Hit paper breakdown →
2010877
2 201092
3 201137
4 200623
5 201615
6 200713
7 201712
8 201011
9 20116
10 20234
11 20253
12
A pilot bridging data integration and analytics: BioMediator and R?
20052

About J. Barbero

J. Barbero is a scholar working on General Health Professions, Public Health, Environmental and Occupational Health, Sociology and Political Science, Information Systems and Management and Artificial Intelligence, having authored 12 papers that have together received 1.1k indexed citations. Recurring topics across this work include Hemophilia Treatment and Research (2 papers), Ethics and bioethics in healthcare (2 papers), Artificial Intelligence in Games (2 papers), Educational Games and Gamification (2 papers), Patient Dignity and Privacy (2 papers), Scientific Computing and Data Management (2 papers), Palliative Care and End-of-Life Issues (2 papers) and Patient-Provider Communication in Healthcare (2 papers). The work is most often cited by research in Computer Science Applications (422 citations), Ecological Modeling (90 citations), Human-Computer Interaction (80 citations), Information Systems and Management (87 citations) and Developmental and Educational Psychology (128 citations). J. Barbero has collaborated with scholars based in United States and Spain. Frequent co-authors include David Baker, Firas Khatib, Seth Cooper, Zoran Popović, Adrien Treuille, Andrew Leaver‐Fay, Foldit Players, Jeehyung Lee, David Salesin and James Fogarty. Their work appears in journals such as Neurotherapeutics, Haemophilia, Nature, Vox Sanguinis and Journal of Neurosurgical 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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