Matthew E. Ritchie

57.1k total citations · 5 hit papers
117 papers, 31.1k citations indexed

About

Matthew E. Ritchie is a scholar working on Molecular Biology, Genetics and Cancer Research. According to data from OpenAlex, Matthew E. Ritchie has authored 117 papers receiving a total of 31.1k indexed citations (citations by other indexed papers that have themselves been cited), including 84 papers in Molecular Biology, 21 papers in Genetics and 19 papers in Cancer Research. Recurrent topics in Matthew E. Ritchie's work include Gene expression and cancer classification (31 papers), Single-cell and spatial transcriptomics (19 papers) and Molecular Biology Techniques and Applications (15 papers). Matthew E. Ritchie is often cited by papers focused on Gene expression and cancer classification (31 papers), Single-cell and spatial transcriptomics (19 papers) and Molecular Biology Techniques and Applications (15 papers). Matthew E. Ritchie collaborates with scholars based in Australia, United Kingdom and United States. Matthew E. Ritchie's co-authors include Gordon K. Smyth, Charity W. Law, Wei Shi, Yifang Hu, Belinda Phipson, Di Wu, Shian Su, Xueyi Dong, Quentin Gouil and Shanika L. Amarasinghe 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 E. Ritchie

115 papers receiving 30.9k citations

Hit Papers

5 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.

limma powers differential expression analyses for RNA-sequencing and microarray studies

2015 23.6k citations Matthew E. Ritchie, Charity W. Law et al. profile →
Opportunities and challenges in long-read sequencing data analysis

2020 865 citations Shian Su, Xueyi Dong et al. Genome biology profile →
Apoptotic Caspases Suppress mtDNA-Induced STING-Mediated Type I IFN Production

2014 741 citations Matthew E. Ritchie, David C.S. Huang et al. profile →
A comparison of background correction methods for two-colour microarrays

2007 735 citations Matthew E. Ritchie, Gordon K. Smyth et al. Bioinformatics profile →
Systematic comparison of sequencing-based spatial transcriptomic methods

2024 63 citations Yue You, Zhongmin Zhang et al. Nature Methods profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Matthew E. Ritchie Australia	41	18.8k	6.8k	5.4k	5.2k	4.0k	117	31.1k
Charity W. Law Australia	15	16.8k 0.9×	6.5k 1.0×	4.6k 0.9×	5.0k 1.0×	3.6k 0.9×	22	28.0k
Belinda Phipson Australia	25	16.7k 0.9×	6.1k 0.9×	4.7k 0.9×	5.0k 1.0×	3.4k 0.9×	42	27.6k
Yifang Hu Australia	19	15.4k 0.8×	6.2k 0.9×	4.5k 0.8×	4.8k 0.9×	3.9k 1.0×	32	26.0k
Amanda G. Paulovich United States	40	26.0k 1.4×	8.3k 1.2×	6.3k 1.2×	5.6k 1.1×	7.0k 1.7×	87	40.1k
Jian Wang China	79	14.5k 0.8×	6.6k 1.0×	4.4k 0.8×	3.5k 0.7×	5.6k 1.4×	1.1k	28.6k
Michael A. Gillette United States	26	25.8k 1.4×	8.4k 1.2×	6.1k 1.1×	6.1k 1.2×	6.5k 1.6×	45	40.3k
Milan Simonovic Switzerland	9	21.7k 1.2×	5.2k 0.8×	3.5k 0.7×	3.9k 0.8×	2.9k 0.7×	10	33.7k
Nadezhda T. Doncheva Denmark	18	17.1k 0.9×	4.5k 0.7×	3.2k 0.6×	3.6k 0.7×	2.6k 0.6×	33	28.4k
Jian Zhang China	79	15.5k 0.8×	7.5k 1.1×	5.0k 0.9×	4.4k 0.8×	6.7k 1.7×	1.3k	32.7k

Countries citing papers authored by Matthew E. Ritchie

Since Specialization

Citations

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

Fields of papers citing papers by Matthew E. Ritchie

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew E. Ritchie

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew E. Ritchie. A scholar is included among the top collaborators of Matthew E. Ritchie 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 E. Ritchie. Matthew E. Ritchie 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

Du, Mei R. M., Charity W. Law, Daniela Amann‐Zalcenstein, et al.. (2025). Benchmarking spatial transcriptomics technologies with the multi-sample SpatialBenchVisium dataset. Genome biology. 26(1). 77–77. 6 indexed citations

Peng, Hongke, Jafar S. Jabbari, Luyi Tian, et al.. (2025). Single-cell Rapid Capture Hybridization sequencing reliably detects isoform usage and coding mutations in targeted genes. Genome Research. 35(4). 942–955. 1 indexed citations

