Chris Gaiteri

7.9k total citations
58 papers, 2.2k citations indexed

About

Chris Gaiteri is a scholar working on Molecular Biology, Physiology and Psychiatry and Mental health. According to data from OpenAlex, Chris Gaiteri has authored 58 papers receiving a total of 2.2k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 19 papers in Physiology and 13 papers in Psychiatry and Mental health. Recurrent topics in Chris Gaiteri's work include Bioinformatics and Genomic Networks (19 papers), Alzheimer's disease research and treatments (16 papers) and Dementia and Cognitive Impairment Research (13 papers). Chris Gaiteri is often cited by papers focused on Bioinformatics and Genomic Networks (19 papers), Alzheimer's disease research and treatments (16 papers) and Dementia and Cognitive Impairment Research (13 papers). Chris Gaiteri collaborates with scholars based in United States, Canada and Sweden. Chris Gaiteri's co-authors include David A. Bennett, Philip L. De Jager, Sara Mostafavi, Etienne Sibille, Lei Yu, Julie A. Schneider, George C. Tseng, Jishu Xu, Shinya Tasaki and Hans‐Ulrich Klein and has published in prestigious journals such as Nature Communications, Neuron and Nature Genetics.

In The Last Decade

Chris Gaiteri

56 papers receiving 2.2k citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Chris Gaiteri 1.1k 698 394 392 315 58 2.2k
Pavel Katsel 1.7k 1.6× 979 1.4× 523 1.3× 478 1.2× 243 0.8× 59 3.2k
Jennifer S. Yokoyama 741 0.7× 790 1.1× 465 1.2× 462 1.2× 508 1.6× 91 2.6k
Silvia Bagnoli 814 0.8× 1.0k 1.5× 342 0.9× 187 0.5× 431 1.4× 135 2.4k
Sarah Bertelsen 601 0.6× 667 1.0× 347 0.9× 315 0.8× 214 0.7× 42 1.6k
M. Axel Wollmer 954 0.9× 1.3k 1.9× 474 1.2× 307 0.8× 351 1.1× 56 2.9k
Annerieke Sierksma 929 0.9× 695 1.0× 514 1.3× 159 0.4× 118 0.4× 26 2.0k
Adrian L. Oblak 815 0.8× 944 1.4× 599 1.5× 361 0.9× 223 0.7× 83 2.3k
Nilüfer Ertekin‐Taner 1.2k 1.1× 1.6k 2.2× 453 1.1× 578 1.5× 646 2.1× 108 2.8k
Daniel Felsky 582 0.5× 496 0.7× 283 0.7× 265 0.7× 376 1.2× 79 1.9k
Rebecca Sims 570 0.5× 722 1.0× 234 0.6× 371 0.9× 294 0.9× 51 1.5k

Countries citing papers authored by Chris Gaiteri

Since Specialization
Citations

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

Fields of papers citing papers by Chris Gaiteri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Chris Gaiteri

