David Hurtado

1.4k total citations · 1 hit paper
8 papers, 1.1k citations indexed

About

David Hurtado is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Physiology. According to data from OpenAlex, David Hurtado has authored 8 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Cellular and Molecular Neuroscience and 3 papers in Physiology. Recurrent topics in David Hurtado's work include Alzheimer's disease research and treatments (3 papers), Neuroscience and Neuropharmacology Research (3 papers) and Cellular transport and secretion (2 papers). David Hurtado is often cited by papers focused on Alzheimer's disease research and treatments (3 papers), Neuroscience and Neuropharmacology Research (3 papers) and Cellular transport and secretion (2 papers). David Hurtado collaborates with scholars based in United States, United Kingdom and Spain. David Hurtado's co-authors include John Q. Trojanowski, Virginia M.‐Y. Lee, Linda K. Kwong, Jing Guo, Todd J. Cohen, Laura Molina‐Porcel, Michiyo Iba, Steven M. Paul, Katherine W. Roche and John Isaac and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and Journal of Neuroscience.

In The Last Decade

David Hurtado

7 papers receiving 1.1k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The acetylation of tau inhibits its function and promotes pathological tau aggregation

2011 533 citations Todd J. Cohen, Jing Guo et al. Nature Communications profile →

Peers

David Hurtado

PHYSI

MB

CMN

CB

PHARM

Kanae Ando Japan

Matthias Gralle Brazil

Aida Abraha United States

Lidia Bakota Germany

Jean Sévalle France

Jordana L. Meyerson United States

Nathalie Pierrot Belgium

Raquel Cuadros Spain

Jian‐Zhi Wang China

Virginie Buggia-Prévot United States

Kanae Ando Japan

David Hurtado

856 ×1.4

PHYSI

681 ×1.1

MB

273 ×1.0

CMN

309 ×1.4

CB

185 ×1.1

PHARM

Citations per year, relative to David Hurtado David Hurtado (= 1×) peers Kanae Ando

Countries citing papers authored by David Hurtado

Since Specialization

Citations

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

Fields of papers citing papers by David Hurtado

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Hurtado

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

All Works

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8 of 8 papers shown

1.

Hurtado, David, et al.. (2012). Selectively Silencing GSK-3 Isoforms Reduces Plaques and Tangles in Mouse Models of Alzheimer's Disease. Journal of Neuroscience. 32(21). 7392–7402. 97 indexed citations

2.

Cohen, Todd J., Jing Guo, David Hurtado, et al.. (2011). The acetylation of tau inhibits its function and promotes pathological tau aggregation. Nature Communications. 2(1). 252–252. 533 indexed citations breakdown →

3.

Hurtado, David. (2011). Selective reduction of GSK-3 isoforms ameliorates pathological signatures of Alzheimer's disease. Scholarly Commons (University of Pennsylvania).

4.

Hurtado, David, Laura Molina‐Porcel, Michiyo Iba, et al.. (2010). Aβ Accelerates the Spatiotemporal Progression of Tau Pathology and Augments Tau Amyloidosis in an Alzheimer Mouse Model. American Journal Of Pathology. 177(4). 1977–1988. 170 indexed citations

5.

Nasu‐Nishimura, Yukiko, et al.. (2006). Identification of an Endoplasmic Reticulum-Retention Motif in an Intracellular Loop of the Kainate Receptor Subunit KA2. Journal of Neuroscience. 26(26). 7014–7021. 58 indexed citations

6.

Isaac, John, Jack R. Mellor, David Hurtado, & Katherine W. Roche. (2004). Kainate receptor trafficking: physiological roles and molecular mechanisms. Pharmacology & Therapeutics. 104(3). 163–172. 37 indexed citations

7.

Hurtado, David, et al.. (2003). Trafficking and surface expression of the glutamate receptor subunit, KA2. Biochemical and Biophysical Research Communications. 310(1). 8–13. 30 indexed citations

8.

Parlati, Francesco, Oleg Varlamov, Keren Paz, et al.. (2002). Distinct SNARE complexes mediating membrane fusion in Golgi transport based on combinatorial specificity. Proceedings of the National Academy of Sciences. 99(8). 5424–5429. 147 indexed citations

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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