Kelley Paskov

1.4k total citations · 1 hit paper
33 papers, 747 citations indexed

About

Kelley Paskov is a scholar working on Molecular Biology, Cognitive Neuroscience and Epidemiology. According to data from OpenAlex, Kelley Paskov has authored 33 papers receiving a total of 747 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 16 papers in Cognitive Neuroscience and 9 papers in Epidemiology. Recurrent topics in Kelley Paskov's work include Autism Spectrum Disorder Research (16 papers), Virology and Viral Diseases (7 papers) and Genomics and Phylogenetic Studies (5 papers). Kelley Paskov is often cited by papers focused on Autism Spectrum Disorder Research (16 papers), Virology and Viral Diseases (7 papers) and Genomics and Phylogenetic Studies (5 papers). Kelley Paskov collaborates with scholars based in United States, France and Canada. Kelley Paskov's co-authors include Dennis P. Wall, Nate Stockham, Brianna Chrisman, Peter Washington, Jae-Yoon Jung, Maya Varma, Aaron Kline, Elizabeth K. Ruzzo, Jennifer K. Lowe and David A. Prober and has published in prestigious journals such as Cell, Nucleic Acids Research and SHILAP Revista de lepidopterología.

In The Last Decade

Kelley Paskov

33 papers receiving 734 citations

Hit Papers

align trajectories

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.

Inherited and De Novo Genetic Risk for Autism Impacts Shared Networks

2019 257 citations Elizabeth K. Ruzzo, Laura Pérez‐Cano et al. Cell profile →

Peers

Kelley Paskov

GENET

EDUCA

EPIDE

Nate Stockham United States

Jae-Yoon Jung United States

Todd F. DeLuca United States

Jeanne P. Ryan United States

Johannes Schumacher Germany

Christopher W. Bartlett United States

Gilles J. P. Rautureau France

David W. Walker United States

Elizabeth L. Johnson United States

Michael A. Mooney United States

Nate Stockham United States

Kelley Paskov

330 ×1.0

211 ×0.7

191 ×1.0

GENET

102 ×1.0

EDUCA

67 ×0.9

EPIDE

Citations per year, relative to Kelley Paskov Kelley Paskov (= 1×) peers Nate Stockham

Countries citing papers authored by Kelley Paskov

Since Specialization

Citations

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

Fields of papers citing papers by Kelley Paskov

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kelley Paskov

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

All Works

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20 of 20 papers shown

Paskov, Kelley, Brianna Chrisman, Nate Stockham, et al.. (2023). Identifying crossovers and shared genetic material in whole genome sequencing data from families. Genome Research. 33(10). 1747–1756. 2 indexed citations

Washington, Peter, Brianna Chrisman, Émilie Leblanc, et al.. (2022). Crowd annotations can approximate clinical autism impressions from short home videos with privacy protections. Intelligence-Based Medicine. 6. 100056–100056. 8 indexed citations

Kline, Aaron, Onur Cezmi Mutlu, Kelley Paskov, et al.. (2022). The Classification of Abnormal Hand Movement to Aid in Autism Detection: Machine Learning Study. SHILAP Revista de lepidopterología. 7(1). e33771–e33771. 23 indexed citations

Stockham, Nate, Peter Washington, Brianna Chrisman, et al.. (2022). Causal Modeling to Mitigate Selection Bias and Unmeasured Confounding in Internet-Based Epidemiology of COVID-19: Model Development and Validation. JMIR Public Health and Surveillance. 8(7). e31306–e31306. 3 indexed citations

Washington, Peter, Haik Kalantarian, John Kent, et al.. (2022). Improved Digital Therapy for Developmental Pediatrics Using Domain-Specific Artificial Intelligence: Machine Learning Study. JMIR Pediatrics and Parenting. 5(2). e26760–e26760. 17 indexed citations

