Thomas Molina

506 total citations
10 papers, 294 citations indexed

About

Thomas Molina is a scholar working on Molecular Biology, Physiology and Surgery. According to data from OpenAlex, Thomas Molina has authored 10 papers receiving a total of 294 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 4 papers in Physiology and 2 papers in Surgery. Recurrent topics in Thomas Molina's work include Muscle Physiology and Disorders (6 papers), Adipose Tissue and Metabolism (4 papers) and Tissue Engineering and Regenerative Medicine (2 papers). Thomas Molina is often cited by papers focused on Muscle Physiology and Disorders (6 papers), Adipose Tissue and Metabolism (4 papers) and Tissue Engineering and Regenerative Medicine (2 papers). Thomas Molina collaborates with scholars based in Canada, United States and Spain. Thomas Molina's co-authors include Paul Fabre, Nicolas A. Dumont, Junio Dort, Ornella Pellerito, Jean‐François Bilodeau, Eugenia Migliavacca, Sonia Karaz, Sina Nassiri, Patrick Aouad and Ghulam Rehman Mohyuddin and has published in prestigious journals such as Nature Communications, Journal of Clinical Oncology and The EMBO Journal.

In The Last Decade

Thomas Molina

10 papers receiving 294 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Thomas Molina Canada	5	197	93	55	50	49	10	294
Paul Fabre Canada	5	197 1.0×	93 1.0×	56 1.0×	50 1.0×	49 1.0×	8	291
Adelaida R. Palla United States	6	322 1.6×	124 1.3×	58 1.1×	43 0.9×	42 0.9×	8	471
Maria Grazia Berardinelli Italy	8	268 1.4×	117 1.3×	45 0.8×	88 1.8×	76 1.6×	9	385
Wenjun Yang China	13	223 1.1×	45 0.5×	57 1.0×	51 1.0×	58 1.2×	28	393
Matthew Peloquin United States	6	143 0.7×	79 0.8×	35 0.6×	28 0.6×	36 0.7×	13	242
Aurélie Schirmann France	5	162 0.8×	67 0.7×	53 1.0×	35 0.7×	39 0.8×	9	338
Jaeyoon Kim South Korea	6	144 0.7×	87 0.9×	56 1.0×	65 1.3×	110 2.2×	8	323
Paula Fraczek United States	6	310 1.6×	101 1.1×	59 1.1×	43 0.9×	61 1.2×	10	365
Francesca Ascenzi Italy	6	209 1.1×	133 1.4×	36 0.7×	22 0.4×	17 0.3×	7	375
Heiko Steenbock Germany	8	144 0.7×	39 0.4×	77 1.4×	42 0.8×	21 0.4×	13	351

Countries citing papers authored by Thomas Molina

Since Specialization

Citations

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

Fields of papers citing papers by Thomas Molina

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Thomas Molina

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

Fabre, Paul, Thomas Molina, Jessica Gokee LaRose, et al.. (2025). Bioactive lipid mediator class switching regulates myogenic cell progression and muscle regeneration. Nature Communications. 16(1). 5578–5578. 2 indexed citations

Molina, Thomas, Paul Fabre, Ornella Pellerito, et al.. (2024). Transcriptomic and lipidomic profiling reveals distinct bioactive lipid signatures in slow and fast muscles and highlights the role of resolvin‐ D2 in fiber type determination during myogenesis. The FASEB Journal. 38(24). e70250–e70250. 2 indexed citations

Molina, Thomas, et al.. (2023). Physical Activity and Patient-Reported Outcomes in Monoclonal Plasma Cell Disorders. Medicine & Science in Sports & Exercise. 55(11). 1952–1960. 1 indexed citations

Mashinchian, Omid, Filippo De Franceschi, Sina Nassiri, et al.. (2022). An engineered multicellular stem cell niche for the 3D derivation of human myogenic progenitors from iPSCs. The EMBO Journal. 41(14). e110655–e110655. 7 indexed citations

Mohyuddin, Ghulam Rehman, et al.. (2022). A patient perspective on cure in multiple myeloma: A survey of over 1,500 patients.. Journal of Clinical Oncology. 40(16_suppl). 8046–8046. 1 indexed citations

Fabre, Paul, et al.. (2022). Assessment of Muscle Function Following hiPSC‐Derived Myoblast Transplantation in Dystrophic Mice. Current Protocols. 2(1). e356–e356. 4 indexed citations

Molina, Thomas, Paul Fabre, & Nicolas A. Dumont. (2021). Fibro-adipogenic progenitors in skeletal muscle homeostasis, regeneration and diseases. Open Biology. 11(12). 210110–210110. 91 indexed citations

Dort, Junio, Paul Fabre, Thomas Molina, et al.. (2021). Resolvin-D2 targets myogenic cells and improves muscle regeneration in Duchenne muscular dystrophy. Nature Communications. 12(1). 6264–6264. 45 indexed citations

Dort, Junio, Paul Fabre, Thomas Molina, & Nicolas A. Dumont. (2019). Macrophages Are Key Regulators of Stem Cells during Skeletal Muscle Regeneration and Diseases. Stem Cells International. 2019. 1–20. 139 indexed citations

10.

Guerra, Federico, et al.. (1995). [Use of ticlopidine in primary care].. PubMed. 16(3). 137–40. 2 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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