Suchira Gallage

2.8k total citations · 1 hit paper
10 papers, 273 citations indexed

About

Suchira Gallage is a scholar working on Epidemiology, Molecular Biology and Physiology. According to data from OpenAlex, Suchira Gallage has authored 10 papers receiving a total of 273 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Epidemiology, 3 papers in Molecular Biology and 3 papers in Physiology. Recurrent topics in Suchira Gallage's work include Liver Disease Diagnosis and Treatment (5 papers), Lipid metabolism and disorders (2 papers) and Hepatocellular Carcinoma Treatment and Prognosis (2 papers). Suchira Gallage is often cited by papers focused on Liver Disease Diagnosis and Treatment (5 papers), Lipid metabolism and disorders (2 papers) and Hepatocellular Carcinoma Treatment and Prognosis (2 papers). Suchira Gallage collaborates with scholars based in Germany, United Kingdom and United States. Suchira Gallage's co-authors include Mathias Heikenwälder, Mohammad Rahbari, Jose Efren Barragan Avila, Quentin M. Anstee, Adnan Ali, Enrico Focaccia, Nisar P. Malek, Pierluigi Ramadori, Marta Szydlowska and Gabriel N. Valbuena and has published in prestigious journals such as Nature, Nature Communications and Hepatology.

In The Last Decade

Suchira Gallage

9 papers receiving 270 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 researcher’s guide to preclinical mouse NASH models

2022 105 citations Suchira Gallage, Jose Efren Barragan Avila et al. Nature Metabolism profile →

Peers

Suchira Gallage

EPIDE

MB

PHYSI

EDM

HEPAT

Raúl Jiménez-Agüero Spain

Emelie Barreby Sweden

Fanta Barrow United States

Yuda Wei China

Ren Yamada Japan

Myeong‐Jin Nam South Korea

Carla Frau United States

Yanhao Chen China

Kevin De Muynck Belgium

Kenji Fukumoto Japan

Raúl Jiménez-Agüero Spain

Suchira Gallage

138 ×1.2

EPIDE

95 ×0.8

MB

22 ×0.4

PHYSI

40 ×0.9

EDM

44 ×1.0

HEPAT

Citations per year, relative to Suchira Gallage Suchira Gallage (= 1×) peers Raúl Jiménez-Agüero

Countries citing papers authored by Suchira Gallage

Since Specialization

Citations

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

Fields of papers citing papers by Suchira Gallage

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suchira Gallage

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

All Works

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10 of 10 papers shown

1.

Gallage, Suchira, et al.. (2026). Metabolic dysfunction-associated steatotic liver disease and steatohepatitis-associated hepatocarcinoma preclinical models. Nature Reviews Gastroenterology & Hepatology.

2.

Cuesta‐Zuluaga, Jacobo de la, Patrick Müller, Cordula Gekeler, et al.. (2025). Non-antibiotics disrupt colonization resistance against enteropathogens. Nature. 644(8076). 497–505. 8 indexed citations

3.

Pombo, Joaquim, Bin Sun, Suchira Gallage, et al.. (2024). Detection of senescence using machine learning algorithms based on nuclear features. Nature Communications. 15(1). 1041–1041. 39 indexed citations

4.

Gallage, Suchira, Elaine E. Irvine, Jose Efren Barragan Avila, et al.. (2024). Ribosomal S6 kinase 1 regulates inflammaging via the senescence secretome. Nature Aging. 4(11). 1544–1561. 11 indexed citations

5.

Gallage, Suchira, et al.. (2023). Intermittent fasting—the future treatment in NASH patients?. Hepatology. 78(4). 1290–1305. 17 indexed citations

6.

Gallage, Suchira, Jose Efren Barragan Avila, Pierluigi Ramadori, et al.. (2022). A researcher’s guide to preclinical mouse NASH models. Nature Metabolism. 4(12). 1632–1649. 105 indexed citations breakdown →

7.

Gallage, Suchira, María García‐Beccaria, Marta Szydlowska, et al.. (2021). The therapeutic landscape of hepatocellular carcinoma. Med. 2(5). 505–552. 34 indexed citations

8.

Gallage, Suchira, Adnan Ali, Jose Efren Barragan Avila, et al.. (2021). Spontaneous Cholemia in C57BL/6 Mice Predisposes to Liver Cancer in NASH. Cellular and Molecular Gastroenterology and Hepatology. 13(3). 875–878. 6 indexed citations

9.

Drescher, Hannah K., Angela Schippers, Felix Gremse, et al.. (2020). L-Selectin/CD62L Is a Key Driver of Non-Alcoholic Steatohepatitis in Mice and Men. Cells. 9(5). 1106–1106. 18 indexed citations

10.

Koufaris, Costas, et al.. (2016). Suppression of MTHFD2 in MCF-7 Breast Cancer Cells Increases Glycolysis, Dependency on Exogenous Glycine, and Sensitivity to Folate Depletion. Journal of Proteome Research. 15(8). 2618–2625. 35 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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