Ian R. Lanza
- Physiology top 0.5%
- Adipose Tissue and Metabolism 47
- Diet and metabolism studies 14
- Aging top 1%
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- Cardiovascular and exercise physiology 16
- Rehabilitation top 0.5%
- Exercise and Physiological Responses 10
- Geriatrics and Gerontology top 1%
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- Muscle metabolism and nutrition 24
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- Mitochondrial Function and Pathology 23
- Muscle Physiology and Disorders 13
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- Muscle activation and electromyography studies 10
- Co-authors
- K. Sreekumaran NairJane A. Kent‐BraunSurendra DasariMatthew L. JohnsonMatthew M. RobinsonAntigoni Z. LaliaDavid W. RussBrian A. Irving
- Partner nations
- United StatesChinaItaly
In The Last Decade
Ian R. Lanza
109 papers receiving 6.3k citations
Hit Papers
Peers
Comparison fields: 5 of 145
- Physiology 3.2k
- Aging 184
- Complementary and alternative medicine 676
- Rehabilitation 539
- Geriatrics and Gerontology 267
Countries citing papers authored by Ian R. Lanza
This map shows the geographic impact of Ian R. Lanza'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 Ian R. Lanza with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ian R. Lanza more than expected).
Fields of papers citing papers by Ian R. Lanza
This network shows the impact of papers produced by Ian R. Lanza. 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 Ian R. Lanza. The network helps show where Ian R. Lanza may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Ian R. Lanza, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2024 | 7 | |
| 3 | 2024 | 0 | |
| 4 | 2024 | 2 | |
| 5 | 2022 | 1 | |
| 6 | 2021 | 9 | |
| 7 | 2021 | 50 | |
| 8 | 2020 | 12 | |
| 9 | 2020 | 127 | |
| 10 | 2020 | 15 | |
| 11 | 2020 | 36 | |
| 12 | 2020 | 2 | |
| 13 | 2020 | 9 | |
| 14 | Enhanced Protein Translation Underlies Improved Metabolic and Physical Adaptations to Different Exercise Training Modes in Young and Old Humansbreakdown → | 2017 | 377 |
| 15 | 2017 | 30 | |
| 16 | 2013 | 212 | |
| 17 | A PGC-1α Isoform Induced by Resistance Training Regulates Skeletal Muscle Hypertrophybreakdown → | 2012 | 531 |
| 18 | 2010 | 48 | |
| 19 | 2009 | 9 | |
| 20 | 2006 | 76 |
About Ian R. Lanza
Ian R. Lanza is a scholar working on Aging, Physiology and Complementary and alternative medicine, having authored 112 papers that have together received 6.4k indexed citations. Recurring topics across this work include Adipose Tissue and Metabolism (47 papers), Muscle metabolism and nutrition (24 papers), Mitochondrial Function and Pathology (23 papers), Cardiovascular and exercise physiology (16 papers), Diet and metabolism studies (14 papers), Muscle Physiology and Disorders (13 papers), Muscle activation and electromyography studies (10 papers) and Exercise and Physiological Responses (10 papers). The work is most often cited by research in Physiology (3.2k citations), Aging (184 citations) and Complementary and alternative medicine (676 citations). Ian R. Lanza has collaborated with scholars based in United States, China and Italy. Frequent co-authors include K. Sreekumaran Nair, Jane A. Kent‐Braun, Surendra Dasari, Matthew L. Johnson, Matthew M. Robinson, Antigoni Z. Lalia, David W. Russ, Brian A. Irving, Douglas E. Befroy and Adam R. Konopka. Their work appears in journals such as Cell, Journal of Biological Chemistry and Nature Communications.
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.