Massimo Bionaz

7.6k total citations · 2 hit papers
130 papers, 6.1k citations indexed

About

Massimo Bionaz is a scholar working on Agronomy and Crop Science, Molecular Biology and Genetics. According to data from OpenAlex, Massimo Bionaz has authored 130 papers receiving a total of 6.1k indexed citations (citations by other indexed papers that have themselves been cited), including 50 papers in Agronomy and Crop Science, 47 papers in Molecular Biology and 41 papers in Genetics. Recurrent topics in Massimo Bionaz's work include Reproductive Physiology in Livestock (34 papers), Genetic and phenotypic traits in livestock (30 papers) and Peroxisome Proliferator-Activated Receptors (21 papers). Massimo Bionaz is often cited by papers focused on Reproductive Physiology in Livestock (34 papers), Genetic and phenotypic traits in livestock (30 papers) and Peroxisome Proliferator-Activated Receptors (21 papers). Massimo Bionaz collaborates with scholars based in United States, Italy and China. Massimo Bionaz's co-authors include Juan J. Loor, Erminio Trevisi, Giuseppe Bertoni, J.K. Drackley, Sandra L. Rodriguez‐Zas, Xuefeng Han, J. S. Osorio, Sebastiano Busato, Matthew B. Wheeler and Harris A. Lewin and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Journal of Agricultural and Food Chemistry.

In The Last Decade

Massimo Bionaz

126 papers receiving 5.9k citations

Hit Papers

Gene networks driving bov... 2008 2026 2014 2020 2008 2008 200 400 600

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Massimo Bionaz 2.9k 2.0k 1.8k 1.1k 1.0k 130 6.1k
B.A. Corl 2.8k 1.0× 1.1k 0.5× 977 0.5× 288 0.3× 3.0k 2.8× 90 5.5k
Christine Leroux 1.7k 0.6× 1.7k 0.8× 1.2k 0.6× 481 0.4× 1.3k 1.3× 96 4.0k
A.L. Lock 4.2k 1.5× 2.1k 1.0× 640 0.4× 217 0.2× 3.1k 3.0× 161 6.7k
Marcello Mele 2.4k 0.8× 1.3k 0.7× 683 0.4× 421 0.4× 1.3k 1.3× 238 5.3k
Jörg R. Aschenbach 3.0k 1.0× 1.1k 0.5× 1.4k 0.8× 176 0.2× 648 0.6× 154 5.7k
J.K. Drackley 9.6k 3.3× 4.6k 2.3× 1.3k 0.7× 518 0.5× 1.9k 1.8× 258 13.0k
R.A. Erdman 4.6k 1.6× 2.2k 1.1× 633 0.3× 200 0.2× 1.3k 1.2× 105 5.9k
A.V. Capuco 2.6k 0.9× 1.7k 0.8× 771 0.4× 399 0.4× 628 0.6× 118 4.4k
J.J. Kennelly 3.5k 1.2× 1.8k 0.9× 615 0.3× 129 0.1× 1000 1.0× 148 4.9k
Zhihua Jiang 393 0.1× 1.8k 0.9× 1.9k 1.0× 795 0.7× 252 0.2× 203 4.9k

