Paola N. Perrat

1.2k total citations
12 papers, 853 citations indexed

About

Paola N. Perrat is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Aging. According to data from OpenAlex, Paola N. Perrat has authored 12 papers receiving a total of 853 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 6 papers in Cellular and Molecular Neuroscience and 4 papers in Aging. Recurrent topics in Paola N. Perrat's work include Neurobiology and Insect Physiology Research (5 papers), Genetics, Aging, and Longevity in Model Organisms (4 papers) and Acute Myeloid Leukemia Research (3 papers). Paola N. Perrat is often cited by papers focused on Neurobiology and Insect Physiology Research (5 papers), Genetics, Aging, and Longevity in Model Organisms (4 papers) and Acute Myeloid Leukemia Research (3 papers). Paola N. Perrat collaborates with scholars based in United States, Canada and Netherlands. Paola N. Perrat's co-authors include Scott Waddell, Shamik Dasgupta, Lucio H. Castilla, Sean F. Landrette, Jie Wang, Zhiping Weng, Michael Rosbash, William E. Theurkauf, Ya‐Huei Kuo and Susan A. Heilman and has published in prestigious journals such as Science, Proceedings of the National Academy of Sciences and Neuron.

In The Last Decade

Paola N. Perrat

11 papers receiving 847 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Paola N. Perrat United States 10 455 295 190 145 133 12 853
Makoto I. Kanai Japan 10 285 0.6× 496 1.7× 208 1.1× 73 0.5× 75 0.6× 12 800
Olga Barmina United States 16 234 0.5× 175 0.6× 335 1.8× 52 0.4× 57 0.4× 30 744
Sijun Zhu United States 15 717 1.6× 679 2.3× 111 0.6× 33 0.2× 168 1.3× 21 1.2k
Krista Golden United States 13 614 1.3× 198 0.7× 124 0.7× 21 0.1× 85 0.6× 16 723
Heather T. Broihier United States 19 819 1.8× 418 1.4× 206 1.1× 21 0.1× 101 0.8× 26 1.2k
Natalia Tulina United States 9 572 1.3× 205 0.7× 192 1.0× 21 0.1× 62 0.5× 11 880
Justin P. Blumenstiel United States 20 958 2.1× 79 0.3× 245 1.3× 37 0.3× 642 4.8× 35 1.3k
Claire Cronmiller United States 14 577 1.3× 237 0.8× 254 1.3× 13 0.1× 76 0.6× 18 802
Melanie Hamblen United States 9 460 1.0× 291 1.0× 337 1.8× 287 2.0× 185 1.4× 10 1.4k
Stéphanie Le Bras France 16 515 1.1× 120 0.4× 174 0.9× 21 0.1× 38 0.3× 24 740

Countries citing papers authored by Paola N. Perrat

Since Specialization
Citations

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

Fields of papers citing papers by Paola N. Perrat

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Paola N. Perrat. 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 Paola N. Perrat. The network helps show where Paola N. Perrat may publish in the future.

Co-authorship network of co-authors of Paola N. Perrat

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

All Works

12 of 12 papers shown
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Peterson, Nicholas, Pengpeng Liu, Sarah M. Anderson, et al.. (2019). The nuclear hormone receptor NHR-86 controls anti-pathogen responses in C. elegans. PLoS Genetics. 15(1). e1007935–e1007935. 39 indexed citations
4.
Perrat, Paola N., et al.. (2017). Functional Requirements for Heparan Sulfate Biosynthesis in Morphogenesis and Nervous System Development in C. elegans. PLoS Genetics. 13(1). e1006525–e1006525. 16 indexed citations
5.
Barnstedt, Oliver, David Owald, Johannes Felsenberg, et al.. (2016). Memory-Relevant Mushroom Body Output Synapses Are Cholinergic. Neuron. 89(6). 1237–1247. 127 indexed citations
6.
Perrat, Paola N., et al.. (2015). Glypican Is a Modulator of Netrin-Mediated Axon Guidance. PLoS Biology. 13(7). e1002183–e1002183. 44 indexed citations
7.
Perrat, Paola N., Shamik Dasgupta, Jie Wang, et al.. (2013). Transposition-Driven Genomic Heterogeneity in the Drosophila Brain. Science. 340(6128). 91–95. 177 indexed citations
8.
Dasgupta, Shamik, et al.. (2009). There are many ways to train a fly. Fly. 3(1). 3–9. 41 indexed citations
9.
Kuo, Ya‐Huei, Sean F. Landrette, Susan A. Heilman, et al.. (2006). Cbfβ-SMMHC induces distinct abnormal myeloid progenitors able to develop acute myeloid leukemia. Cancer Cell. 9(1). 57–68. 97 indexed citations
10.
Keene, Alex C., Markus Stratmann, Andreas Keller, et al.. (2004). Diverse Odor-Conditioned Memories Require Uniquely Timed Dorsal Paired Medial Neuron Output. Neuron. 44(3). 521–533. 108 indexed citations
11.
Landrette, Sean F., Ya‐Huei Kuo, Karen Hensen, et al.. (2004). Plag1 and Plagl2 are oncogenes that induce acute myeloid leukemia in cooperation with Cbfb-MYH11. Blood. 105(7). 2900–2907. 97 indexed citations
12.
Castilla, Lucio H., Paola N. Perrat, Natalia J. Martinez, et al.. (2004). Identification of genes that synergize with Cbfb-MYH11 in the pathogenesis of acute myeloid leukemia. Proceedings of the National Academy of Sciences. 101(14). 4924–4929. 103 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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