Todd M. Gierahn

3.2k total citations · 1 hit paper
27 papers, 2.0k citations indexed

About

Todd M. Gierahn is a scholar working on Molecular Biology, Immunology and Epidemiology. According to data from OpenAlex, Todd M. Gierahn has authored 27 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 10 papers in Immunology and 7 papers in Epidemiology. Recurrent topics in Todd M. Gierahn's work include Single-cell and spatial transcriptomics (6 papers), T-cell and B-cell Immunology (5 papers) and Pneumonia and Respiratory Infections (4 papers). Todd M. Gierahn is often cited by papers focused on Single-cell and spatial transcriptomics (6 papers), T-cell and B-cell Immunology (5 papers) and Pneumonia and Respiratory Infections (4 papers). Todd M. Gierahn collaborates with scholars based in United States, Netherlands and United Kingdom. Todd M. Gierahn's co-authors include J. Christopher Love, Alex K. Shalek, Marc H. Wadsworth, Mario Roederer, Pratip K. Chattopadhyay, Rahul Satija, Travis K. Hughes, Andrew Butler, Bryan D. Bryson and Sarah M. Fortune and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Clinical Investigation and Nature Communications.

In The Last Decade

Todd M. Gierahn

27 papers receiving 2.0k citations

Hit Papers

Seq-Well: portable, low-cost RNA sequencing of single cel... 2017 2026 2020 2023 2017 100 200 300 400 500
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.

  1. Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput
    2017 593 citations Todd M. Gierahn, Marc H. Wadsworth et al. Nature Methods profile →

Peers

Todd M. Gierahn
Uwe Klemm Germany
Erik Bos Netherlands
Jingping Xie United States
Torunn Elisabeth Tjelle Norway
Katherine McKinnon United States
Claude Backendorf Netherlands
Étienne Weiss France
Anna M. Grabowska United Kingdom
Sudha Kumari United States
Stephan Stremersch Belgium
Uwe Klemm Germany
Todd M. Gierahn
Citations per year, relative to Todd M. Gierahn Todd M. Gierahn (= 1×) peers Uwe Klemm

Countries citing papers authored by Todd M. Gierahn

Since Specialization
Citations

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

Fields of papers citing papers by Todd M. Gierahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Todd M. Gierahn

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

All Works

20 of 20 papers shown
1.
Monian, Brinda, Ang A. Tu, Bert Ruiter, et al.. (2021). Peanut oral immunotherapy differentially suppresses clonally distinct subsets of T helper cells. Journal of Clinical Investigation. 132(2). 60 indexed citations
2.
Rauner, Gat, Dexter X. Jin, Daniel Miller, et al.. (2021). Breast tissue regeneration is driven by cell-matrix interactions coordinating multi-lineage stem cell differentiation through DDR1. Nature Communications. 12(1). 7116–7116. 13 indexed citations
3.
Hughes, Tudor, Marc H. Wadsworth, Todd M. Gierahn, et al.. (2020). Second-Strand Synthesis-Based Massively Parallel scRNA-Seq Reveals Cellular States and Molecular Features of Human Inflammatory Skin Pathologies. Immunity. 53(4). 878–894.e7. 150 indexed citations
4.
Lu, Junjie, Xiaobo Zhu, Jessica E. Shui, et al.. (2020). Rho/SMAD/mTOR triple inhibition enables long-term expansion of human neonatal tracheal aspirate-derived airway basal cell-like cells. Pediatric Research. 89(3). 502–509. 13 indexed citations
5.
Monian, Brinda, Ang A. Tu, Bert Ruiter, et al.. (2020). Peanut Oral Immunotherapy Suppresses Clonally Distinct Subsets of T Helper Cells. SSRN Electronic Journal. 2 indexed citations
6.
Aicher, Toby P., Shaina L. Carroll, Gianmarco Raddi, et al.. (2019). Seq-Well: A Sample-Efficient, Portable Picowell Platform for Massively Parallel Single-Cell RNA Sequencing. Methods in molecular biology. 1979. 111–132. 26 indexed citations
7.
Tu, Ang A., Todd M. Gierahn, Brinda Monian, et al.. (2019). TCR sequencing paired with massively parallel 3′ RNA-seq reveals clonotypic T cell signatures. Nature Immunology. 20(12). 1692–1699. 87 indexed citations
8.
Gierahn, Todd M., Marc H. Wadsworth, Tudor Hughes, et al.. (2017). Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput. Protocol Exchange. 5 indexed citations
9.
Gierahn, Todd M., Marc H. Wadsworth, Travis K. Hughes, et al.. (2017). Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput. Nature Methods. 14(4). 395–398. 593 indexed citations breakdown →
10.
11.
Sun, Zhenyu, Melissa C. Hanson, Michael Zhang, et al.. (2016). Generation of Long-Lived Bone Marrow Plasma Cells Secreting Antibodies Specific for the HIV-1 gp41 Membrane-Proximal External Region in the Absence of Polyreactivity. Journal of Virology. 90(19). 8875–8890. 16 indexed citations
12.
Liao, Mei-Chen, Christina Muratore, Todd M. Gierahn, et al.. (2016). Single-Cell Detection of Secreted Aβ and sAPPα from Human IPSC-Derived Neurons and Astrocytes. Journal of Neuroscience. 36(5). 1730–1746. 76 indexed citations
13.
14.
Chattopadhyay, Pratip K., Todd M. Gierahn, Mario Roederer, & J. Christopher Love. (2014). Single-cell technologies for monitoring immune systems. Nature Immunology. 15(2). 128–135. 291 indexed citations
15.
Yamanaka, Yvonne J., Todd M. Gierahn, & J. Christopher Love. (2012). The dynamic lives of T cells: new approaches and themes. Trends in Immunology. 34(2). 59–66. 14 indexed citations
16.
17.
Li, Yuan, Todd M. Gierahn, Claudette M. Thompson, et al.. (2012). Distinct Effects on Diversifying Selection by Two Mechanisms of Immunity against Streptococcus pneumoniae. PLoS Pathogens. 8(11). e1002989–e1002989. 38 indexed citations
18.
Moffitt, Kristin, Todd M. Gierahn, Ying‐Jie Lu, et al.. (2011). TH17-Based Vaccine Design for Prevention of Streptococcus pneumoniae Colonization. Cell Host & Microbe. 9(2). 158–165. 152 indexed citations
19.
Gunasekera, Anusha, Alissa Myrick, Kevin T. Militello, et al.. (2007). Regulatory motifs uncovered among gene expression clusters in Plasmodium falciparum. Molecular and Biochemical Parasitology. 153(1). 19–30. 26 indexed citations
20.
Rogge, Corina E., et al.. (2003). Insight into the mechanism of aromatic hydroxylation by toluene 4-monooxygenase by use of specifically deuterated toluene and p- xylene. Proceedings of the National Academy of Sciences. 100(7). 3784–3789. 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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