Cheryl L. Gatto

1.2k total citations
29 papers, 621 citations indexed

About

Cheryl L. Gatto is a scholar working on Molecular Biology, Genetics and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Cheryl L. Gatto has authored 29 papers receiving a total of 621 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 7 papers in Genetics and 5 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Cheryl L. Gatto's work include Genetics and Neurodevelopmental Disorders (6 papers), Autism Spectrum Disorder Research (4 papers) and Congenital heart defects research (3 papers). Cheryl L. Gatto is often cited by papers focused on Genetics and Neurodevelopmental Disorders (6 papers), Autism Spectrum Disorder Research (4 papers) and Congenital heart defects research (3 papers). Cheryl L. Gatto collaborates with scholars based in United States, Denmark and Saudi Arabia. Cheryl L. Gatto's co-authors include Kendal Broadie, Barbara J. Walker, Stephen B. Lambert, Mary Lynn Dear, Taketoshi Kambara, Mitsuo Ikebe, Xiang‐dong Li, Jessica L. Crowley, Elizabeth J. Luna and Osamu Satō and has published in prestigious journals such as Journal of Biological Chemistry, The Journal of Cell Biology and Development.

In The Last Decade

Cheryl L. Gatto

25 papers receiving 613 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cheryl L. Gatto United States 14 289 232 114 103 103 29 621
Douglas Londoño United States 12 255 0.9× 172 0.7× 165 1.4× 15 0.1× 67 0.7× 20 734
Marsha F. Browning United States 13 221 0.8× 187 0.8× 17 0.1× 58 0.6× 69 0.7× 15 704
Nicholas M. Allen Ireland 12 223 0.8× 194 0.8× 147 1.3× 22 0.2× 31 0.3× 44 616
David Wu United States 14 374 1.3× 377 1.6× 40 0.4× 206 2.0× 8 0.1× 28 886
A. Mrabet Tunisia 12 184 0.6× 128 0.6× 179 1.6× 24 0.2× 122 1.2× 59 716
Elizabeth Harris United Kingdom 13 365 1.3× 210 0.9× 105 0.9× 43 0.4× 33 0.3× 30 693
Peter T. Vedell United States 12 329 1.1× 111 0.5× 53 0.5× 20 0.2× 11 0.1× 22 852
Marcio Almeida United States 12 206 0.7× 218 0.9× 17 0.1× 46 0.4× 18 0.2× 43 623
Mari Nelis Estonia 13 183 0.6× 306 1.3× 31 0.3× 15 0.1× 19 0.2× 35 567
Haiqing Xu China 8 217 0.8× 284 1.2× 111 1.0× 35 0.3× 12 0.1× 16 588

Countries citing papers authored by Cheryl L. Gatto

Since Specialization
Citations

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

Fields of papers citing papers by Cheryl L. Gatto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cheryl L. Gatto. 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 Cheryl L. Gatto. The network helps show where Cheryl L. Gatto may publish in the future.

