Ryan T. Cleary

430 total citations
9 papers, 327 citations indexed

About

Ryan T. Cleary is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Pediatrics, Perinatology and Child Health. According to data from OpenAlex, Ryan T. Cleary has authored 9 papers receiving a total of 327 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Cellular and Molecular Neuroscience and 2 papers in Pediatrics, Perinatology and Child Health. Recurrent topics in Ryan T. Cleary's work include Neuroscience and Neuropharmacology Research (4 papers), Inflammation biomarkers and pathways (2 papers) and Neonatal and fetal brain pathology (2 papers). Ryan T. Cleary is often cited by papers focused on Neuroscience and Neuropharmacology Research (4 papers), Inflammation biomarkers and pathways (2 papers) and Neonatal and fetal brain pathology (2 papers). Ryan T. Cleary collaborates with scholars based in United States and Spain. Ryan T. Cleary's co-authors include Gerard T. Berry, Delia M. Talos, Frances E. Jensen, Kristopher T. Kahle, Thanhthao Huynh, Alexander Rotenberg, Simon M. Manning, Michele Jackson, Hongyu Sun and Sanjay N. Rakhade and has published in prestigious journals such as PLoS ONE, Science Advances and Journal of neurosurgery.

In The Last Decade

Ryan T. Cleary

9 papers receiving 323 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ryan T. Cleary United States	7	159	112	112	82	44	9	327
Jiangwei Ding China	10	77 0.5×	108 1.0×	75 0.7×	35 0.4×	17 0.4×	31	335
Diede W. M. Broekaart Netherlands	14	124 0.8×	203 1.8×	92 0.8×	39 0.5×	30 0.7×	21	462
Anu Anttinen Finland	9	141 0.9×	164 1.5×	123 1.1×	88 1.1×	14 0.3×	10	430
Michele Zeinieh Lebanon	9	119 0.7×	117 1.0×	38 0.3×	57 0.7×	7 0.2×	10	278
Philip H. Iffland United States	11	93 0.6×	181 1.6×	107 1.0×	51 0.6×	14 0.3×	17	377
Takehisa Araki Japan	10	138 0.9×	115 1.0×	73 0.7×	25 0.3×	15 0.3×	32	362
Stefania Bassanini Italy	10	204 1.3×	139 1.2×	125 1.1×	145 1.8×	5 0.1×	13	424
Paven K. Aujla United States	7	167 1.1×	167 1.5×	92 0.8×	72 0.9×	6 0.1×	7	342
Olga Cozzolino Italy	7	127 0.8×	74 0.7×	45 0.4×	19 0.2×	38 0.9×	7	317
Dorota Hoffman‐Zacharska Poland	14	169 1.1×	216 1.9×	64 0.6×	39 0.5×	14 0.3×	53	541

Countries citing papers authored by Ryan T. Cleary

Since Specialization

Citations

This map shows the geographic impact of Ryan T. Cleary'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 Ryan T. Cleary with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ryan T. Cleary more than expected).

Fields of papers citing papers by Ryan T. Cleary

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ryan T. Cleary. 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 Ryan T. Cleary. The network helps show where Ryan T. Cleary may publish in the future.

Co-authorship network of co-authors of Ryan T. Cleary

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

All Works

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9 of 9 papers shown

Ishahak, Matthew, Rowland H. Han, Ryan T. Cleary, et al.. (2025). Genetically Engineered Brain Organoids Recapitulate Spatial and Developmental States of Glioblastoma Progression. Advanced Science. 12(10). e2410110–e2410110. 3 indexed citations

Sun, Rui, Rowland H. Han, Saad M. Khan, et al.. (2023). TREM2 inhibition triggers antitumor cell activity of myeloid cells in glioblastoma. Science Advances. 9(19). eade3559–eade3559. 62 indexed citations

Sun, Rui, Rowland H. Han, G. Travis Tabor, et al.. (2023). IMMU-28. TREM2 INHIBITION REPROGRAMS MYELOID CELLS TO STIMULATE ANTI-TUMOR IMMUNITY THROUGH BOTH DIRECT AND INDIRECT MECHANISMS. Neuro-Oncology. 25(Supplement_5). v148–v148. 1 indexed citations

Mao, Diane D., Ryan T. Cleary, Amit D. Gujar, Tatenda Mahlokozera, & Albert H. Kim. (2022). CDC20 regulates sensitivity to chemotherapy and radiation in glioblastoma stem cells. PLoS ONE. 17(6). e0270251–e0270251. 7 indexed citations

Abdulrauf, Saleem I., et al.. (2016). “Awake” clipping of cerebral aneurysms: report of initial series. Journal of neurosurgery. 127(2). 311–318. 32 indexed citations

Loddenkemper, Tobias, Delia M. Talos, Ryan T. Cleary, et al.. (2014). Subunit composition of glutamate and gamma-aminobutyric acid receptors in status epilepticus. Epilepsy Research. 108(4). 605–615. 36 indexed citations

Cleary, Ryan T., Hongyu Sun, Thanhthao Huynh, et al.. (2013). Bumetanide Enhances Phenobarbital Efficacy in a Rat Model of Hypoxic Neonatal Seizures. PLoS ONE. 8(3). e57148–e57148. 111 indexed citations

Cleary, Ryan T., Hongyu Sun, Thanhthao Huynh, et al.. (2013). Correction: Bumetanide Enhances Phenobarbital Efficacy in a Rat Model of Hypoxic Neonatal Seizures. PLoS ONE. 8(8). 28 indexed citations

Cleary, Ryan T., et al.. (2011). Sensitive isotope dilution liquid chromatography/tandem mass spectrometry method for quantitative analysis of bumetanide in serum and brain tissue. Journal of Chromatography B. 879(13-14). 998–1002. 47 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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