Isabelle Grass

741 total citations
9 papers, 561 citations indexed

About

Isabelle Grass is a scholar working on Molecular Biology, Immunology and Cell Biology. According to data from OpenAlex, Isabelle Grass has authored 9 papers receiving a total of 561 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 6 papers in Immunology and 4 papers in Cell Biology. Recurrent topics in Isabelle Grass's work include Invertebrate Immune Response Mechanisms (4 papers), Hippo pathway signaling and YAP/TAZ (3 papers) and Viral Infectious Diseases and Gene Expression in Insects (2 papers). Isabelle Grass is often cited by papers focused on Invertebrate Immune Response Mechanisms (4 papers), Hippo pathway signaling and YAP/TAZ (3 papers) and Viral Infectious Diseases and Gene Expression in Insects (2 papers). Isabelle Grass collaborates with scholars based in Germany and United States. Isabelle Grass's co-authors include Alla Berezovskaya, Vassiliki A. Boussiotis, Leonard J. Appleman, Patricia A. Taylor, Bruce R. Blazar, Lee M. Nadler, Gordon J. Freeman, Anne-Kathrin Classen, Andrea Cosolo and Stefan Höning and has published in prestigious journals such as Journal of Biological Chemistry, Nature Medicine and Nature Communications.

In The Last Decade

Isabelle Grass

8 papers receiving 555 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Isabelle Grass Germany	6	315	252	169	104	50	9	561
Karolin Zachmann Germany	11	250 0.8×	258 1.0×	57 0.3×	119 1.1×	58 1.2×	16	553
André Engling Germany	7	205 0.7×	237 0.9×	71 0.4×	108 1.0×	61 1.2×	10	517
Shiuan Wang United States	6	144 0.5×	244 1.0×	98 0.6×	137 1.3×	54 1.1×	6	453
Jason Baum United States	11	141 0.4×	348 1.4×	258 1.5×	50 0.5×	44 0.9×	30	656
Linda Hii Australia	13	204 0.6×	527 2.1×	116 0.7×	147 1.4×	110 2.2×	18	850
Ronit Pasvolsky Israel	11	362 1.1×	284 1.1×	200 1.2×	86 0.8×	23 0.5×	19	769
Tomikazu Arita Japan	8	132 0.4×	245 1.0×	101 0.6×	181 1.7×	22 0.4×	11	486
Hans‐Martin Herz United States	10	131 0.4×	534 2.1×	114 0.7×	268 2.6×	48 1.0×	13	699
Yelena Pavlova United States	11	109 0.3×	437 1.7×	107 0.6×	127 1.2×	50 1.0×	16	628
Ryan Galea Australia	8	95 0.3×	317 1.3×	124 0.7×	270 2.6×	34 0.7×	9	511

Countries citing papers authored by Isabelle Grass

Since Specialization

Citations

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

Fields of papers citing papers by Isabelle Grass

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Isabelle Grass

This figure shows the co-authorship network connecting the top 25 collaborators of Isabelle Grass. A scholar is included among the top collaborators of Isabelle Grass 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 Isabelle Grass. Isabelle Grass 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.

Grass, Isabelle, et al.. (2025). A JAK/STAT-Pdk1-S6K axis bypasses systemic growth restrictions to promote regeneration. Nature Communications. 16(1). 10944–10944.

2.

Engesser, Raphael, et al.. (2023). Mutual repression between JNK/AP-1 and JAK/STAT stratifies senescent and proliferative cell behaviors during tissue regeneration. PLoS Biology. 21(5). e3001665–e3001665. 18 indexed citations

3.

Cosolo, Andrea, et al.. (2022). Distinct signaling signatures drive compensatory proliferation via S-phase acceleration. PLoS Genetics. 18(12). e1010516–e1010516. 5 indexed citations

4.

Cosolo, Andrea, et al.. (2019). JNK-dependent cell cycle stalling in G2 promotes survival and senescence-like phenotypes in tissue stress. eLife. 8. 40 indexed citations

5.

Fortezza, Marco La, et al.. (2016). JAK/STAT signalling mediates cell survival in response to tissue stress. Development. 143(16). 2907–2919. 74 indexed citations

6.

Fortezza, Marco La, et al.. (2016). JAK/STAT signalling mediates cell survival in response to tissue stress. Journal of Cell Science. 129(17). e1.1–e1.1. 2 indexed citations

7.

Grass, Isabelle, et al.. (2004). Recognition of a Basic AP-2 Binding Motif within the C2B Domain of Synaptotagmin Is Dependent on Multimerization. Journal of Biological Chemistry. 279(52). 54872–54880. 60 indexed citations

8.

Appleman, Leonard J., Alla Berezovskaya, Isabelle Grass, & Vassiliki A. Boussiotis. (2000). CD28 Costimulation Mediates T Cell Expansion Via IL-2-Independent and IL-2-Dependent Regulation of Cell Cycle Progression. The Journal of Immunology. 164(1). 144–151. 165 indexed citations

9.

Boussiotis, Vassiliki A., Gordon J. Freeman, Patricia A. Taylor, et al.. (2000). p27kip1 functions as an anergy factor inhibiting interleukin 2 transcription and clonal expansion of alloreactive human and mouse helper T lymphocytes. Nature Medicine. 6(3). 290–297. 197 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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