Michelle Arlotto

4.1k citations
11 papers · 2.9k indexed · 1 hit paper · h-index 11
Topics
Pancreatic function and diabetes (5 papers)Diet and metabolism studies (4 papers)Genetics and Neurodevelopmental Disorders (3 papers)
Partner nations
United StatesCanada

In The Last Decade

Michelle Arlotto

11 papers receiving 2.9k citations

Hit Papers

A Branched-Chain Amino Acid-Related Metabolic Signature t...2009202620142020200950010001.5k2.0k

Peers

Michelle Arlotto
Comparison fields: 5 of 112
  • Molecular Biology 1.9k
  • Physiology 1.6k
  • Epidemiology 524
  • Cell Biology 330
  • Surgery 319
Replace Mark D. Butler with:
Mark D. Butler Ireland
Pengxiang She United States
Michael D. Neinast United States
Debby P.Y. Koonen Netherlands
Brian T. O’Neill United States
Ryan P. McMillan United States
Miriam Hoene Germany
Richard G. Kibbey United States
Ruth C. R. Meex Netherlands
Lee D. Roberts United Kingdom
Michelle Arlotto relative to Mark D. Butler Ireland Mark D. Butler's profile →
Citations per field
00.5×1.5×
Mark D. Butler · 1×
Citations per year

Countries citing papers authored by Michelle Arlotto

Since Specialization
Citations

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

Fields of papers citing papers by Michelle Arlotto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michelle Arlotto

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

All Works

11 of 11 papers shown
#WorkIndexed citations
1 16
2 23
3 20
4 18
5 74
6 22
7 76
8 87
9
A Branched-Chain Amino Acid-Related Metabolic Signature that Differentiates Obese and Lean Humans and Contributes to Insulin Resistancebreakdown →
2442
10 77
11 33

About Michelle Arlotto

Michelle Arlotto is a scholar working on Genetics, Physiology and Endocrine and Autonomic Systems, having authored 11 papers that have together received 2.9k indexed citations. Recurring topics across this work include Pancreatic function and diabetes (5 papers), Diet and metabolism studies (4 papers) and Genetics and Neurodevelopmental Disorders (3 papers). The work is most often cited by research in Physiology (1.6k citations), Molecular Biology (1.9k citations) and Clinical Biochemistry (180 citations). Michelle Arlotto has collaborated with scholars based in United States and Canada. Frequent co-authors include Christopher B. Newgard, James R. Bain, David S. Millington, Cris A. Slentz, Dianne Gallup, James Rochon, Michael J. Muehlbauer, Andrea M. Haqq, Laura P. Svetkey and Lillian F. Lien. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research 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.

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