Varma, Maya, Peter Washington, Brianna Chrisman, et al.. (2022). Identification of Social Engagement Indicators Associated With Autism Spectrum Disorder Using a Game-Based Mobile App: Comparative Study of Gaze Fixation and Visual Scanning Methods. Journal of Medical Internet Research. 24(2). e31830–e31830. 30 indexed citations

Chrisman, Brianna, Kelley Paskov, Nate Stockham, et al.. (2021). Indels in SARS-CoV-2 occur at template-switching hotspots. BioData Mining. 14(1). 20–20. 24 indexed citations

Chrisman, Brianna, Kelley Paskov, Nate Stockham, et al.. (2021). Improved detection of disease-associated gut microbes using 16S sequence-based biomarkers. BMC Bioinformatics. 22(1). 509–509. 8 indexed citations

Washington, Peter, Qandeel Tariq, Émilie Leblanc, et al.. (2021). Crowdsourced privacy-preserved feature tagging of short home videos for machine learning ASD detection. Scientific Reports. 11(1). 7620–7620. 22 indexed citations

10.

Paskov, Kelley, Jae-Yoon Jung, Brianna Chrisman, et al.. (2021). Estimating sequencing error rates using families. BioData Mining. 14(1). 27–27. 6 indexed citations

11.

Washington, Peter, Émilie Leblanc, Kaitlyn Dunlap, et al.. (2020). Precision Telemedicine through Crowdsourced Machine Learning: Testing Variability of Crowd Workers for Video-Based Autism Feature Recognition. Journal of Personalized Medicine. 10(3). 86–86. 24 indexed citations

12.

Sun, Min, Stefano Moretti, Kelley Paskov, et al.. (2020). Game theoretic centrality: a novel approach to prioritize disease candidate genes by combining biological networks with the Shapley value. BMC Bioinformatics. 21(1). 356–356. 11 indexed citations

13.

Washington, Peter, Haik Kalantarian, Qandeel Tariq, et al.. (2019). Validity of Online Screening for Autism: Crowdsourcing Study Comparing Paid and Unpaid Diagnostic Tasks. Journal of Medical Internet Research. 21(5). e13668–e13668. 21 indexed citations

14.

Washington, Peter, Catalin Voss, Aaron Kline, et al.. (2019). Data-Driven Diagnostics and the Potential of Mobile Artificial Intelligence for Digital Therapeutic Phenotyping in Computational Psychiatry. Biological Psychiatry Cognitive Neuroscience and Neuroimaging. 5(8). 759–769. 60 indexed citations

15.

Ruzzo, Elizabeth K., Laura Pérez‐Cano, Jae-Yoon Jung, et al.. (2019). Inherited and De Novo Genetic Risk for Autism Impacts Shared Networks. Cell. 178(4). 850–866.e26. 257 indexed citations breakdown →

16.

Paskov, Kelley & Dennis P. Wall. (2018). A Low Rank Model for Phenotype Imputation in Autism Spectrum Disorder.. PubMed. 2017. 178–187. 4 indexed citations

17.

Engel, Stacia R., Shuai Weng, Gail Binkley, et al.. (2016). From one to many: expanding theSaccharomyces cerevisiaereference genome panel. Database. 2016. baw020–baw020. 8 indexed citations

18.

Song, Giltae, Rama Balakrishnan, Gail Binkley, et al.. (2016). Integration of new alternative reference strain genome sequences into theSaccharomycesgenome database. Database. 2016. baw074–baw074. 13 indexed citations

19.

Hitz, Benjamin C., Stacia R. Engel, Giltae Song, et al.. (2015). TheSaccharomycesGenome Database Variant Viewer. Nucleic Acids Research. 44(D1). D698–D702. 20 indexed citations

20.

Costanzo, Maria C., Stacia R. Engel, Edith D. Wong, et al.. (2013). Saccharomycesgenome database provides new regulation data. Nucleic Acids Research. 42(D1). D717–D725. 50 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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