David Báez-Nieto

35 total papers · 886 total citations
20 papers, 501 citations indexed

About

David Báez-Nieto is a scholar working on Cellular and Molecular Neuroscience, Molecular Biology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, David Báez-Nieto has authored 20 papers receiving a total of 501 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Cellular and Molecular Neuroscience, 14 papers in Molecular Biology and 6 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in David Báez-Nieto's work include Ion channel regulation and function (12 papers), Cardiac electrophysiology and arrhythmias (6 papers) and Neuroscience and Neural Engineering (5 papers). David Báez-Nieto is often cited by papers focused on Ion channel regulation and function (12 papers), Cardiac electrophysiology and arrhythmias (6 papers) and Neuroscience and Neural Engineering (5 papers). David Báez-Nieto collaborates with scholars based in United States, Chile and Germany. David Báez-Nieto's co-authors include Ramón Latorre, Carlos González, Patricio Rojas, Ignacio Leyva-Valencia, David Naranjo, Jen Q. Pan, Andrew S. Allen, Osvaldo Álvarez, Juan P. Castillo and Henrike Heyne and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Neuroscience and Brain.

In The Last Decade

David Báez-Nieto

19 papers receiving 493 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
David Báez-Nieto	359	179	112	111	74	20	501
Alicia Sedó	244 0.7×	122 0.7×	173 1.5×	96 0.9×	44 0.6×	15	602
Jiaofeng Chen	461 1.3×	188 1.1×	64 0.6×	143 1.3×	31 0.4×	11	562
Raul E. Guzman	361 1.0×	237 1.3×	89 0.8×	33 0.3×	40 0.5×	20	548
Hongli Sun	267 0.7×	92 0.5×	38 0.3×	240 2.2×	29 0.4×	20	556
Romina V. Sepúlveda	322 0.9×	154 0.9×	155 1.4×	116 1.0×	16 0.2×	26	484
Willy Carrasquel-Ursulaez	408 1.1×	231 1.3×	49 0.4×	195 1.8×	25 0.3×	12	501
Caihong Wu	333 0.9×	208 1.2×	40 0.4×	184 1.7×	23 0.3×	31	553
Ramón A. Lorca	321 0.9×	183 1.0×	35 0.3×	75 0.7×	31 0.4×	24	605
Katrin Schnizler	383 1.1×	241 1.3×	105 0.9×	49 0.4×	18 0.2×	14	610
Cindy Barbosa	215 0.6×	233 1.3×	48 0.4×	35 0.3×	23 0.3×	13	486

Countries citing papers authored by David Báez-Nieto

Since Specialization

Citations

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

Fields of papers citing papers by David Báez-Nieto

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Báez-Nieto. 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 David Báez-Nieto. The network helps show where David Báez-Nieto may publish in the future.

Co-authorship network of co-authors of David Báez-Nieto

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

All Works

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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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