Jyothi Mula

2.0k total citations · 1 hit paper
15 papers, 1.6k citations indexed

About

Jyothi Mula is a scholar working on Molecular Biology, Physiology and Rehabilitation. According to data from OpenAlex, Jyothi Mula has authored 15 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 9 papers in Physiology and 4 papers in Rehabilitation. Recurrent topics in Jyothi Mula's work include Muscle Physiology and Disorders (11 papers), Nutrition and Health in Aging (6 papers) and Exercise and Physiological Responses (4 papers). Jyothi Mula is often cited by papers focused on Muscle Physiology and Disorders (11 papers), Nutrition and Health in Aging (6 papers) and Exercise and Physiological Responses (4 papers). Jyothi Mula collaborates with scholars based in United States, Japan and South Korea. Jyothi Mula's co-authors include Charlotte A. Peterson, John J. McCarthy, Esther E. Dupont‐Versteegden, Christopher S. Fry, Jonah D. Lee, Janna R. Jackson, Tyler J. Kirby, Kenneth S. Campbell, Karyn A. Esser and Ratchakrit Srikuea and has published in prestigious journals such as Journal of Biological Chemistry, Nature Medicine and Development.

In The Last Decade

Jyothi Mula

15 papers receiving 1.6k citations

Hit Papers

Effective fiber hypertrophy in satellite cell-depleted sk... 2011 2026 2016 2021 2011 100 200 300 400
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.

  1. Effective fiber hypertrophy in satellite cell-depleted skeletal muscle
    2011 490 citations John J. McCarthy, Jyothi Mula et al. Development profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jyothi Mula United States 14 1.2k 598 303 297 274 15 1.6k
Giorgia Pallafacchina Italy 19 2.1k 1.7× 666 1.1× 336 1.1× 244 0.8× 196 0.7× 28 2.5k
Kevin A. Murach United States 30 1.6k 1.3× 1.0k 1.7× 530 1.7× 206 0.7× 369 1.3× 84 2.4k
Mitsunori Miyazaki Japan 15 957 0.8× 441 0.7× 412 1.4× 126 0.4× 232 0.8× 29 1.3k
Angelika Paul New Zealand 10 1.2k 1.0× 602 1.0× 373 1.2× 153 0.5× 213 0.8× 11 1.7k
Christophe Hourdé France 22 1.0k 0.8× 385 0.6× 248 0.8× 134 0.5× 130 0.5× 50 1.3k
Norio Motohashi Japan 20 1.4k 1.1× 324 0.5× 159 0.5× 288 1.0× 115 0.4× 47 1.6k
Cathy M. Gurley United States 14 1.1k 0.9× 504 0.8× 253 0.8× 120 0.4× 236 0.9× 15 1.5k
Ratchakrit Srikuea Thailand 13 722 0.6× 381 0.6× 265 0.9× 130 0.4× 256 0.9× 24 1.2k
Jill A. Rafael‐Fortney United States 23 1.7k 1.4× 525 0.9× 214 0.7× 158 0.5× 334 1.2× 56 2.1k
Luca Madaro Italy 23 1.2k 1.0× 429 0.7× 156 0.5× 258 0.9× 153 0.6× 46 1.7k

Countries citing papers authored by Jyothi Mula

Since Specialization
Citations

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

Fields of papers citing papers by Jyothi Mula

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jyothi Mula

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

All Works

15 of 15 papers shown
1.
Moyer, Adam L., Congshan Sun, Ting Liu, et al.. (2019). Mss51 deletion enhances muscle metabolism and glucose homeostasis in mice. JCI Insight. 4(20). 18 indexed citations
2.
Walton, R. Grace, Kate Kosmac, Jyothi Mula, et al.. (2019). Human skeletal muscle macrophages increase following cycle training and are associated with adaptations that may facilitate growth. Scientific Reports. 9(1). 969–969. 73 indexed citations
3.
Kosmac, Kate, Bailey D. Peck, Jyothi Mula, et al.. (2018). Immunohistochemical Identification of Human Skeletal Muscle Macrophages. BIO-PROTOCOL. 8(12). 61 indexed citations
4.
Chung, Liam, Kaitlyn Sadtler, Shoumyo Majumdar, et al.. (2018). Biological scaffold–mediated delivery of myostatin inhibitor promotes a regenerative immune response in an animal model of Duchenne muscular dystrophy. Journal of Biological Chemistry. 293(40). 15594–15605. 19 indexed citations
5.
Choi, In Young, Jyothi Mula, Tatiana V. Cohen, et al.. (2016). Concordant but Varied Phenotypes among Duchenne Muscular Dystrophy Patient-Specific Myoblasts Derived using a Human iPSC-Based Model. Cell Reports. 15(10). 2301–2312. 127 indexed citations
6.
Lee, Jonah D., Christopher S. Fry, Jyothi Mula, et al.. (2015). Aged Muscle Demonstrates Fiber-Type Adaptations in Response to Mechanical Overload, in the Absence of Myofiber Hypertrophy, Independent of Satellite Cell Abundance. The Journals of Gerontology Series A. 71(4). 461–467. 42 indexed citations
7.
Schroder, Elizabeth A., Brianna D. Harfmann, Xiping Zhang, et al.. (2015). Intrinsic muscle clock is necessary for musculoskeletal health. The Journal of Physiology. 593(24). 5387–5404. 116 indexed citations
8.
Walton, R. Grace, Brian S. Finlin, Jyothi Mula, et al.. (2015). Insulin-resistant subjects have normal angiogenic response to aerobic exercise training in skeletal muscle, but not in adipose tissue. Physiological Reports. 3(6). e12415–e12415. 24 indexed citations
9.
Fry, Christopher S., Jonah D. Lee, Jyothi Mula, et al.. (2014). Inducible depletion of satellite cells in adult, sedentary mice impairs muscle regenerative capacity without affecting sarcopenia. Nature Medicine. 21(1). 76–80. 335 indexed citations
10.
Fry, Christopher S., Brian Noehren, Jyothi Mula, et al.. (2014). Fibre type‐specific satellite cell response to aerobic training in sedentary adults. The Journal of Physiology. 592(12). 2625–2635. 107 indexed citations
11.
Liu, Fujun, Christopher S. Fry, Jyothi Mula, et al.. (2013). Automated fiber-type-specific cross-sectional area assessment and myonuclei counting in skeletal muscle. Journal of Applied Physiology. 115(11). 1714–1724. 32 indexed citations
12.
Mula, Jyothi, Christopher S. Fry, Tyler J. Kirby, et al.. (2013). Sarcopenia and hypertrophy in aged skeletal muscle is independent of lifelong muscle stem cell depletion. The FASEB Journal. 27(S1). 1 indexed citations
13.
Jackson, Janna R., Jyothi Mula, Tyler J. Kirby, et al.. (2012). Satellite cell depletion does not inhibit adult skeletal muscle regrowth following unloading-induced atrophy. American Journal of Physiology-Cell Physiology. 303(8). C854–C861. 119 indexed citations
14.
Mula, Jyothi, Jonah D. Lee, Fujun Liu, Lin Yang, & Charlotte A. Peterson. (2012). Automated image analysis of skeletal muscle fiber cross-sectional area. Journal of Applied Physiology. 114(1). 148–155. 51 indexed citations
15.
McCarthy, John J., Jyothi Mula, Mitsunori Miyazaki, et al.. (2011). Effective fiber hypertrophy in satellite cell-depleted skeletal muscle. Development. 138(17). 3657–3666. 490 indexed citations breakdown →

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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