Matthew T. Weirauch

31.1k total citations · 4 hit papers
136 papers, 8.9k citations indexed

About

Matthew T. Weirauch is a scholar working on Molecular Biology, Immunology and Rheumatology. According to data from OpenAlex, Matthew T. Weirauch has authored 136 papers receiving a total of 8.9k indexed citations (citations by other indexed papers that have themselves been cited), including 85 papers in Molecular Biology, 36 papers in Immunology and 17 papers in Rheumatology. Recurrent topics in Matthew T. Weirauch's work include Genomics and Chromatin Dynamics (29 papers), RNA Research and Splicing (21 papers) and RNA modifications and cancer (14 papers). Matthew T. Weirauch is often cited by papers focused on Genomics and Chromatin Dynamics (29 papers), RNA Research and Splicing (21 papers) and RNA modifications and cancer (14 papers). Matthew T. Weirauch collaborates with scholars based in United States, Canada and United Kingdom. Matthew T. Weirauch's co-authors include Brendan J. Frey, Babak Alipanahi, Andrew Delong, Timothy R. Hughes, Xiaoting Chen, Mihai Albu, Samuel A. Lambert, Laura F. Campitelli, Pratyush Kumar Das and Yimeng Yin and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Nucleic Acids Research.

In The Last Decade

Matthew T. Weirauch

132 papers receiving 8.8k 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.

The Human Transcription Factors

2018 2.0k citations Mihai Albu, Xiaoting Chen et al. profile →
Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning

2015 1.8k citations Matthew T. Weirauch et al. Nature Biotechnology profile →
Temporal transcriptional response to ethylene gas drives growth hormone cross-regulation in Arabidopsis

2013 334 citations Matthew T. Weirauch, Timothy R. Hughes et al. eLife profile →
Gene–environment interactions and their impact on human health

2022 125 citations Andrew VonHandorf, Matthew T. Weirauch et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew T. Weirauch United States	40	6.0k	1.1k	1.1k	831	831	136	8.9k
Pablo Mínguez Spain	27	6.3k 1.1×	860 0.8×	1.0k 0.9×	601 0.7×	1.2k 1.4×	79	9.0k
Yasset Pérez‐Riverol United Kingdom	29	8.0k 1.3×	1.0k 1.0×	842 0.8×	887 1.1×	669 0.8×	86	12.0k
Magnus Åstrand Sweden	11	4.5k 0.8×	620 0.6×	819 0.8×	559 0.7×	1.1k 1.3×	32	7.0k
Kalliopi P. Tsafou Denmark	4	5.1k 0.9×	799 0.7×	727 0.7×	603 0.7×	1.3k 1.6×	4	7.9k
Juan Antonio Vizcaíno United Kingdom	42	9.8k 1.6×	1.1k 1.0×	928 0.9×	1.4k 1.7×	758 0.9×	127	14.4k
Niall J. Lennon United States	30	4.4k 0.7×	1.3k 1.2×	656 0.6×	991 1.2×	944 1.1×	66	8.3k
Stefka Tyanova Germany	17	7.7k 1.3×	1.1k 1.0×	766 0.7×	798 1.0×	888 1.1×	25	11.8k
Jean Muller France	31	5.7k 1.0×	567 0.5×	1.8k 1.7×	533 0.6×	702 0.8×	93	8.4k
Xiaochen Bo China	16	4.7k 0.8×	1.4k 1.3×	782 0.7×	784 0.9×	1.4k 1.7×	43	8.1k
Andrew Keller United States	30	7.9k 1.3×	1.1k 1.0×	788 0.7×	544 0.7×	557 0.7×	65	11.5k

Countries citing papers authored by Matthew T. Weirauch

Since Specialization

Citations

This map shows the geographic impact of Matthew T. Weirauch'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 Matthew T. Weirauch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew T. Weirauch more than expected).

Fields of papers citing papers by Matthew T. Weirauch

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew T. Weirauch. 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 Matthew T. Weirauch. The network helps show where Matthew T. Weirauch may publish in the future.

Co-authorship network of co-authors of Matthew T. Weirauch

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Yoneyama, Yosuke, Ranran Zhang, Mari Maezawa, et al.. (2025). Intercellular mRNA transfer alters the human pluripotent stem cell state. Proceedings of the National Academy of Sciences. 122(4). e2413351122–e2413351122.

Sasse, Alexander, Debashish Ray, Kaitlin U. Laverty, et al.. (2025). A resource of RNA-binding protein motifs across eukaryotes reveals evolutionary dynamics and gene-regulatory function. Nature Biotechnology. 4 indexed citations

Albu, Mihai, Xiaoting Chen, Alexander Sasse, et al.. (2025). CisBP-RNA: a web resource for eukaryotic RNA-binding proteins and their motifs. Nucleic Acids Research. 54(D1). D98–D105. 1 indexed citations

Parameswaran, Sreeja, Lee Edsall, Andrew VonHandorf, et al.. (2024). Human cytomegalovirus infection coopts chromatin organization to diminish TEAD1 transcription factor activity. eLife. 13.

