David Pacheco-Villalobos

684 total citations
7 papers, 488 citations indexed

About

David Pacheco-Villalobos is a scholar working on Plant Science, Molecular Biology and Mechanical Engineering. According to data from OpenAlex, David Pacheco-Villalobos has authored 7 papers receiving a total of 488 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Plant Science, 3 papers in Molecular Biology and 1 paper in Mechanical Engineering. Recurrent topics in David Pacheco-Villalobos's work include Plant Molecular Biology Research (7 papers), Plant nutrient uptake and metabolism (4 papers) and Polysaccharides and Plant Cell Walls (2 papers). David Pacheco-Villalobos is often cited by papers focused on Plant Molecular Biology Research (7 papers), Plant nutrient uptake and metabolism (4 papers) and Polysaccharides and Plant Cell Walls (2 papers). David Pacheco-Villalobos collaborates with scholars based in Switzerland, Germany and Sweden. David Pacheco-Villalobos's co-authors include Christian S. Hardtke, Laura Ragni, Richard Sibout, Claus Schwechheimer, Kaisa Nieminen, Karin Ljung, Martial Sankar, Andika Gunadi, Dhiraj Thakare and Susana Martin‐Ortigosa and has published in prestigious journals such as The Plant Cell, Philosophical Transactions of the Royal Society B Biological Sciences and PLoS Genetics.

In The Last Decade

David Pacheco-Villalobos

7 papers receiving 481 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
David Pacheco-Villalobos Switzerland	6	439	330	30	21	18	7	488
Kaija Keinonen Finland	7	420 1.0×	408 1.2×	26 0.9×	24 1.1×	10 0.6×	8	488
Paul Passarinho Netherlands	6	357 0.8×	315 1.0×	16 0.5×	19 0.9×	9 0.5×	6	396
Cristina Úrbez Spain	12	609 1.4×	505 1.5×	40 1.3×	6 0.3×	25 1.4×	20	676
Greg F. W. Gocal Australia	6	467 1.1×	448 1.4×	36 1.2×	37 1.8×	37 2.1×	8	546
Elizabeth Etherington United States	6	334 0.8×	292 0.9×	28 0.9×	9 0.4×	18 1.0×	8	385
Yakun Xie China	13	635 1.4×	388 1.2×	21 0.7×	9 0.4×	26 1.4×	15	688
Ken-ichi Konagaya Japan	12	308 0.7×	289 0.9×	21 0.7×	67 3.2×	29 1.6×	28	414
Genkichi Takeda Japan	11	371 0.8×	205 0.6×	37 1.2×	52 2.5×	29 1.6×	41	437
Virginie Jouannet Germany	11	900 2.1×	604 1.8×	33 1.1×	5 0.2×	12 0.7×	11	951
Yanguang Chu China	10	267 0.6×	182 0.6×	12 0.4×	10 0.5×	62 3.4×	18	350

Countries citing papers authored by David Pacheco-Villalobos

Since Specialization

Citations

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

Fields of papers citing papers by David Pacheco-Villalobos

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of David Pacheco-Villalobos

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

All Works

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7 of 7 papers shown

1.

Kong, Jixiang, Susana Martin‐Ortigosa, John J. Finer, et al.. (2020). Overexpression of the Transcription Factor GROWTH-REGULATING FACTOR5 Improves Transformation of Dicot and Monocot Species. Frontiers in Plant Science. 11. 572319–572319. 136 indexed citations

2.

Pacheco-Villalobos, David, Sara M. Díaz-Moreno, Takayuki Tamaki, et al.. (2016). The Effects of High Steady State Auxin Levels on Root Cell Elongation in Brachypodium. The Plant Cell. 28(5). 1009–1024. 65 indexed citations

3.

Pacheco-Villalobos, David, Sara M. Díaz-Moreno, Takayuki Tamaki, et al.. (2016). The Effects of High Steady State Auxin Levels on Root Cell Elongation in Brachypodium. The Plant Cell. tpc.01057.2016–tpc.01057.2016. 3 indexed citations

4.

Pacheco-Villalobos, David, Martial Sankar, Karin Ljung, & Christian S. Hardtke. (2013). Disturbed Local Auxin Homeostasis Enhances Cellular Anisotropy and Reveals Alternative Wiring of Auxin-ethylene Crosstalk in Brachypodium distachyon Seminal Roots. PLoS Genetics. 9(6). e1003564–e1003564. 52 indexed citations

5.

Pacheco-Villalobos, David & Christian S. Hardtke. (2012). Natural genetic variation of root system architecture from Arabidopsis to Brachypodium : towards adaptive value. Philosophical Transactions of the Royal Society B Biological Sciences. 367(1595). 1552–1558. 43 indexed citations

6.

Ragni, Laura, Kaisa Nieminen, David Pacheco-Villalobos, et al.. (2011). Mobile Gibberellin Directly Stimulates Arabidopsis Hypocotyl Xylem Expansion . The Plant Cell. 23(4). 1322–1336. 176 indexed citations

7.

Canales, Javier, Concepción Ávila, Francisco R. Cantón, et al.. (2011). Gene expression profiling in the stem of young maritime pine trees: detection of ammonium stress-responsive genes in the apex. Trees. 26(2). 609–619. 13 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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