Jonathan Sebat

68.7k total citations · 5 hit papers
62 papers, 7.7k citations indexed

About

Jonathan Sebat is a scholar working on Genetics, Molecular Biology and Cognitive Neuroscience. According to data from OpenAlex, Jonathan Sebat has authored 62 papers receiving a total of 7.7k indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Genetics, 39 papers in Molecular Biology and 11 papers in Cognitive Neuroscience. Recurrent topics in Jonathan Sebat's work include Genomic variations and chromosomal abnormalities (29 papers), Genomics and Rare Diseases (18 papers) and Genetics and Neurodevelopmental Disorders (15 papers). Jonathan Sebat is often cited by papers focused on Genomic variations and chromosomal abnormalities (29 papers), Genomics and Rare Diseases (18 papers) and Genetics and Neurodevelopmental Disorders (15 papers). Jonathan Sebat collaborates with scholars based in United States, United Kingdom and Sweden. Jonathan Sebat's co-authors include Dheeraj Malhotra, Kenny Ye, Michael Wigler, Shane McCarthy, Lilia M. Iakoucheva, Jennifer Troge, John Healy, Robert Lucito, Joan Alexander and Andrew H. Reiner and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Jonathan Sebat

61 papers receiving 7.5k citations

Hit Papers

align trajectories sort by overperformance

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.

Large-Scale Copy Number Polymorphism in the Human Genome

2004 1.8k citations Jonathan Sebat, Jennifer Troge et al. profile →
Modelling schizophrenia using human induced pluripotent stem cells

2011 985 citations Kristen Brennand, Shane McCarthy et al. profile →
Linkage, Association, and Gene-Expression Analyses Identify CNTNAP2 as an Autism-Susceptibility Gene

2008 603 citations Jonathan Sebat, Michael Wigler et al. The American Journal of Human Genetics profile →
CNVs: Harbingers of a Rare Variant Revolution in Psychiatric Genetics

2012 551 citations Dheeraj Malhotra, Jonathan Sebat profile →
Inferring the molecular and phenotypic impact of amino acid variants with MutPred2

2020 426 citations Vikas Pejaver, Jorge Urresti et al. Nature Communications profile →

Author Peers

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

Author						Papers	Cites
Jonathan Sebat	4.7k	4.3k	1.4k	1.1k	681	62	7.7k
Gudrun Rappold	5.1k 1.1×	5.9k 1.4×	652 0.5×	1.1k 1.0×	469 0.7×	216	10.0k
Santhosh Girirajan	3.4k 0.7×	2.5k 0.6×	1.0k 0.7×	596 0.6×	251 0.4×	82	5.0k
Janine M. LaSalle	4.3k 0.9×	4.5k 1.0×	2.1k 1.5×	299 0.3×	405 0.6×	142	7.5k
Carl Baker	3.2k 0.7×	2.8k 0.7×	993 0.7×	898 0.8×	267 0.4×	34	5.0k
Alessandra Renieri	4.2k 0.9×	4.1k 0.9×	1.7k 1.2×	269 0.2×	352 0.5×	246	8.2k
Christian R. Marshall	3.2k 0.7×	2.8k 0.7×	1.2k 0.8×	266 0.2×	441 0.6×	142	5.4k
R. Frank Kooy	4.8k 1.0×	4.0k 0.9×	2.5k 1.8×	356 0.3×	248 0.4×	170	6.8k
Brian J. O’Roak	4.7k 1.0×	4.6k 1.1×	1.3k 0.9×	234 0.2×	951 1.4×	36	8.3k
Maja Bućan	2.8k 0.6×	4.1k 0.9×	730 0.5×	546 0.5×	542 0.8×	102	7.3k
T. Conrad Gilliam	4.8k 1.0×	5.4k 1.2×	1.6k 1.2×	1.1k 1.0×	432 0.6×	122	11.3k

Countries citing papers authored by Jonathan Sebat

Since Specialization

Citations

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

Fields of papers citing papers by Jonathan Sebat

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jonathan Sebat

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan Sebat. A scholar is included among the top collaborators of Jonathan Sebat 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 Jonathan Sebat. Jonathan Sebat 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

Guevara, James P., Stephen Tran, Serge Batalov, et al.. (2026). Long-read genome sequencing improves detection and functional interpretation of structural and repeat variants in autism. Cell Genomics. 101186–101186.

