Jake Gockley

2.4k total citations · 1 hit paper
15 papers, 629 citations indexed

About

Jake Gockley is a scholar working on Molecular Biology, Genetics and Physiology. According to data from OpenAlex, Jake Gockley has authored 15 papers receiving a total of 629 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 7 papers in Genetics and 3 papers in Physiology. Recurrent topics in Jake Gockley's work include Bioinformatics and Genomic Networks (7 papers), Genetic Associations and Epidemiology (4 papers) and Epigenetics and DNA Methylation (4 papers). Jake Gockley is often cited by papers focused on Bioinformatics and Genomic Networks (7 papers), Genetic Associations and Epidemiology (4 papers) and Epigenetics and DNA Methylation (4 papers). Jake Gockley collaborates with scholars based in United States and China. Jake Gockley's co-authors include Benjamin A. Logsdon, Thomas S. Wingo, Aliza P. Wingo, Ekaterina S. Gerasimov, James P. Noonan, Steven K. Reilly, Yue Liu, Allan I. Levey, Nicholas T. Seyfried and Philip L. De Jager and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Genetics and Blood.

In The Last Decade

Jake Gockley

15 papers receiving 628 citations

Hit Papers

Integrating human brain proteomes with genome-wide associ... 2021 2026 2022 2024 2021 50 100 150 200
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.

  1. Integrating human brain proteomes with genome-wide association data implicates new proteins in Alzheimer’s disease pathogenesis
    2021 201 citations Aliza P. Wingo, Yue Liu et al. Nature Genetics profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jake Gockley United States 10 392 224 98 56 56 15 629
Andrew B. Singleton United States 4 348 0.9× 306 1.4× 124 1.3× 65 1.2× 51 0.9× 6 643
Wen‐Ning Zhao United States 16 545 1.4× 104 0.5× 120 1.2× 23 0.4× 24 0.4× 23 800
Г. И. Коровайцева Russia 13 293 0.7× 132 0.6× 169 1.7× 104 1.9× 91 1.6× 86 772
Perla Cota Germany 6 576 1.5× 267 1.2× 155 1.6× 58 1.0× 92 1.6× 8 859
Zane Zeier United States 17 682 1.7× 208 0.9× 63 0.6× 80 1.4× 49 0.9× 25 1.1k
Janet Harwood United Kingdom 14 785 2.0× 192 0.9× 73 0.7× 26 0.5× 27 0.5× 26 1.1k
Kelley Faber United States 6 325 0.8× 170 0.8× 241 2.5× 63 1.1× 60 1.1× 9 574
Patrícia Natália Silva Brazil 14 315 0.8× 123 0.5× 124 1.3× 24 0.4× 30 0.5× 17 502
Shabeesh Balan Japan 16 290 0.7× 131 0.6× 56 0.6× 36 0.6× 25 0.4× 35 577
Jiebiao Wang United States 15 355 0.9× 129 0.6× 38 0.4× 47 0.8× 51 0.9× 33 563

Countries citing papers authored by Jake Gockley

Since Specialization
Citations

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

Fields of papers citing papers by Jake Gockley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jake Gockley

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

All Works

15 of 15 papers shown
1.
Geller, Evan, Mark Noble, Jake Gockley, et al.. (2024). Massively parallel disruption of enhancers active in human neural stem cells. Cell Reports. 43(2). 113693–113693. 9 indexed citations
2.
Cary, Gregory A., Jesse C. Wiley, Jake Gockley, et al.. (2024). Genetic and multi‐omic risk assessment of Alzheimer's disease implicates core associated biological domains. Alzheimer s & Dementia Translational Research & Clinical Interventions. 10(2). e12461–e12461. 10 indexed citations
3.
Wingo, Thomas S., Ekaterina S. Gerasimov, Yue Liu, et al.. (2022). Integrating human brain proteomes with genome-wide association data implicates novel proteins in post-traumatic stress disorder. Molecular Psychiatry. 27(7). 3075–3084. 17 indexed citations
4.
Wiley, Jesse C., Jessica E. Young, Suman Jayadev, et al.. (2022). Alternative Theory of AD Pathogenesis: Membrane Delimitation of the Histone Acetyltransferase Tip60/Kat5. Alzheimer s & Dementia. 18(S4). 1 indexed citations
5.
Wingo, Thomas S., Yue Liu, Ekaterina S. Gerasimov, et al.. (2021). Brain proteome-wide association study implicates novel proteins in depression pathogenesis. Nature Neuroscience. 24(6). 810–817. 98 indexed citations
6.
Wingo, Aliza P., Yue Liu, Ekaterina S. Gerasimov, et al.. (2021). Integrating human brain proteomes with genome-wide association data implicates new proteins in Alzheimer’s disease pathogenesis. Nature Genetics. 53(2). 143–146. 201 indexed citations breakdown →
7.
Gockley, Jake, Kelsey S. Montgomery, William L. Poehlman, et al.. (2021). Multi-tissue neocortical transcriptome-wide association study implicates 8 genes across 6 genomic loci in Alzheimer’s disease. Genome Medicine. 13(1). 76–76. 42 indexed citations
8.
Uebbing, Severin, Jake Gockley, Steven K. Reilly, et al.. (2020). Massively parallel discovery of human-specific substitutions that alter enhancer activity. Proceedings of the National Academy of Sciences. 118(2). 69 indexed citations
9.
Greenwood, Anna K., Kelsey S. Montgomery, Kara Woo, et al.. (2020). The AD Knowledge Portal: A Repository for Multi‐Omic Data on Alzheimer's Disease and Aging. Current Protocols in Human Genetics. 108(1). e105–e105. 52 indexed citations
10.
Wingo, Aliza P., Yue Liu, Jake Gockley, et al.. (2020). Integrating human brain proteomes and genome‐wide association results implicates new genes in Alzheimer’s disease. Alzheimer s & Dementia. 16(S3). 1 indexed citations
11.
Gockley, Jake, Kenneth Daily, Solveig K. Sieberts, et al.. (2020). Agora: An open platform for exploration of Alzheimer’s disease evidence. Alzheimer s & Dementia. 16(S2). 12 indexed citations
12.
Gockley, Jake, Kelsey S. Montgomery, William L. Poehlman, et al.. (2020). Brain transcriptome wide association study (TWAS) implicates 8 genes across 6 loci in Alzheimer’s disease. Alzheimer s & Dementia. 16(S3). 2 indexed citations
13.
Young, Mary H., Alison Fitch, Frank Schmitz, et al.. (2018). Deep Immunoprofiling of the Bone Marrow Microenvironmental Changes Underlying the Multistep Progression of Multiple Myeloma. Blood. 132(Supplement 1). 243–243. 2 indexed citations
14.
Emera, Deena, Jun Yin, Steven K. Reilly, Jake Gockley, & James P. Noonan. (2016). Origin and evolution of developmental enhancers in the mammalian neocortex. Proceedings of the National Academy of Sciences. 113(19). E2617–26. 66 indexed citations
15.
Gockley, Jake, A. Jeremy Willsey, Shan Dong, et al.. (2015). The female protective effect in autism spectrum disorder is not mediated by a single genetic locus. Molecular Autism. 6(1). 25–25. 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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