Co-authorship network of co-authors of Cheryl L. Gatto

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

All Works

20 of 20 papers shown
1.
Agarwal, Rajiv, Sumathi Misra, Jill M. Pulley, et al.. (2025). Evaluating Performance of the Surprise Question to Predict 12-Month Mortality in Patients With End-Stage Liver Disease. American Journal of Hospice and Palliative Medicine®. 42(11). 1136–1143.
2.
Lentz, Robert J., Justin K. Siemann, Jonathan D. Casey, et al.. (2025). Robotic versus Electromagnetic Bronchoscopy for Peripheral Pulmonary Lesions: A Randomized Trial (RELIANT). American Journal of Respiratory and Critical Care Medicine. 211(9). 1644–1651. 3 indexed citations
3.
Siemann, Justin K., Jonathan D. Casey, Samira Shojaee, et al.. (2025). Robotic Versus Electromagnetic Navigational Bronchoscopy for Pulmonary Lesion Assessment. Results from the RELIANT Randomized Trial. American Journal of Respiratory and Critical Care Medicine. 211(Supplement_1). A5018–A5018.
4.
5.
Lentz, Robert J., Justin K. Siemann, See‐Wei Low, et al.. (2024). Robotic versus Electromagnetic bronchoscopy for pulmonary LesIon AssessmeNT: the RELIANT pragmatic randomized trial. Trials. 25(1). 66–66. 7 indexed citations
6.
Freiberg, Jeffrey A., Justin K. Siemann, Edward T. Qian, et al.. (2024). Swab Testing to Optimize Pneumonia treatment with empiric Vancomycin (STOP-Vanc): study protocol for a randomized controlled trial. Trials. 25(1). 854–854.
7.
Welch, Lisa C., et al.. (2023). Learning health system benefits: Development and initial validation of a framework. Learning Health Systems. 8(1). e10380–e10380. 2 indexed citations
8.
Yiadom, Maame Yaa A. B., Henry J. Domenico, Daniel W. Byrne, et al.. (2020). Impact of a Follow-up Telephone Call Program on 30-Day Readmissions (FUTR-30). Medical Care. 58(9). 785–792. 8 indexed citations
9.
Driest, Sara L. Van, Li Wang, Brian C. Bridges, et al.. (2019). Acute kidney injury risk-based screening in pediatric inpatients: a pragmatic randomized trial. Pediatric Research. 87(1). 118–124. 6 indexed citations
10.
Shinall, Myrick C., Mohana Karlekar, Sara Martin, et al.. (2019). COMPASS: A Pilot Trial of an Early Palliative Care Intervention for Patients With End-Stage Liver Disease. Journal of Pain and Symptom Management. 58(4). 614–622.e3. 44 indexed citations
11.
12.
Gatto, Cheryl L., et al.. (2015). A fully automated Drosophila olfactory classical conditioning and testing system for behavioral learning and memory assessment. Journal of Neuroscience Methods. 261. 62–74. 11 indexed citations
13.
Gatto, Cheryl L., et al.. (2014). GABAergic circuit dysfunction in the Drosophila Fragile X syndrome model. Neurobiology of Disease. 65. 142–159. 43 indexed citations
14.
Gatto, Cheryl L. & Kendal Broadie. (2011). Fragile X mental retardation protein is required for programmed cell death and clearance of developmentally-transient peptidergic neurons. Developmental Biology. 356(2). 291–307. 26 indexed citations
15.
Gatto, Cheryl L. & Kendal Broadie. (2011). Drosophila modeling of heritable neurodevelopmental disorders. Current Opinion in Neurobiology. 21(6). 834–841. 44 indexed citations
16.
Gatto, Cheryl L. & Kendal Broadie. (2009). The Fragile X Mental Retardation Protein in Circadian Rhythmicity and Memory Consolidation. Molecular Neurobiology. 39(2). 107–129. 33 indexed citations
17.
Gatto, Cheryl L., Barbara J. Walker, & Stephen B. Lambert. (2006). Asymmetric ERM activation at the Schwann cell process tip is required in Axon‐Associated motility. Journal of Cellular Physiology. 210(1). 122–132. 13 indexed citations
18.
Gatto, Cheryl L., Barbara J. Walker, & Stephen B. Lambert. (2003). Local ERM activation and dynamic growth cones at Schwann cell tips implicated in efficient formation of nodes of Ranvier. The Journal of Cell Biology. 162(3). 489–498. 64 indexed citations
19.
Chen, Yu, Norio Takizawa, Jessica L. Crowley, et al.. (2003). F-actin and Myosin II Binding Domains in Supervillin. Journal of Biological Chemistry. 278(46). 46094–46106. 59 indexed citations
20.
Nebl, Thomas, et al.. (2001). Motile Membrane Skeletons: What Neutrophils and Muscle Have in Common.. PubMed. 6(2). 219–219. 1 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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