Michaël Shum

2.7k total citations · 2 hit papers
35 papers, 1.9k citations indexed

About

Michaël Shum is a scholar working on Molecular Biology, Physiology and Epidemiology. According to data from OpenAlex, Michaël Shum has authored 35 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 12 papers in Physiology and 7 papers in Epidemiology. Recurrent topics in Michaël Shum's work include Adipose Tissue and Metabolism (10 papers), Mitochondrial Function and Pathology (6 papers) and Metabolism, Diabetes, and Cancer (5 papers). Michaël Shum is often cited by papers focused on Adipose Tissue and Metabolism (10 papers), Mitochondrial Function and Pathology (6 papers) and Metabolism, Diabetes, and Cancer (5 papers). Michaël Shum collaborates with scholars based in United States, Canada and Australia. Michaël Shum's co-authors include Marc Liesa, Orian S. Shirihai, André Marette, Jeremy N. Bailenson, David H. Uttal, Rebeca Acín‐Pérez, Essam A. Assali, Anton Petcherski, Michaela Veliova and Marcus F. Oliveira and has published in prestigious journals such as Journal of Biological Chemistry, Nature Communications and Psychological Bulletin.

In The Last Decade

Michaël Shum

35 papers receiving 1.9k citations

Hit Papers

Mitochondria Bound to Lipid Droplets Have Unique Bioenerg... 2017 2026 2020 2023 2018 2017 100 200 300 400

Peers

Michaël Shum
Jessica M. Ellis United States
Philip A. Wood United States
Moyra Smith United States
Leslie Smith United States
Gary L. Wright United States
Kristina Hellberg United States
Michaël Shum
Citations per year, relative to Michaël Shum Michaël Shum (= 1×) peers Simon N. Jacob