Countries citing papers authored by Massimo Bionaz

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Bionaz

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Massimo Bionaz

This figure shows the co-authorship network connecting the top 25 collaborators of Massimo Bionaz. A scholar is included among the top collaborators of Massimo Bionaz 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 Massimo Bionaz. Massimo Bionaz 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
2.
Irawan, Agung & Massimo Bionaz. (2024). Liver Transcriptomic Profiles of Ruminant Species Fed Spent Hemp Biomass Containing Cannabinoids. Genes. 15(7). 963–963.
3.
Xia, Wei, et al.. (2023). Dynamic Profile of the Yak Mammary Transcriptome during the Lactation Cycle. Animals. 13(10). 1710–1710. 3 indexed citations
4.
Busato, Sebastiano, et al.. (2022). Peroxisome Proliferator-Activated Receptor Activation in Precision-Cut Bovine Liver Slices Reveals Novel Putative PPAR Targets in Periparturient Dairy Cows. Frontiers in Veterinary Science. 9. 931264–931264. 9 indexed citations
5.
6.
Gao, Shengtao, et al.. (2020). Hepatic transcriptomic adaptation from prepartum to postpartum in dairy cows. Journal of Dairy Science. 104(1). 1053–1072. 20 indexed citations
7.
Abdelatty, Alzahraa M., Asmaa K. Al‐Mokaddem, Heba M. A. Khalil, et al.. (2020). Influence of level of inclusion of Azolla leaf meal on growth performance, meat quality and skeletal muscle p70S6 kinase α abundance in broiler chickens. animal. 14(11). 2423–2432. 26 indexed citations
8.
McLean, Derek J., et al.. (2019). A natural bioactive feed additive alters expression of genes involved in inflammation in whole blood of healthy Angus heifers. Innate Immunity. 26(4). 285–293. 3 indexed citations
9.
Kutzler, Michelle Anne, et al.. (2019). Cow milk does not affect adiposity in growing piglets as a model for children. Journal of Dairy Science. 102(6). 4798–4807. 3 indexed citations
10.
Mirhoseini, Seyed Ziaeddin, et al.. (2018). Transcriptome analysis showed differences of two purebred cattle and their crossbreds. Italian Journal of Animal Science. 18(1). 70–79. 1 indexed citations
11.
Bionaz, Massimo. (2014). Cross-talk between liver and mammary tissue after experimental Escherichia coli mastitis in Holstein dairy cows using RNAseq. 2014 ADSA-ASAS-CSAS Joint Annual Meeting. 2 indexed citations
12.
Bionaz, Massimo, Gary J. Hausman, Juan J. Loor, & Stéphane Mandard. (2013). Physiological and Nutritional Roles of PPAR across Species. PPAR Research. 2013. 1–3. 14 indexed citations
13.
Monaco, Elisa Lo, Massimo Bionaz, Sandra L. Rodriguez‐Zas, W.L. Hurley, & Matthew B. Wheeler. (2012). Transcriptomics Comparison between Porcine Adipose and Bone Marrow Mesenchymal Stem Cells during In Vitro Osteogenic and Adipogenic Differentiation. PLoS ONE. 7(3). e32481–e32481. 63 indexed citations
14.
Wheeler, Matthew B., Elisa Lo Monaco, Massimo Bionaz, & Tetsuya S. Tanaka. (2010). The Role of Existing and Emerging Biotechnologies for Livestock Production: toward holism. ACTA SCIENTIAE VETERINARIAE. 38. 9 indexed citations
15.
Mukesh, Manishi, Massimo Bionaz, D.E. Graugnard, J.K. Drackley, & Juan J. Loor. (2009). Adipose tissue depots of Holstein cows are immune responsive: Inflammatory gene expression in vitro. Domestic Animal Endocrinology. 38(3). 168–178. 55 indexed citations
16.
Piantoni, Paola, Massimo Bionaz, D.E. Graugnard, et al.. (2008). Gene Expression Ratio Stability Evaluation in Prepubertal Bovine Mammary Tissue from Calves Fed Different Milk Replacers Reveals Novel Internal Controls for Quantitative Polymerase Chain Reaction2. Journal of Nutrition. 138(6). 1158–1164. 33 indexed citations
17.
Tramontana, S, Massimo Bionaz, Ankita Sharma, et al.. (2008). Internal Controls for Quantitative Polymerase Chain Reaction of Swine Mammary Glands During Pregnancy and Lactation. Journal of Dairy Science. 91(8). 3057–3066. 38 indexed citations
18.
Bionaz, Massimo, Craig R. Baumrucker, Erin N. Shirk, et al.. (2008). Short Communication: Characterization of Madin-Darby Bovine Kidney Cell Line for Peroxisome Proliferator-Activated Receptors: Temporal Response and Sensitivity to Fatty Acids. Journal of Dairy Science. 91(7). 2808–2813. 34 indexed citations
19.
Bionaz, Massimo & Juan J. Loor. (2008). ACSL1, AGPAT6, FABP3, LPIN1, and SLC27A6 Are the Most Abundant Isoforms in Bovine Mammary Tissue and Their Expression Is Affected by Stage of Lactation3. Journal of Nutrition. 138(6). 1019–1024. 201 indexed citations
20.
Bionaz, Massimo, et al.. (2007). Plasma Paraoxonase, Inflammatory Conditions, Liver Functionality and Health Problems in Transition Dairy Cows.. The Journal of Urology. 128(4). 1740–1750. 8 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.

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