Montellese, Christian, Matthew E. Ritchie, Monther Alhamdoosh, et al.. (2024). An optimized protocol for quality control of gene therapy vectors using nanopore direct RNA sequencing. Genome Research. 34(11). 1966–1975. 2 indexed citations

You, Yue, Zhongmin Zhang, Shihong Lu, et al.. (2024). Systematic comparison of sequencing-based spatial transcriptomic methods. Nature Methods. 21(9). 1743–1754. 63 indexed citations breakdown →

Liew, Lim Chee, Yue You, Marina Oliva, et al.. (2024). Establishment of single-cell transcriptional states during seed germination. Nature Plants. 10(9). 1418–1434. 20 indexed citations

You, Yue, Xueyi Dong, Mhairi J. Maxwell, et al.. (2023). Modeling group heteroscedasticity in single-cell RNA-seq pseudo-bulk data. Genome biology. 24(1). 107–107. 6 indexed citations

Keniry, Andrew, Natasha Jansz, Peter F. Hickey, et al.. (2022). A method for stabilising the XX karyotype in female mESC cultures. Development. 149(22). 1 indexed citations

Uren, Rachel T., et al.. (2022). NAb-seq: an accurate, rapid, and cost-effective method for antibody long-read sequencing in hybridoma cell lines and single B cells. mAbs. 14(1). 2106621–2106621. 13 indexed citations

Su, Shian, et al.. (2021). Dashboard-style interactive plots for RNA-seq analysis are R Markdown ready with Glimma 2.0. NAR Genomics and Bioinformatics. 3(4). lqab116–lqab116. 5 indexed citations

10.

Dong, Xueyi, Luyi Tian, Quentin Gouil, et al.. (2021). The long and the short of it: unlocking nanopore long-read RNA sequencing data with short-read differential expression analysis tools. NAR Genomics and Bioinformatics. 3(2). lqab028–lqab028. 25 indexed citations

11.

Gouil, Quentin, Sarah Kinkel, Tamara Beck, et al.. (2020). Smchd1 is a maternal effect gene required for genomic imprinting. eLife. 9. 21 indexed citations

12.

Jansz, Natasha, Andrew Keniry, Marie Trussart, et al.. (2018). Smchd1 regulates long-range chromatin interactions on the inactive X chromosome and at Hox clusters. Nature Structural & Molecular Biology. 25(9). 766–777. 70 indexed citations

13.

Weeden, Clare E., Aliaksei Z. Holik, Richard J. Young, et al.. (2017). Cisplatin Increases Sensitivity to FGFR Inhibition in Patient-Derived Xenograft Models of Lung Squamous Cell Carcinoma. Molecular Cancer Therapeutics. 16(8). 1610–1622. 19 indexed citations

14.

Su, Shian, Charity W. Law, Casey Ah-Cann, et al.. (2017). Glimma: interactive graphics for gene expression analysis. Bioinformatics. 33(13). 2050–2052. 105 indexed citations

15.

Law, Charity W., Monther Alhamdoosh, Shian Su, Gordon K. Smyth, & Matthew E. Ritchie. (2016). RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR [version 1; referees: 3 approved]. SHILAP Revista de lepidopterología. 8 indexed citations

16.

Alhamdoosh, Monther, Milica Ng, Nicholas J. Wilson, et al.. (2016). Combining multiple tools outperforms individual methods in gene set enrichment analyses. Bioinformatics. 33(3). 414–424. 120 indexed citations

17.

Oakes, Samantha R., François Vaillant, Elgene Lim, et al.. (2011). Sensitization of BCL-2–expressing breast tumors to chemotherapy by the BH3 mimetic ABT-737. Proceedings of the National Academy of Sciences. 109(8). 2766–2771. 150 indexed citations

18.

Scharpf, Robert B., Rafael A. Irizarry, Matthew E. Ritchie, Benilton S. Carvalho, & Ingo Ruczinski. (2010). USING THE R PACKAGE crlmm FOR GENOTYPING AND COPY NUMBER ESTIMATION. SHILAP Revista de lepidopterología. 3 indexed citations

19.

Dunning, Mark, Matthew E. Ritchie, Nuno L. Barbosa‐Morais, Simon Tavaré, & Andy G. Lynch. (2008). Spike-in validation of an Illumina-specific variance-stabilizing transformation. BMC Research Notes. 1(1). 18–18. 13 indexed citations

20.

Ritchie, Matthew E., et al.. (2004). Gene expression profiling reveals distinct sets of genes altered during hormonally and metabolically induced cardiac hypertrophies. Journal of Molecular and Cellular Cardiology. 37(1). 5 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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