A.M. Gutiérrez

2.2k total citations
91 papers, 1.6k citations indexed

About

A.M. Gutiérrez is a scholar working on Animal Science and Zoology, Small Animals and Molecular Biology. According to data from OpenAlex, A.M. Gutiérrez has authored 91 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Animal Science and Zoology, 26 papers in Small Animals and 15 papers in Molecular Biology. Recurrent topics in A.M. Gutiérrez's work include Animal health and immunology (18 papers), Animal Nutrition and Physiology (14 papers) and Microbial infections and disease research (14 papers). A.M. Gutiérrez is often cited by papers focused on Animal health and immunology (18 papers), Animal Nutrition and Physiology (14 papers) and Microbial infections and disease research (14 papers). A.M. Gutiérrez collaborates with scholars based in Spain, Argentina and Austria. A.M. Gutiérrez's co-authors include J. M. Castro Cerón, Silvia Martínez‐Subiela, Damián Escribano, Carmen Cámara, Laura Soler, M. Ángeles Quijano, Fernando Tecles, M.C. Pérez-Conde, Miguel Yus and María Fuentes-Rubio and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and The Journal of Physical Chemistry.

In The Last Decade

A.M. Gutiérrez

87 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
A.M. Gutiérrez Spain 26 470 441 279 221 191 91 1.6k
Mario Gıorgı Italy 26 441 0.9× 920 2.1× 72 0.3× 117 0.5× 367 1.9× 254 2.9k
Anu Rahal India 19 211 0.4× 82 0.2× 233 0.8× 146 0.7× 468 2.5× 74 2.4k
Pilar Hernández Spain 33 1.4k 2.9× 83 0.2× 138 0.5× 62 0.3× 604 3.2× 116 3.2k
Alessandro Di Cerbo Italy 28 430 0.9× 77 0.2× 220 0.8× 76 0.3× 644 3.4× 142 2.3k
Sabry M. El-Bahr Saudi Arabia 20 500 1.1× 413 0.9× 109 0.4× 145 0.7× 176 0.9× 77 1.7k
Sílvia González Monteiro Brazil 26 192 0.4× 369 0.8× 78 0.3× 50 0.2× 494 2.6× 271 2.8k
Phillip S. Miller United States 31 1.7k 3.7× 898 2.0× 344 1.2× 52 0.2× 323 1.7× 123 2.8k
Xinyan Han China 27 472 1.0× 106 0.2× 219 0.8× 63 0.3× 819 4.3× 62 1.9k
Francis D. Galey United States 26 173 0.4× 101 0.2× 172 0.6× 192 0.9× 259 1.4× 70 1.6k
Arthur L. Craigmill United States 23 219 0.5× 288 0.7× 45 0.2× 154 0.7× 158 0.8× 98 1.5k

Countries citing papers authored by A.M. Gutiérrez

Since Specialization
Citations

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

Fields of papers citing papers by A.M. Gutiérrez

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by A.M. Gutiérrez. 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 A.M. Gutiérrez. The network helps show where A.M. Gutiérrez may publish in the future.

