Julie Russeil

1.4k total citations · 1 hit paper
16 papers, 707 citations indexed

About

Julie Russeil is a scholar working on Molecular Biology, Physiology and Epidemiology. According to data from OpenAlex, Julie Russeil has authored 16 papers receiving a total of 707 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 5 papers in Physiology and 4 papers in Epidemiology. Recurrent topics in Julie Russeil's work include Adipose Tissue and Metabolism (4 papers), Adipokines, Inflammation, and Metabolic Diseases (4 papers) and Single-cell and spatial transcriptomics (3 papers). Julie Russeil is often cited by papers focused on Adipose Tissue and Metabolism (4 papers), Adipokines, Inflammation, and Metabolic Diseases (4 papers) and Single-cell and spatial transcriptomics (3 papers). Julie Russeil collaborates with scholars based in Switzerland, Germany and United States. Julie Russeil's co-authors include Bart Deplancke, Daniel Alpern, Petra Schwalie, Magda Zachara, Christian Wolfrum, Hua Dong, Christian Caprara, Gianni Soldati, Wenfei Sun and Vincent Gardeux and has published in prestigious journals such as Nature, Nature Communications and Nature Genetics.

In The Last Decade

Julie Russeil

15 papers receiving 705 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.

A stromal cell population that inhibits adipogenesis in mammalian fat depots

2018 330 citations Petra Schwalie, Hua Dong et al. Nature profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Julie Russeil Switzerland	11	329	296	215	92	82	16	707
Daniel Alpern Switzerland	11	598 1.8×	278 0.9×	209 1.0×	110 1.2×	86 1.0×	15	981
Liam C. Hunt United States	17	415 1.3×	158 0.5×	73 0.3×	33 0.4×	42 0.5×	25	588
Paolo Scudieri Italy	20	575 1.7×	175 0.6×	67 0.3×	50 0.5×	90 1.1×	41	1.0k
Dimos Kapetis Italy	15	531 1.6×	240 0.8×	42 0.2×	87 0.9×	62 0.8×	26	979
Dai Chida Japan	14	226 0.7×	129 0.4×	100 0.5×	131 1.4×	22 0.3×	27	651
Long Jin United States	15	358 1.1×	84 0.3×	142 0.7×	31 0.3×	43 0.5×	27	860
Jesús Garcı́a United States	17	611 1.9×	128 0.4×	158 0.7×	21 0.2×	236 2.9×	29	963
Huibin Tang United States	15	541 1.6×	101 0.3×	71 0.3×	23 0.3×	35 0.4×	23	812
Jessica Cannavino Italy	7	664 2.0×	341 1.2×	57 0.3×	17 0.2×	40 0.5×	9	852
Hong-Chang Tang Canada	6	378 1.1×	106 0.4×	54 0.3×	85 0.9×	36 0.4×	7	777

Countries citing papers authored by Julie Russeil

Since Specialization

Citations

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

Fields of papers citing papers by Julie Russeil

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Julie Russeil

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

All Works

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16 of 16 papers shown

Liu, Wangjie, Wouter Saelens, Pernille Yde Rainer, et al.. (2025). Dissecting the impact of transcription factor dose on cell reprogramming heterogeneity using scTF-seq. Nature Genetics. 57(10). 2522–2535.

Alpern, Daniel, Vincent Gardeux, Julie Russeil, et al.. (2025). Transcriptomic profiling of murine GnRH neurons reveals developmental trajectories linked to human reproduction and infertility. Theranostics. 15(8). 3673–3692. 1 indexed citations

Kribelbauer, Judith F., et al.. (2024). Context transcription factors establish cooperative environments and mediate enhancer communication. Nature Genetics. 56(10). 2199–2212. 4 indexed citations

Rainer, Pernille Yde, Julie Russeil, Magda Zachara, et al.. (2024). A human omentum-specific mesothelial-like stromal population inhibits adipogenesis through IGFBP2 secretion. Cell Metabolism. 36(7). 1566–1585.e9. 9 indexed citations

Pezoldt, Joern, Riccardo Dainese, Antonius Chrisnandy, et al.. (2022). Deterministic scRNA-seq captures variation in intestinal crypt and organoid composition. Nature Methods. 19(3). 323–330. 39 indexed citations

Zachara, Magda, Pernille Yde Rainer, Julie Russeil, et al.. (2022). Mammalian adipogenesis regulator (Areg) cells use retinoic acid signalling to be non‐ and anti‐adipogenic in age‐dependent manner. The EMBO Journal. 41(18). e108206–e108206. 19 indexed citations

Stuelsatz, Pascal, Sonia Karaz, David W. McKellar, et al.. (2022). A Tead1-Apelin axis directs paracrine communication from myogenic to endothelial cells in skeletal muscle. iScience. 25(7). 104589–104589. 15 indexed citations

Pezoldt, Joern, Mangge Zou, Maria Litovchenko, et al.. (2022). Postnatal expansion of mesenteric lymph node stromal cells towards reticular and CD34+ stromal cell subsets. Nature Communications. 13(1). 7227–7227. 8 indexed citations

Kaya-Çopur, Aynur, Marco Y. Hein, Daniel Alpern, et al.. (2021). The Hippo pathway controls myofibril assembly and muscle fiber growth by regulating sarcomeric gene expression. eLife. 10. 32 indexed citations

10.

Litovchenko, Maria, Antonio C.A. Meireles-Filho, Michael Frochaux, et al.. (2021). Extensive tissue-specific expression variation and novel regulators underlying circadian behavior. Science Advances. 7(5). 24 indexed citations

11.

Weger, Meltem, Daniel Alpern, Antoine Cherix, et al.. (2020). Mitochondrial gene signature in the prefrontal cortex for differential susceptibility to chronic stress. Scientific Reports. 10(1). 18308–18308. 50 indexed citations

12.

Chen, Wanze, Petra Schwalie, Carine Gubelmann, et al.. (2019). ZFP30 promotes adipogenesis through the KAP1-mediated activation of a retrotransposon-derived Pparg2 enhancer. Nature Communications. 10(1). 1809–1809. 26 indexed citations

13.

Li, Yongguo, Petra Schwalie, Julie Russeil, et al.. (2019). Systems-Genetics-Based Inference of a Core Regulatory Network Underlying White Fat Browning. Cell Reports. 29(12). 4099–4113.e5. 12 indexed citations

14.

Alpern, Daniel, Vincent Gardeux, Julie Russeil, et al.. (2019). BRB-seq: ultra-affordable high-throughput transcriptomics enabled by bulk RNA barcoding and sequencing. Genome biology. 20(1). 71–71. 121 indexed citations

15.

Schwalie, Petra, Hua Dong, Magda Zachara, et al.. (2018). A stromal cell population that inhibits adipogenesis in mammalian fat depots. Nature. 559(7712). 103–108. 330 indexed citations breakdown →

16.

Pradhan, Rachana, Vincent Gardeux, Petra Schwalie, et al.. (2017). Dissecting the brown adipogenic regulatory network using integrative genomics. Scientific Reports. 7(1). 42130–42130. 17 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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