Núria Mach
Impact in
- Equine top 0.5%
- Animal Science and Zoology top 0.5%
- Animal Nutrition and Physiology
- Meat and Animal Product Quality
Papers in
-
- Gut microbiota and health 25
- Physiology 15
- Diet and metabolism studies 9
- Co-authors
- Allison Clark (9 shared papers)M. Devant (4 shared papers)À. Bach (4 shared papers)Jordi Estellé (7 shared papers)Gaëtan Lemonnier (4 shared papers)Yuliaxis Ramayo‐Caldas (7 shared papers)Claire Rogel Gaillard (5 shared papers)Joël Doré (4 shared papers)
- Journals
- Scientific Reports (8 papers)BMC Genomics (6 papers)Meat Science (4 papers)Frontiers in Physiology (4 papers)Journal of Animal Science (3 papers)
- Partner nations
- FranceSpainNetherlands
In The Last Decade
Núria Mach
102 papers receiving 3.6k citations
Núria Mach's Hit Papers
Peers
Comparison fields: 5 of 153
- Equine 230
- Animal Science and Zoology 656
- Agronomy and Crop Science 491
- Small Animals 314
- Rehabilitation 243
Countries citing papers authored by Núria Mach
This map shows the geographic impact of Núria Mach'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 Núria Mach with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Núria Mach more than expected).
Fields of papers citing papers by Núria Mach
This network shows the impact of papers produced by Núria Mach. 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 Núria Mach. The network helps show where Núria Mach may publish in the future.
Co-authors
The 25 scholars most cited alongside Núria Mach, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 105 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Exercise-induced stress behavior, gut-microbiota-brain axis and diet: a systematic review for athletes Hit paper breakdown → | 2016 | 405 |
| 2 | 2015 | 321 | |
| 3 | 2016 | 263 | |
| 4 | 2017 | 259 | |
| 5 | 2016 | 257 | |
| 6 | 2007 | 169 | |
| 7 | 2008 | 158 | |
| 8 | 2016 | 130 | |
| 9 | 2012 | 116 | |
| 10 | 2006 | 73 | |
| 11 | 2019 | 71 | |
| 12 | 2019 | 61 | |
| 13 | 2017 | 55 | |
| 14 | 2016 | 53 | |
| 15 | 2008 | 53 | |
| 16 | 2018 | 48 | |
| 17 | 2020 | 44 | |
| 18 | 2018 | 41 | |
| 19 | 2017 | 41 | |
| 20 | 2011 | 40 |
About Núria Mach
Núria Mach is a scholar working on Molecular Biology, Physiology, Genetics, Small Animals and Artificial Intelligence, having authored 105 papers that have together received 3.7k indexed citations. Recurring topics across this work include Gut microbiota and health (25 papers), Artificial Intelligence in Law (11 papers), Multi-Agent Systems and Negotiation (11 papers), Semantic Web and Ontologies (10 papers), Veterinary Equine Medical Research (10 papers), Fatty Acid Research and Health (9 papers), Diet and metabolism studies (9 papers) and Ruminant Nutrition and Digestive Physiology (8 papers). The work is most often cited by research in Equine (230 citations), Animal Science and Zoology (656 citations), Agronomy and Crop Science (491 citations), Small Animals (314 citations) and Rehabilitation (243 citations). Núria Mach has collaborated with scholars based in France, Spain and Netherlands. Frequent co-authors include Allison Clark, M. Devant, À. Bach, Jordi Estellé, Gaëtan Lemonnier, Yuliaxis Ramayo‐Caldas, Claire Rogel Gaillard, Joël Doré, Patricia Lepage and Yvon Billon. Their work appears in journals such as Scientific Reports, BMC Genomics, Meat Science, Frontiers in Physiology and Journal of Animal Science.
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.