Jason Perera

1.4k total citations
10 papers, 235 citations indexed

About

Jason Perera is a scholar working on Immunology, Molecular Biology and Genetics. According to data from OpenAlex, Jason Perera has authored 10 papers receiving a total of 235 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Immunology, 3 papers in Molecular Biology and 3 papers in Genetics. Recurrent topics in Jason Perera's work include T-cell and B-cell Immunology (5 papers), Immune Cell Function and Interaction (5 papers) and Immunotherapy and Immune Responses (3 papers). Jason Perera is often cited by papers focused on T-cell and B-cell Immunology (5 papers), Immune Cell Function and Interaction (5 papers) and Immunotherapy and Immune Responses (3 papers). Jason Perera collaborates with scholars based in United States and Israel. Jason Perera's co-authors include Haochu Huang, Fanyong Meng, Liping Meng, Herman Gudjonson, Shuyin Li, Zhong Zheng, Katharine E. Block, Qiang Wu, Martin Weigert and Anne I. Sperling and has published in prestigious journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Cellular and Molecular Life Sciences.

In The Last Decade

Jason Perera

9 papers receiving 233 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jason Perera United States	6	155	38	37	34	30	10	235
Daniel Álvarez‐Sierra Spain	7	108 0.7×	39 1.0×	51 1.4×	21 0.6×	40 1.3×	9	194
Xiaoni Gao United States	8	163 1.1×	97 2.6×	44 1.2×	18 0.5×	26 0.9×	12	272
Minna Turkkila Sweden	7	77 0.5×	68 1.8×	35 0.9×	22 0.6×	18 0.6×	9	189
Metin Yusuf Gelmez Türkiye	5	136 0.9×	48 1.3×	22 0.6×	10 0.3×	12 0.4×	19	225
Christopher Paluch United Kingdom	4	133 0.9×	57 1.5×	81 2.2×	12 0.4×	21 0.7×	5	203
Alessandra Venanzi Italy	6	110 0.7×	62 1.6×	54 1.5×	22 0.6×	50 1.7×	12	257
Souichiro Nakano Japan	9	229 1.5×	34 0.9×	38 1.0×	8 0.2×	25 0.8×	21	322
Mingke Zheng China	7	156 1.0×	47 1.2×	40 1.1×	12 0.4×	15 0.5×	8	224
Alexandra Roux France	6	59 0.4×	35 0.9×	58 1.6×	10 0.3×	73 2.4×	8	199
Yogesh Kamra United Kingdom	7	133 0.9×	42 1.1×	30 0.8×	7 0.2×	47 1.6×	10	213

Countries citing papers authored by Jason Perera

Since Specialization

Citations

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

Fields of papers citing papers by Jason Perera

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jason Perera

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

All Works

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10 of 10 papers shown

Song, Steven, et al.. (2025). Virtual CRISPR: Can LLMs Predict CRISPR Screen Results?. 354–364.

Thrift, William John, Jason Perera, Sivan Cohen, et al.. (2024). Graph-pMHC: graph neural network approach to MHC class II peptide presentation and antibody immunogenicity. Briefings in Bioinformatics. 25(3). 11 indexed citations

Driessen, Terri M., Christine Lo, Richard Blidner, et al.. (2021). Validation of a liquid biopsy assay with molecular and clinical profiling of circulating tumor DNA. npj Precision Oncology. 5(1). 63–63. 37 indexed citations

Molina, Julian R., William Y. Go, Scott Kopetz, et al.. (2021). 491 BASECAMP-1: an observational study to identify relapsed solid tumor patients with human leukocyte antigen (HLA) loss of heterozygosity (LOH) and leukapheresis for future CAR T-cell therapy. SHILAP Revista de lepidopterología. A522–A522. 3 indexed citations

Perera, Jason, Zhong Zheng, Shuyin Li, et al.. (2016). Self-Antigen-Driven Thymic B Cell Class Switching Promotes T Cell Central Tolerance. Cell Reports. 17(2). 387–398. 38 indexed citations

Perera, Jason & Haochu Huang. (2015). The development and function of thymic B cells. Cellular and Molecular Life Sciences. 72(14). 2657–2663. 34 indexed citations

Shilling, Rebecca A., Jesse W. Williams, Jason Perera, et al.. (2013). Autoreactive T and B Cells Induce the Development of Bronchus-Associated Lymphoid Tissue in the Lung. American Journal of Respiratory Cell and Molecular Biology. 48(4). 406–414. 20 indexed citations

Perera, Jason, Xiao Liu, Yuzhen Zhou, et al.. (2013). Insufficient Autoantigen Presentation and Failure of Tolerance in a Mouse Model of Rheumatoid Arthritis. Arthritis & Rheumatism. 65(11). 2847–2856. 4 indexed citations

Perera, Jason, et al.. (2013). Cloning of a hamster anti-mouse CD79B antibody sequences and identification of a new hamster immunoglobulin lambda constant IGLC gene region. Immunogenetics. 65(6). 473–478. 1 indexed citations

10.

Perera, Jason, Liping Meng, Fanyong Meng, & Haochu Huang. (2013). Autoreactive thymic B cells are efficient antigen-presenting cells of cognate self-antigens for T cell negative selection. Proceedings of the National Academy of Sciences. 110(42). 17011–17016. 87 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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