Countries citing papers authored by Michaël Shum

Since Specialization
Citations

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

Fields of papers citing papers by Michaël Shum

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michaël Shum

This figure shows the co-authorship network connecting the top 25 collaborators of Michaël Shum. A scholar is included among the top collaborators of Michaël Shum 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 Michaël Shum. Michaël Shum 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.
Berthiaume, Line, Mario Harvey, Bertrand Neveu, et al.. (2023). Isocitrate dehydrogenase 1 sustains a hybrid cytoplasmic–mitochondrial tricarboxylic acid cycle that can be targeted for therapeutic purposes in prostate cancer. Molecular Oncology. 17(10). 2109–2125. 8 indexed citations
2.
Liesa, Marc, et al.. (2023). Quantifying mitochondrial redox and bilirubin content in intact primary hepatocytes of obese mice using fluorescent reporters. STAR Protocols. 4(3). 102408–102408. 1 indexed citations
3.
Krishnan, Karthickeyan Chella, Laurent Vergnes, Rebeca Acín‐Pérez, et al.. (2021). Sex-specific genetic regulation of adipose mitochondria and metabolic syndrome by Ndufv2. Nature Metabolism. 3(11). 1552–1568. 43 indexed citations
4.
Shum, Michaël, Zhiqiang Zhou, & Marc Liesa. (2021). Determining Basal Energy Expenditure and the Capacity of Thermogenic Adipocytes to Expend Energy in Obese Mice. Journal of Visualized Experiments. 1 indexed citations
5.
Veen, J. Edward van, Michaël Shum, Michelle Reid, et al.. (2020). Hypothalamic oestrogen receptor alpha establishes a sexually dimorphic regulatory node of energy expenditure. Nature Metabolism. 2(4). 351–363. 66 indexed citations
6.
Zhang, Zhi, Fernando MCV Reis, Yanlin He, et al.. (2020). Estrogen-sensitive medial preoptic area neurons coordinate torpor in mice. Nature Communications. 11(1). 6378–6378. 60 indexed citations
7.
Ngo, Jennifer, Ilan Y. Benador, Alexandra J. Brownstein, et al.. (2020). Isolation and functional analysis of peridroplet mitochondria from murine brown adipose tissue. STAR Protocols. 2(1). 100243–100243. 14 indexed citations
8.
Shum, Michaël, Jennifer Ngo, Orian S. Shirihai, & Marc Liesa. (2020). Mitochondrial oxidative function in NAFLD: Friend or foe?. Molecular Metabolism. 50. 101134–101134. 76 indexed citations
9.
Krishnan, Karthickeyan Chella, Michaël Shum, Yonghong Meng, et al.. (2019). Sex-specific metabolic functions of adipose Lipocalin-2. Molecular Metabolism. 30. 30–47. 37 indexed citations
10.
Shum, Michaël, Vanessa P. Houde, Rafael Junges Moreira, et al.. (2019). Inhibition of mitochondrial complex 1 by the S6K1 inhibitor PF-4708671 partly contributes to its glucose metabolic effects in muscle and liver cells. Journal of Biological Chemistry. 294(32). 12250–12260. 13 indexed citations
11.
Benador, Ilan Y., Michaela Veliova, Kiana Mahdaviani, et al.. (2018). Mitochondria Bound to Lipid Droplets Have Unique Bioenergetics, Composition, and Dynamics that Support Lipid Droplet Expansion. Cell Metabolism. 27(4). 869–885.e6. 429 indexed citations breakdown →
12.
Kjøbsted, Rasmus, Janne R. Hingst, Joachim Fentz, et al.. (2017). AMPK in skeletal muscle function and metabolism. The FASEB Journal. 32(4). 1741–1777. 352 indexed citations breakdown →
13.
Caron, Alexandre, Sébastien M. Labbé, Blandine Secco, et al.. (2017). Loss of hepatic DEPTOR alters the metabolic transition to fasting. Molecular Metabolism. 6(5). 447–458. 30 indexed citations
14.
Shum, Michaël, Kerstin Bellmann, Philippe St‐Pierre, & André Marette. (2016). Pharmacological inhibition of S6K1 increases glucose metabolism and Akt signalling in vitro and in diet-induced obese mice. Diabetologia. 59(3). 592–603. 43 indexed citations
15.
Noll, Christophe, Sébastien M. Labbé, Michaël Shum, et al.. (2015). Postprandial fatty acid uptake and adipocyte remodeling in angiotensin type 2 receptor-deficient mice fed a high-fat/high-fructose diet. Adipocyte. 5(1). 43–52. 8 indexed citations
16.
Cheung, Belamy B., Owen Tan, Jessica Koach, et al.. (2015). Thymosin‐β4 is a determinant of drug sensitivity for Fenretinide and Vorinostat combination therapy in neuroblastoma. Molecular Oncology. 9(7). 1484–1500. 15 indexed citations
17.
McCarroll, Joshua A., Pei Pei Gan, Rafael B. Erlich, et al.. (2014). TUBB3 /βIII-Tubulin Acts through the PTEN/AKT Signaling Axis to Promote Tumorigenesis and Anoikis Resistance in Non–Small Cell Lung Cancer. Cancer Research. 75(2). 415–425. 80 indexed citations
18.
Shum, Michaël, et al.. (2013). Insulin Activates RSK (p90 Ribosomal S6 Kinase) to Trigger a New Negative Feedback Loop That Regulates Insulin Signaling for Glucose Metabolism. Journal of Biological Chemistry. 288(43). 31165–31176. 20 indexed citations
19.
Xu, Elaine, Michael Schwab, Rita Kohen Avramoglu, et al.. (2013). Hepatocyte-Specific Ptpn6 Deletion Promotes Hepatic Lipid Accretion, but Reduces NAFLD in Diet-Induced Obesity: Potential Role of Pparγ. Hepatology. 59(5). 1803–1815. 31 indexed citations
20.
Bailenson, Jeremy N., Michaël Shum, & David H. Uttal. (2000). The initial segment strategy: A heuristic for route selection. Memory & Cognition. 28(2). 306–318. 75 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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