Kim, Taehyeung, Marta Martínez‐Bonet, Qiang Wang, et al.. (2024). Non-coding autoimmune risk variant defines role for ICOS in T peripheral helper cell development. Nature Communications. 15(1). 2150–2150. 8 indexed citations

Parameswaran, Sreeja, Carmy Forney, Charles A. Moore, et al.. (2024). Genome-wide epigenetic profiling and transcriptome analysis in pediatric Obstructive Sleep Apnea: A focus on Black female children. Heliyon. 10(23). e40830–e40830. 1 indexed citations

VonHandorf, Andrew, et al.. (2023). Effector memory T cells induce innate inflammation by triggering DNA damage and a non-canonical STING pathway in dendritic cells. Cell Reports. 42(10). 113180–113180. 16 indexed citations

Wang, Li, Robert M. Rossi, Xiaoting Chen, et al.. (2023). A functional mechanism for a non-coding variant near AGTR2 associated with risk for preterm birth. BMC Medicine. 21(1). 258–258. 1 indexed citations

Chidambaran, Vidya, Xue Zhang, Valentina Pilipenko, et al.. (2021). Methylation Quantitative Trait Locus Analysis of Chronic Postsurgical Pain Uncovers Epigenetic Mediators of Genetic Risk. Epigenomics. 13(8). 613–630. 7 indexed citations

10.

Song, Ran, Yajing Gao, Igor Dozmorov, et al.. (2021). IRF1 governs the differential interferon-stimulated gene responses in human monocytes and macrophages by regulating chromatin accessibility. Cell Reports. 34(12). 108891–108891. 50 indexed citations

11.

Bridges, James P., Parvathi Sudha, Andrew J. Wagner, et al.. (2020). Glucocorticoid regulates mesenchymal cell differentiation required for perinatal lung morphogenesis and function. American Journal of Physiology-Lung Cellular and Molecular Physiology. 319(2). L239–L255. 17 indexed citations

12.

Maezawa, So, Akihiko Sakashita, Masashi Yukawa, et al.. (2020). Super-enhancer switching drives a burst in gene expression at the mitosis-to-meiosis transition. Nature Structural & Molecular Biology. 27(10). 978–988. 43 indexed citations

13.

Chen, Xiaoting, Matthew T. Weirauch, Brandy Ruff, et al.. (2019). TET1 contributes to allergic airway inflammation and regulates interferon and aryl hydrocarbon receptor signaling pathways in bronchial epithelial cells. Scientific Reports. 9(1). 7361–7361. 29 indexed citations

14.

Yukawa, Masashi, Sajjeev Jagannathan, Andrey Kartashov, et al.. (2019). AP-1 activity induced by co-stimulation is required for chromatin opening during T cell activation. The Journal of Experimental Medicine. 217(1). 106 indexed citations

15.

Harley, John B., Xiaoting Chen, Mario Pujato, et al.. (2018). Transcription factors operate across disease loci, with EBNA2 implicated in autoimmunity. Nature Genetics. 50(5). 699–707. 241 indexed citations

16.

Modur, Vishnu, Navneet Singh, Vakul Mohanty, et al.. (2018). Defective transcription elongation in a subset of cancers confers immunotherapy resistance. Nature Communications. 9(1). 4410–4410. 17 indexed citations

17.

Lugt, Bryan Vander, Aly A. Khan, Jason A. Hackney, et al.. (2017). Transcriptional determinants of tolerogenic and immunogenic states during dendritic cell maturation. The Journal of Cell Biology. 216(3). 779–792. 69 indexed citations

18.

Pestle, William J., Brooke E. Crowley, & Matthew T. Weirauch. (2014). Quantifying Inter-Laboratory Variability in Stable Isotope Analysis of Ancient Skeletal Remains. PLoS ONE. 9(7). e102844–e102844. 130 indexed citations

19.

Fang, Jing, Lyndsey Bolanos, Xiaona Liu, et al.. (2014). Myeloid Malignancies with Chromosome 5q Deletions Acquire a Dependency on an Intrachromosomal NF-κB Gene Network. Cell Reports. 8(5). 1328–1338. 49 indexed citations

20.

Gordon, Blair R. G., Yifei Li, Atina G. Coté, et al.. (2011). Structural basis for recognition of AT-rich DNA by unrelated xenogeneic silencing proteins. Proceedings of the National Academy of Sciences. 108(26). 10690–10695. 180 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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