Matthew H. Sharp

39 papers receiving 1.4k citations

Matthew H. Sharp's Hit Papers

DrugBank 6.0: the DrugBank Knowledgebase for 2024 2023 · 927 citations
9270+1+2Years since publication250500750

Peers

Matthew H. Sharp
Comparison fields: 5 of 140
  • Computational Theory and Mathematics 253
  • Agronomy and Crop Science 100
  • Cell Biology 158
  • Physiology 216
  • Animal Science and Zoology 87
Replace Min Tian with:
Min Tian China
CLIVE J. DIX United Kingdom
Yuri B. Porozov Russia
Weimin Guo United States
Haitian Ma China
Barbara Zdzisińska Poland
Anil Kumar Balapure India
Karl‐Heinz Storbeck South Africa
Carole Migné France
Guiping Zhang China
Matthew H. Sharp relative to Min Tian China Min Tian's profile →
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Countries citing papers authored by Matthew H. Sharp

Since Specialization
Citations

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

Fields of papers citing papers by Matthew H. Sharp

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Matthew H. Sharp. 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 Matthew H. Sharp. The network helps show where Matthew H. Sharp may publish in the future.

Co-authors

The 25 scholars most cited alongside Matthew H. Sharp, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Matthew H. Sharp Line = papers co-authored together Matthew H. Sharp links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 43 papers — load more, or switch the sort, to bring in the rest.

#Work
1
DrugBank 6.0: the DrugBank Knowledgebase for 2024
Hit paper breakdown →
2023927
2 1980166
3 2017100
4 201724
5 201723
6 201618
7 201417
8 202115
9 202115
10 201815
11 202214
12 201513
13 202113
14 201412
15 202112
16 201612
17 201611
18 20209
19 20197
20 20147

About Matthew H. Sharp

Matthew H. Sharp is a scholar working on Orthopedics and Sports Medicine, Cell Biology, Rehabilitation, Physiology and Endocrinology, Diabetes and Metabolism, having authored 43 papers that have together received 1.5k indexed citations. Recurring topics across this work include Muscle metabolism and nutrition (12 papers), Sports Performance and Training (8 papers), Diet and metabolism studies (7 papers), Exercise and Physiological Responses (6 papers), Diet, Metabolism, and Disease (3 papers), Sports Dynamics and Biomechanics (2 papers), Protein Hydrolysis and Bioactive Peptides (2 papers) and Muscle Physiology and Disorders (2 papers). The work is most often cited by research in Computational Theory and Mathematics (253 citations), Agronomy and Crop Science (100 citations), Cell Biology (158 citations), Physiology (216 citations) and Animal Science and Zoology (87 citations). Matthew H. Sharp has collaborated with scholars based in United States, Türkiye and France. Frequent co-authors include Jennifer Collins Taylor, R.L. Baldwin, N.E. Smith, Ryan P. Lowery, Jacob M. Wilson, Kevin A. Shields, Michael D. Roberts, Jordan M. Joy, Dominic P. D’Agostino and Jeff S. Volek. Their work appears in journals such as Journal of the International Society of Sports Nutrition, Nutrients, The Journal of Strength and Conditioning Research, Journal of the American College of Nutrition and Current Developments in Nutrition.

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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