Earl Glynn

2.1k total citations
9 papers, 1.5k citations indexed

About

Earl Glynn is a scholar working on Molecular Biology, Oncology and Physiology. According to data from OpenAlex, Earl Glynn has authored 9 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 1 paper in Oncology and 1 paper in Physiology. Recurrent topics in Earl Glynn's work include Genomics and Chromatin Dynamics (3 papers), Gene Regulatory Network Analysis (2 papers) and Epigenetics and DNA Methylation (2 papers). Earl Glynn is often cited by papers focused on Genomics and Chromatin Dynamics (3 papers), Gene Regulatory Network Analysis (2 papers) and Epigenetics and DNA Methylation (2 papers). Earl Glynn collaborates with scholars based in United States, Germany and United Kingdom. Earl Glynn's co-authors include Arcady Mushegian, Jie Chen, Karin Gaudenz, Olivier Pourquié, Mary‐Lee Dequéant, Matthias Wahl, Douglas Koshland, Paul C. Megee, Jennifer L. Gerton and Hong-Guo Yu and has published in prestigious journals such as Science, Journal of Biological Chemistry and Nature Medicine.

In The Last Decade

Earl Glynn

9 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Earl Glynn United States	8	1.2k	249	242	179	83	9	1.5k
Takaaki Matsui Japan	19	984 0.8×	157 0.6×	197 0.8×	269 1.5×	47 0.6×	72	1.5k
Vincent Bertrand France	19	916 0.8×	124 0.5×	196 0.8×	149 0.8×	146 1.8×	41	1.5k
Daniel E. Newburger United States	12	2.1k 1.7×	231 0.9×	365 1.5×	92 0.5×	79 1.0×	15	2.4k
Nick Burton United Kingdom	20	1.0k 0.9×	120 0.5×	172 0.7×	201 1.1×	44 0.5×	40	1.6k
Paul François Canada	23	1.6k 1.3×	225 0.9×	297 1.2×	391 2.2×	70 0.8×	62	1.9k
Chau Huynh United States	8	1.5k 1.2×	261 1.0×	179 0.7×	206 1.2×	50 0.6×	10	2.2k
J. Kim Dale United Kingdom	20	1.8k 1.4×	157 0.6×	343 1.4×	205 1.1×	39 0.5×	35	2.0k
Miguel Maroto United Kingdom	17	1.1k 0.9×	100 0.4×	186 0.8×	126 0.7×	38 0.5×	22	1.2k
Mihail Sarov Germany	23	1.4k 1.1×	107 0.4×	317 1.3×	180 1.0×	77 0.9×	41	1.9k
John A. Calarco United States	20	2.8k 2.3×	157 0.6×	328 1.4×	108 0.6×	47 0.6×	39	3.2k

Countries citing papers authored by Earl Glynn

Since Specialization

Citations

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

Fields of papers citing papers by Earl Glynn

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Earl Glynn

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

All Works

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9 of 9 papers shown

1.

Roellig, Daniela, Mary‐Lee Dequéant, Olivier Tassy, et al.. (2011). Evolutionary plasticity of segmentation clock networks. Development. 138(13). 2783–2792. 148 indexed citations

2.

Fournier, Marjorie, Ariel Paulson, Norman Pavelka, et al.. (2009). Delayed Correlation of mRNA and Protein Expression in Rapamycin-treated Cells and a Role for Ggc1 in Cellular Sensitivity to Rapamycin. Molecular & Cellular Proteomics. 9(2). 271–284. 134 indexed citations

3.

Roellig, Daniela, Mary‐Lee Dequéant, Olivier Tassy, et al.. (2009). 15-P018 A phase-ordered microarray screen for cyclic genes in zebrafish reveals her genes as the conserved core of the somitogenesis clock. Mechanisms of Development. 126. S252–S253. 2 indexed citations

4.

Ahnert, Sebastian E., Herbert Edelsbrunner, Thomas Fink, et al.. (2008). Comparison of Pattern Detection Methods in Microarray Time Series of the Segmentation Clock. PLoS ONE. 3(8). e2856–e2856. 36 indexed citations

5.

Jones, N C, Karin Gaudenz, Daisuke Sakai, et al.. (2008). Prevention of the neurocristopathy Treacher Collins syndrome through inhibition of p53 function. Nature Medicine. 14(2). 125–133. 324 indexed citations

6.

Zappulla, David C., et al.. (2008). A Flexible Template Boundary Element in the RNA Subunit of Fission Yeast Telomerase. Journal of Biological Chemistry. 283(35). 24224–24233. 31 indexed citations

7.

Dequéant, Mary‐Lee, Earl Glynn, Karin Gaudenz, et al.. (2006). A Complex Oscillating Network of Signaling Genes Underlies the Mouse Segmentation Clock. Science. 314(5805). 1595–1598. 342 indexed citations

8.

Glynn, Earl, Jie Chen, & Arcady Mushegian. (2005). Detecting periodic patterns in unevenly spaced gene expression time series using Lomb–Scargle periodograms. Bioinformatics. 22(3). 310–316. 182 indexed citations

9.

Glynn, Earl, Paul C. Megee, Hong-Guo Yu, et al.. (2004). Genome-Wide Mapping of the Cohesin Complex in the Yeast Saccharomyces cerevisiae. PLoS Biology. 2(9). e259–e259. 342 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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