M. Grace Gordon

1.8k total citations · 1 hit paper
8 papers, 405 citations indexed

About

M. Grace Gordon is a scholar working on Molecular Biology, Immunology and Computational Mathematics. According to data from OpenAlex, M. Grace Gordon has authored 8 papers receiving a total of 405 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Immunology and 1 paper in Computational Mathematics. Recurrent topics in M. Grace Gordon's work include RNA modifications and cancer (3 papers), Single-cell and spatial transcriptomics (3 papers) and Immune Cell Function and Interaction (2 papers). M. Grace Gordon is often cited by papers focused on RNA modifications and cancer (3 papers), Single-cell and spatial transcriptomics (3 papers) and Immune Cell Function and Interaction (2 papers). M. Grace Gordon collaborates with scholars based in United States, Australia and Netherlands. M. Grace Gordon's co-authors include Chun Ye, Anne Senabouth, Thomas R. Taylor, José Alquicira-Hernández, Alex W. Hewitt, Kirsten A. Fairfax, Antonia C. Rowson, Kristof Wing, Qinyi Lu and Christine Chen and has published in prestigious journals such as Science, Nature Communications and Nature Biotechnology.

In The Last Decade

M. Grace Gordon

8 papers receiving 402 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.

Single-cell eQTL mapping identifies cell type–specific genetic control of autoimmune disease

2022 228 citations Seyhan Yazar, José Alquicira-Hernández et al. Science profile →

Peers

M. Grace Gordon

MB

GENET

IMMUN

CR

EPIDE

Kristof Wing Australia

Diego Calderon United States

Cecilia Domínguez Conde Austria

Pratyaydipta Rudra United States

Vlad C. Seitan United Kingdom

Nathaniel D. Tippens United States

Nikolina Nakić United Kingdom

Theodore G. Drivas United States

Marsha Myrthil United States

Lindsay M. Payer United States

Kristof Wing Australia

M. Grace Gordon

247 ×0.8

MB

86 ×0.8

GENET

67 ×0.7

IMMUN

43 ×0.9

CR

19 ×0.9

EPIDE

Citations per year, relative to M. Grace Gordon M. Grace Gordon (= 1×) peers Kristof Wing

Countries citing papers authored by M. Grace Gordon

Since Specialization

Citations

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

Fields of papers citing papers by M. Grace Gordon

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Grace Gordon. 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 M. Grace Gordon. The network helps show where M. Grace Gordon may publish in the future.

Co-authorship network of co-authors of M. Grace Gordon

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

All Works

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8 of 8 papers shown

1.

Strober, Benjamin J., Guanghao Qi, M. Grace Gordon, et al.. (2024). SURGE: uncovering context-specific genetic-regulation of gene expression from single-cell RNA sequencing using latent-factor models. Genome biology. 25(1). 28–28. 4 indexed citations

2.

Gordon, M. Grace, Richard K. Perez, Evan Biederstedt, et al.. (2024). Coordinated, multicellular patterns of transcriptional variation that stratify patient cohorts are revealed by tensor decomposition. Nature Biotechnology. 43(7). 1192–1201. 8 indexed citations

3.

Yazar, Seyhan, José Alquicira-Hernández, Kristof Wing, et al.. (2022). Single-cell eQTL mapping identifies cell type–specific genetic control of autoimmune disease. Science. 376(6589). eabf3041–eabf3041. 228 indexed citations breakdown →

4.

Oelen, Roy, Dylan H. de Vries, Harm Brugge, et al.. (2022). Single-cell RNA-sequencing of peripheral blood mononuclear cells reveals widespread, context-specific gene expression regulation upon pathogenic exposure. Nature Communications. 13(1). 3267–3267. 53 indexed citations

5.

Gordon, M. Grace, Fumitaka Inoue, Beth Martin, et al.. (2020). lentiMPRA and MPRAflow for high-throughput functional characterization of gene regulatory elements. Nature Protocols. 15(8). 2387–2412. 70 indexed citations

6.

Wu, Anchi, M. Grace Gordon, Lukas Vlahos, et al.. (2019). A suite of automated sequence analyses reduces the number of candidate deleterious variants and reveals a difference between probands and unaffected siblings. Genetics in Medicine. 21(8). 1772–1780. 3 indexed citations

7.

Field, Conroy O., et al.. (2017). Testis-specific ATP synthase peripheral stalk subunits required for tissue-specific mitochondrial morphogenesis in Drosophila. BMC Cell Biology. 18(1). 16–16. 30 indexed citations

8.

Noti, John D., M. Grace Gordon, & Robert E. Hall. (1992). Human p150,95 α-Subunit: Genomic Organization and Analysis of the 5′-Flanking Region. DNA and Cell Biology. 11(2). 123–138. 9 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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