Co-authorship network of co-authors of A.M. Gutiérrez

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

All Works

20 of 20 papers shown
1.
Ipharraguerre, Ignacio R., et al.. (2025). Assessing the inflammatory response in horses undergoing gastric ulceration using salivary ADA and S100A12 as biomarkers. Research in Veterinary Science. 190. 105667–105667.
2.
Magaña‐Torres, María Teresa, et al.. (2025). Genotype-Phenotype Correlation and Psychiatric Manifestations in a Case of Phelan-McDermid Syndrome With 22q13.33 Deletion. Cureus. 17(9). e92379–e92379.
3.
Gómez‐Carmona, Carlos D., et al.. (2024). Effects of Congested Matches and Training Schedules on Salivary Markers in Elite Futsal Players. Applied Sciences. 14(12). 4968–4968. 1 indexed citations
4.
5.
Hernández, Ivones, et al.. (2022). The Connection Between Stress and Immune Status in Pigs: A First Salivary Analytical Panel for Disease Differentiation. Frontiers in Veterinary Science. 9. 881435–881435. 11 indexed citations
6.
Fuentes, Noemí, et al.. (2021). A multi-herd study shows that saliva is more than a reflection of serum biomarkers in pigs. animal. 15(12). 100413–100413. 14 indexed citations
7.
8.
Gutiérrez, A.M., A. Montes, Cándido Gutiérrez Panizo, Pablo Cerezuela, & Ernesto de la Cruz Sánchez. (2017). Gender influence on the salivary protein profile of finishing pigs. Journal of Proteomics. 178. 107–113. 12 indexed citations
9.
Gutiérrez, A.M., et al.. (2017). Influence of different sample preparation strategies on the proteomic identification of stress biomarkers in porcine saliva. BMC Veterinary Research. 13(1). 375–375. 13 indexed citations
10.
Gutiérrez, A.M., Ernesto de la Cruz Sánchez, A. Montes, et al.. (2017). Easy and non-invasive disease detection in pigs by adenosine deaminase activity determinations in saliva. PLoS ONE. 12(6). e0179299–e0179299. 18 indexed citations
11.
Sassu, Elena L., J. Catharina Duvigneau, Ingrid Miller, et al.. (2016). Host-pathogen interplay at primary infection sites in pigs challenged with Actinobacillus pleuropneumoniae. BMC Veterinary Research. 13(1). 64–64. 17 indexed citations
12.
Escribano, Damián, A.M. Gutiérrez, Fernando Tecles, & J. M. Castro Cerón. (2015). Changes in saliva biomarkers of stress and immunity in domestic pigs exposed to a psychosocial stressor. Research in Veterinary Science. 102. 38–44. 64 indexed citations
13.
Gutiérrez, A.M., Katharina Nöbauer, Laura Soler, et al.. (2012). Detection of potential markers for systemic disease in saliva of pigs by proteomics: A pilot study. Veterinary Immunology and Immunopathology. 151(1-2). 73–82. 25 indexed citations
14.
Soler, Laura, A.M. Gutiérrez, & J. M. Castro Cerón. (2012). Serum amyloid A measurements in saliva and serum in growing pigs affected by porcine respiratory and reproductive syndrome in field conditions. Research in Veterinary Science. 93(3). 1266–1270. 11 indexed citations
15.
Tvarijonaviciute, Asta, A.M. Gutiérrez, Ingrid Miller, et al.. (2012). A proteomic analysis of serum from dogs before and after a controlled weight-loss program. Domestic Animal Endocrinology. 43(4). 271–277. 12 indexed citations
16.
Escribano, Damián, Laura Soler, A.M. Gutiérrez, Silvia Martínez‐Subiela, & J. M. Castro Cerón. (2012). Measurement of chromogranin A in porcine saliva: validation of a time-resolved immunofluorometric assay and evaluation of its application as a marker of acute stress. animal. 7(4). 640–647. 64 indexed citations
17.
Soler, Laura, Adrian Molenaar, P.D. Eckersall, et al.. (2012). Why working with porcine circulating serum amyloid A is a pig of a job. Journal of Theoretical Biology. 317. 119–125. 12 indexed citations
18.
Gutiérrez, A.M., et al.. (2011). Longitudinal analysis of acute-phase proteins in saliva in pig farms with different health status. animal. 6(2). 321–326. 20 indexed citations
19.
Tvarijonaviciute, Asta, Silvia Martínez‐Subiela, A.M. Gutiérrez, J. M. Castro Cerón, & Fernando Tecles. (2010). Serum acute phase proteins concentrations in dogs during experimentally short-term induced overweight. A preliminary study. Research in Veterinary Science. 90(1). 31–34. 20 indexed citations
20.
Gutiérrez, A.M., Silvia Martínez‐Subiela, A. Montes, M. Parra, & J. M. Castro Cerón. (2008). C-reactive protein measurements in meat juice of pigs. Veterinary Immunology and Immunopathology. 122(3-4). 250–255. 6 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Mario Gıorgı Breakdown of academic impact, for papers by Anu Rahal Breakdown of academic impact, for papers by Pilar Hernández Breakdown of academic impact, for papers by Alessandro Di Cerbo Breakdown of academic impact, for papers by Sabry M. El-Bahr Breakdown of academic impact, for papers by Sílvia González Monteiro Breakdown of academic impact, for papers by Phillip S. Miller Breakdown of academic impact, for papers by Xinyan Han Breakdown of academic impact, for papers by Francis D. Galey Breakdown of academic impact, for papers by Arthur L. Craigmill
Rankless by CCL
2026