Cara Ruble

1.8k total citations · 1 hit paper
9 papers, 989 citations indexed

About

Cara Ruble is a scholar working on Molecular Biology, Genetics and Cellular and Molecular Neuroscience. According to data from OpenAlex, Cara Ruble has authored 9 papers receiving a total of 989 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Genetics and 2 papers in Cellular and Molecular Neuroscience. Recurrent topics in Cara Ruble's work include Genetic Associations and Epidemiology (3 papers), Receptor Mechanisms and Signaling (3 papers) and Alzheimer's disease research and treatments (2 papers). Cara Ruble is often cited by papers focused on Genetic Associations and Epidemiology (3 papers), Receptor Mechanisms and Signaling (3 papers) and Alzheimer's disease research and treatments (2 papers). Cara Ruble collaborates with scholars based in United States, United Kingdom and Bulgaria. Cara Ruble's co-authors include Mark E. Gurney, Jinhe Li, Wei Xu, Javier Apfeld, Ross S. Francis, Annette L. Parks, Carol S. Himes, Jeffrey S. Nye, Mark Maxwell and Michael C. Ellis and has published in prestigious journals such as Bioinformatics, Biological Psychiatry and Developmental Cell.

In The Last Decade

Cara Ruble

9 papers receiving 978 citations

Hit Papers

aph-1 and pen-2 Are Required for Notch Pathway Signaling,... 2002 2026 2010 2018 2002 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cara Ruble United States 8 533 514 203 176 172 9 989
Eva Czirr United States 14 635 1.2× 391 0.8× 149 0.7× 160 0.9× 111 0.6× 21 1.2k
Matthias Gralle Brazil 13 659 1.2× 446 0.9× 226 1.1× 157 0.9× 163 0.9× 17 1.1k
Akira Kuzuya Japan 17 476 0.9× 436 0.8× 228 1.1× 106 0.6× 143 0.8× 41 952
Mikako Sakurai Japan 18 362 0.7× 703 1.4× 297 1.5× 129 0.7× 123 0.7× 23 1.2k
Kenichi Nagata Japan 14 601 1.1× 522 1.0× 263 1.3× 121 0.7× 46 0.3× 30 1.2k
Pilar Gómez‐Ramos Spain 15 586 1.1× 766 1.5× 518 2.6× 237 1.3× 199 1.2× 37 1.3k
Xu‐Qiao Chen United States 13 323 0.6× 416 0.8× 254 1.3× 142 0.8× 130 0.8× 28 918
Qingyi Zheng‐Fischhöfer Germany 9 701 1.3× 696 1.4× 281 1.4× 129 0.7× 293 1.7× 9 1.1k
Božidar Novak Germany 11 511 1.0× 390 0.8× 227 1.1× 220 1.3× 132 0.8× 18 1.0k
Jeremy H. Herskowitz United States 20 628 1.2× 563 1.1× 451 2.2× 128 0.7× 139 0.8× 37 1.4k

Countries citing papers authored by Cara Ruble

Since Specialization
Citations

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

Fields of papers citing papers by Cara Ruble

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cara Ruble

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

All Works

9 of 9 papers shown
1.
Pearson, Neil D., Karim Malki, David A. Evans, et al.. (2019). TractaViewer: a genome-wide tool for preliminary assessment of therapeutic target druggability. Bioinformatics. 35(21). 4509–4510. 5 indexed citations
2.
Ruble, Cara, Ryan M. Smith, John Calley, et al.. (2016). Genomic structure and expression of the human serotonin 2A receptor gene (HTR2A) locus: identification of novel HTR2A and antisense (HTR2A-AS1) exons. BMC Genetics. 17(1). 16–16. 29 indexed citations
3.
Ursu, Daniel, Philip J. Ebert, Cara Ruble, et al.. (2014). Gain and Loss of Function of P2X7 Receptors: Mechanisms, Pharmacology and Relevance to Diabetic Neuropathic Pain. Molecular Pain. 10. 37–37. 64 indexed citations
4.
Grubisha, Olivera, Adrian J. Mogg, Helen Sanger, et al.. (2013). Pharmacological profiling of the TRPV3 channel in recombinant and native assays. British Journal of Pharmacology. 171(10). 2631–2644. 18 indexed citations
5.
Smith, Ryan M., Audrey C. Papp, Amy Webb, et al.. (2012). Multiple Regulatory Variants Modulate Expression of 5-Hydroxytryptamine 2A Receptors in Human Cortex. Biological Psychiatry. 73(6). 546–554. 57 indexed citations
6.
Munsie, Leanne, Mike Reed, Cara Ruble, et al.. (2010). Pharmacogenetic analysis of the mGlu2/3 agonist LY2140023 monohydrate in the treatment of schizophrenia. The Pharmacogenomics Journal. 12(3). 246–254. 34 indexed citations
7.
Karnovsky, Alla, Denise D. McKinley, Cara Ruble, et al.. (2003). A cluster of novel serotonin receptor 3-like genes on human chromosome 3. Gene. 319. 137–148. 69 indexed citations
8.
Li, Jinhe, Adele M. Pauley, John R. Brashler, et al.. (2002). SEL‐10 interacts with presenilin 1, facilitates its ubiquitination, and alters A‐beta peptide production. Journal of Neurochemistry. 82(6). 1540–1548. 58 indexed citations
9.
Francis, Ross S., Jianhua Zhang, David A. Ruddy, et al.. (2002). aph-1 and pen-2 Are Required for Notch Pathway Signaling, γ-Secretase Cleavage of βAPP, and Presenilin Protein Accumulation. Developmental Cell. 3(1). 85–97. 655 indexed citations breakdown →

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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