This figure shows the co-authorship network connecting the top 25 collaborators of Chris Gaiteri. A scholar is included among the top collaborators of Chris Gaiteri 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 Chris Gaiteri. Chris Gaiteri 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.
Vialle, Ricardo A., Kátia de Paiva Lopes, Li Y, et al.. (2025). Structural variants linked to Alzheimer’s disease and other common age-related clinical and neuropathologic traits. Genome Medicine. 17(1). 20–20. 1 indexed citations
2.
Ng, Bernard, Shinya Tasaki, Kelsey M. Greathouse, et al.. (2024). Integration across biophysical scales identifies molecular and cellular correlates of person-to-person variability in human brain connectivity. Nature Neuroscience. 27(11). 2240–2252. 5 indexed citations
3.
Greathouse, Kelsey M., et al.. (2024). Dendritic spine head diameter predicts episodic memory performance in older adults. Science Advances. 10(32). eadn5181–eadn5181. 2 indexed citations
4.
Gaiteri, Chris, David Connell, Faraz Sultan, et al.. (2023). Robust, scalable, and informative clustering for diverse biological networks. Genome biology. 24(1). 228–228. 3 indexed citations
5.
Kuzmin, Konstantin, et al.. (2023). Network Analytics Enabled by Generating a Pool of Network Variants from Noisy Data. Entropy. 25(8). 1118–1118.
6.
Kearns, Nicola A., Artemis Iatrou, Denis Avey, et al.. (2023). Elucidating Cell Diversity and Functions of Human Brain Borders in Alzheimer’s Disease. Alzheimer s & Dementia. 19(S13). 1 indexed citations
7.
Sasse, Alexander, Bernard Ng, Shinya Tasaki, et al.. (2023). Benchmarking of deep neural networks for predicting personal gene expression from DNA sequence highlights shortcomings. Nature Genetics. 55(12). 2060–2064. 38 indexed citations
8.
Tasaki, Shinya, Jishu Xu, Denis Avey, et al.. (2022). Inferring protein expression changes from mRNA in Alzheimer’s dementia using deep neural networks. Nature Communications. 13(1). 655–655. 49 indexed citations
9.
Patrick, Ellis, Marta Olah, Mariko Taga, et al.. (2021). A cortical immune network map identifies distinct microglial transcriptional programs associated with β-amyloid and Tau pathologies. Translational Psychiatry. 11(1). 50–50. 18 indexed citations
10.
Buchman, Aron S., Lei Yu, Shahram Oveisgharan, et al.. (2021). Cortical proteins may provide motor resilience in older adults. Scientific Reports. 11(1). 11311–11311. 11 indexed citations
11.
Heuer, Sarah E., Sarah M. Neuner, Niran Hadad, et al.. (2020). Identifying the molecular systems that influence cognitive resilience to Alzheimer's disease in genetically diverse mice. Learning & Memory. 27(9). 355–371. 13 indexed citations
12.
Tasaki, Shinya, Chris Gaiteri, Sara Mostafavi, & Yanling Wang. (2020). Deep learning decodes the principles of differential gene expression. Nature Machine Intelligence. 2(7). 376–386. 24 indexed citations
13.
Tasaki, Shinya, Chris Gaiteri, Vladislav Petyuk, et al.. (2019). Genetic risk for Alzheimer’s dementia predicts motor deficits through multi-omic systems in older adults. Translational Psychiatry. 9(1). 241–241. 13 indexed citations
14.
Tasaki, Shinya, Chris Gaiteri, Sara Mostafavi, Philip L. De Jager, & David A. Bennett. (2018). The Molecular and Neuropathological Consequences of Genetic Risk for Alzheimer's Dementia. Frontiers in Neuroscience. 12. 699–699. 39 indexed citations
15.
Yu, Lei, Michael W. Lutz, Robert S. Wilson, et al.. (2017). APOE ε4-TOMM40 ‘523 haplotypes and the risk of Alzheimer’s disease in older Caucasian and African Americans. PLoS ONE. 12(7). e0180356–e0180356. 48 indexed citations
16.
Yang, Jingyun, Lei Yu, Chris Gaiteri, et al.. (2015). Association of DNA methylation in the brain with age in older persons is confounded by common neuropathologies. The International Journal of Biochemistry & Cell Biology. 67. 58–64. 30 indexed citations
17.
Gaiteri, Chris. (2011). Finding the pathology of major depression through effects on gene interaction networks. Optics Letters. 37(4). 452–4. 2 indexed citations
18.
Gaiteri, Chris & Etienne Sibille. (2011). Differentially Expressed Genes in Major Depression Reside on the Periphery of Resilient Gene Coexpression Networks. Frontiers in Neuroscience. 5. 95–95. 31 indexed citations
19.
Gaiteri, Chris, Jean‐Philippe Guilloux, David A. Lewis, & Etienne Sibille. (2010). Altered Gene Synchrony Suggests a Combined Hormone-Mediated Dysregulated State in Major Depression. PLoS ONE. 5(4). e9970–e9970. 36 indexed citations
20.
Sibille, Etienne, Yingjie Wang, Chris Gaiteri, et al.. (2009). A Molecular Signature of Depression in the Amygdala. American Journal of Psychiatry. 166(9). 1011–1024. 160 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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