Batalov, Serge, Jerica Lenberg, Daniel Helbling, et al.. (2025). Long-Read Genome Sequencing in Clinical Psychiatry: RFX3 Haploinsufficiency in a Hospitalized Adolescent With Autism, Intellectual Disability, and Behavioral Decompensation. American Journal of Psychiatry. 182(8). 722–727. 1 indexed citations

Maihofer, Adam X., Andrew Ratanatharathorn, Sian Hemmings, et al.. (2024). Effects of genetically predicted posttraumatic stress disorder on autoimmune phenotypes. Translational Psychiatry. 14(1). 172–172. 6 indexed citations

Kimura, Hiroki, Masahiro Nakatochi, Branko Aleksić, et al.. (2022). Exome sequencing analysis of Japanese autism spectrum disorder case-control sample supports an increased burden of synaptic function-related genes. Translational Psychiatry. 12(1). 265–265. 8 indexed citations

Antaki, Danny, James P. Guevara, Adam X. Maihofer, et al.. (2022). A phenotypic spectrum of autism is attributable to the combined effects of rare variants, polygenic risk and sex. Nature Genetics. 54(9). 1284–1292. 110 indexed citations

Guevara, James P., et al.. (2021). Customized de novo mutation detection for any variant calling pipeline: SynthDNM. Bioinformatics. 37(20). 3640–3641. 3 indexed citations

Pramod, Akula Bala, Nam‐Kyung Yu, Lily R. Qiu, et al.. (2021). Autism-linked Cullin3 germline haploinsufficiency impacts cytoskeletal dynamics and cortical neurogenesis through RhoA signaling. Molecular Psychiatry. 26(7). 3586–3613. 33 indexed citations

Urresti, Jorge, Pan Zhang, Patricia Moran‐Losada, et al.. (2021). Cortical organoids model early brain development disrupted by 16p11.2 copy number variants in autism. Molecular Psychiatry. 26(12). 7560–7580. 74 indexed citations

Pejaver, Vikas, Jorge Urresti, Jose Lugo-Martinez, et al.. (2020). Inferring the molecular and phenotypic impact of amino acid variants with MutPred2. Nature Communications. 11(1). 5918–5918. 426 indexed citations breakdown →

10.

Noor, Amina, et al.. (2020). The effects of common structural variants on 3D chromatin structure. BMC Genomics. 21(1). 95–95. 18 indexed citations

11.

Heckerman, David, Ali Torkamani, Li Yin, et al.. (2019). Ranking of non-coding pathogenic variants and putative essential regions of the human genome. Nature Communications. 10(1). 52 indexed citations

12.

Grochowski, Christopher M., Shen Gu, Bo Yuan, et al.. (2018). Marker chromosome genomic structure and temporal origin implicate a chromoanasynthesis event in a family with pleiotropic psychiatric phenotypes. Human Mutation. 39(7). 939–946. 19 indexed citations

13.

Antaki, Danny, William M. Brandler, & Jonathan Sebat. (2017). SV2: accurate structural variation genotyping and de novo mutation detection from whole genomes. Bioinformatics. 34(10). 1774–1777. 29 indexed citations

14.

Lin, Guan Ning, Roser Corominas, Irma Lemmens, et al.. (2015). Spatiotemporal 16p11.2 Protein Network Implicates Cortical Late Mid-Fetal Brain Development and KCTD13-Cul3-RhoA Pathway in Psychiatric Diseases. Neuron. 85(4). 742–754. 103 indexed citations

15.

Koren, Amnon, Paz Polak, James Nemesh, et al.. (2012). Differential Relationship of DNA Replication Timing to Different Forms of Human Mutation and Variation. The American Journal of Human Genetics. 91(6). 1033–1040. 161 indexed citations

16.

Walsh, Tom, Sarah B. Pierce, Danielle R. Lenz, et al.. (2010). Genomic Duplication and Overexpression of TJP2/ZO-2 Leads to Altered Expression of Apoptosis Genes in Progressive Nonsyndromic Hearing Loss DFNA51. The American Journal of Human Genetics. 87(1). 101–109. 74 indexed citations

17.

Yoon, Seungtai, Zhenyu Xuan, Vladimir Makarov, Kenny Ye, & Jonathan Sebat. (2009). Sensitive and accurate detection of copy number variants using read depth of coverage. Genome Research. 19(9). 1586–1592. 424 indexed citations

18.

Gordon, Derek, et al.. (2008). Computing Power and Sample Size for Case-Control Association Studies with Copy Number Polymorphism: Application of Mixture-Based Likelihood Ratio Test. PLoS ONE. 3(10). e3475–e3475. 10 indexed citations

19.

Zhao, Xiaoyue, Anthony Leotta, Vlad Kustanovich, et al.. (2007). A unified genetic theory for sporadic and inherited autism. Proceedings of the National Academy of Sciences. 104(31). 12831–12836. 223 indexed citations

20.

Jobanputra, Vaidehi, Jonathan Sebat, Jennifer Troge, et al.. (2005). Application of ROMA (representational oligonucleotide microarray analysis) to patients with cytogenetic rearrangements. Genetics in Medicine. 7(2). 111–118. 26 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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