J.A. Hernandez Prada

19 total papers · 1.1k total citations
13 papers, 889 citations indexed

About

J.A. Hernandez Prada is a scholar working on Molecular Biology, Immunology and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, J.A. Hernandez Prada has authored 13 papers receiving a total of 889 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Molecular Biology, 4 papers in Immunology and 3 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in J.A. Hernandez Prada's work include Hormonal Regulation and Hypertension (3 papers), Computational Drug Discovery Methods (3 papers) and Renin-Angiotensin System Studies (3 papers). J.A. Hernandez Prada is often cited by papers focused on Hormonal Regulation and Hypertension (3 papers), Computational Drug Discovery Methods (3 papers) and Renin-Angiotensin System Studies (3 papers). J.A. Hernandez Prada collaborates with scholars based in United States and Brazil. J.A. Hernandez Prada's co-authors include David A. Ostrov, Mohan K. Raizada, Kathryn A. K. Finton, Thomas C. Rowe, Patrick Corsino, Matthew J. Huentelman, Jasenka Zubcevic, Xiaodong Xiao, Dimiter S. Dimitrov and Anderson J. Ferreira and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Immunity and Nature Immunology.

In The Last Decade

J.A. Hernandez Prada

12 papers receiving 869 citations

Author Peers

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

Author						Papers	Cites
J.A. Hernandez Prada	314	192	192	182	152	13	889
Santosh A. Khedkar	461 1.5×	49 0.3×	145 0.8×	150 0.8×	53 0.3×	27	993
Saurabh Menon	460 1.5×	84 0.4×	93 0.5×	34 0.2×	299 2.0×	15	971
Andreas Blum	281 0.9×	35 0.2×	502 2.6×	57 0.3×	50 0.3×	29	1.0k
Tsau-Yen Lin	535 1.7×	80 0.4×	155 0.8×	72 0.4×	27 0.2×	24	963
Charles David	592 1.9×	41 0.2×	75 0.4×	79 0.4×	80 0.5×	14	976
Terry Wood	274 0.9×	46 0.2×	184 1.0×	69 0.4×	85 0.6×	21	906
Wai‐Lung Ng	442 1.4×	43 0.2×	205 1.1×	78 0.4×	342 2.3×	32	972
Sarah L. Greig	326 1.0×	46 0.2×	105 0.5×	71 0.4×	121 0.8×	28	918
Rafael Andrade Caceres	586 1.9×	116 0.6×	111 0.6×	37 0.2×	152 1.0×	39	984
R.J. Rosenfeld	480 1.5×	75 0.4×	123 0.6×	41 0.2×	94 0.6×	15	1.0k

Countries citing papers authored by J.A. Hernandez Prada

Since Specialization

Citations

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

Fields of papers citing papers by J.A. Hernandez Prada

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of J.A. Hernandez Prada

This figure shows the co-authorship network connecting the top 25 collaborators of J.A. Hernandez Prada. A scholar is included among the top collaborators of J.A. Hernandez Prada 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 J.A. Hernandez Prada. J.A. Hernandez Prada 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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