Kimberly Siletti

4.2k total citations · 1 hit paper
8 papers, 424 citations indexed

About

Kimberly Siletti is a scholar working on Molecular Biology, Sensory Systems and Developmental Neuroscience. According to data from OpenAlex, Kimberly Siletti has authored 8 papers receiving a total of 424 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Sensory Systems and 2 papers in Developmental Neuroscience. Recurrent topics in Kimberly Siletti's work include Hearing, Cochlea, Tinnitus, Genetics (3 papers), Developmental Biology and Gene Regulation (3 papers) and Single-cell and spatial transcriptomics (2 papers). Kimberly Siletti is often cited by papers focused on Hearing, Cochlea, Tinnitus, Genetics (3 papers), Developmental Biology and Gene Regulation (3 papers) and Single-cell and spatial transcriptomics (2 papers). Kimberly Siletti collaborates with scholars based in United States, Sweden and Switzerland. Kimberly Siletti's co-authors include A. J. Hudspeth, Elin Vinsland, Alex R. Lederer, Alessandro Furlan, Mats Nilsson, Christoffer Mattsson Langseth, Alejandro Mossi Albiach, Peter Lönnerberg, Daniel Gyllborg and Anna Johnsson and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Genes & Development.

In The Last Decade

Kimberly Siletti

8 papers receiving 421 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.

Molecular architecture of the developing mouse brain

2021 256 citations Gioele La Manno, Kimberly Siletti et al. Nature profile →

Peers

Kimberly Siletti

MB

SS

CB

NEURO

DN

Connor Finkbeiner United States

Tracy Yamawaki United States

Laurence Borgs Belgium

Paromita Majumder Brazil

William Joo United States

Kersti Lilleväli Estonia

Kathryn M. Tabor United States

Catherine M. Drerup United States

Mariela Zirlinger United States

Tuanlian Luo United States

Connor Finkbeiner United States

Kimberly Siletti

542 ×2.0

MB

37 ×0.7

SS

46 ×0.9

CB

87 ×1.7

NEURO

73 ×1.5

DN

Citations per year, relative to Kimberly Siletti Kimberly Siletti (= 1×) peers Connor Finkbeiner

Countries citing papers authored by Kimberly Siletti

Since Specialization

Citations

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

Fields of papers citing papers by Kimberly Siletti

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kimberly Siletti

This figure shows the co-authorship network connecting the top 25 collaborators of Kimberly Siletti. A scholar is included among the top collaborators of Kimberly Siletti 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 Kimberly Siletti. Kimberly Siletti 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.

Herb, Brian R., Aparna Bhaduri, Carlo Colantuoni, et al.. (2023). Single-cell genomics reveals region-specific developmental trajectories underlying neuronal diversity in the human hypothalamus. Science Advances. 9(45). eadf6251–eadf6251. 21 indexed citations

2.

Manno, Gioele La, Kimberly Siletti, Alessandro Furlan, et al.. (2021). Molecular architecture of the developing mouse brain. Nature. 596(7870). 92–96. 256 indexed citations breakdown →

3.

Jacobo, Adrián, et al.. (2019). Notch-Mediated Determination of Hair-Bundle Polarity in Mechanosensory Hair Cells of the Zebrafish Lateral Line. Current Biology. 29(21). 3579–3587.e7. 33 indexed citations

4.

Dow, Eliot R., et al.. (2018). Connectomics of the zebrafish's lateral-line neuromast reveals wiring and miswiring in a simple microcircuit. eLife. 7. 27 indexed citations

5.

Siletti, Kimberly, Basile Tarchini, & A. J. Hudspeth. (2017). Daple coordinates organ-wide and cell-intrinsic polarity to pattern inner-ear hair bundles. Proceedings of the National Academy of Sciences. 114(52). 34 indexed citations

6.

Shah, Pavak K., Anthony Santella, Adrián Jacobo, et al.. (2017). An In Toto Approach to Dissecting Cellular Interactions in Complex Tissues. Developmental Cell. 43(4). 530–540.e4. 14 indexed citations

7.

Dow, Eliot R., Kimberly Siletti, & A. J. Hudspeth. (2015). Cellular projections from sensory hair cells form polarity-specific scaffolds during synaptogenesis. Genes & Development. 29(10). 1087–1094. 17 indexed citations

8.

Butler, Ian, Kimberly Siletti, Peter R. Oxley, & Daniel J. C. Kronauer. (2014). Conserved Microsatellites in Ants Enable Population Genetic and Colony Pedigree Studies across a Wide Range of Species. PLoS ONE. 9(9). e107334–e107334. 22 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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