Matthew T. Flowers

2.8k citations
32 papers · 2.2k indexed · h-index 21
Topics
Lipid metabolism and biosynthesis (13 papers)Peroxisome Proliferator-Activated Receptors (11 papers)Fatty Acid Research and Health (7 papers)

In The Last Decade

Matthew T. Flowers

32 papers receiving 2.1k citations

Peers

Matthew T. Flowers
Comparison fields: 5 of 103
  • Molecular Biology 966
  • Physiology 576
  • Surgery 540
  • Biochemistry 503
  • Epidemiology 501
Replace Cathérine Mounier with:
Cathérine Mounier Canada
Gen‐ichi Atsumi Japan
Lei O. Li United States
M. Mahmood Hussain United States
Holger Doege United States
Chi–Liang Eric Yen United States
Yingjiang Zhou United States
Sandra Guilmeau France
Tal M. Lewin United States
Kathy Jaworski United States
Matthew T. Flowers relative to Cathérine Mounier Canada Cathérine Mounier's profile →
Citations per field
00.5×1.5×2.1×
Cathérine Mounier · 1×
Citations per year

Countries citing papers authored by Matthew T. Flowers

Since Specialization
Citations

This map shows the geographic impact of Matthew T. Flowers'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 T. Flowers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew T. Flowers more than expected).

Fields of papers citing papers by Matthew T. Flowers

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Matthew T. Flowers

This figure shows the co-authorship network connecting the top 25 collaborators of Matthew T. Flowers. A scholar is included among the top collaborators of Matthew T. Flowers 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 Matthew T. Flowers. Matthew T. Flowers 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
#WorkIndexed citations
1 2
2 19
3 2
4 9
5 38
6 48
7 9
8 48
9 47
10 41
11 65
12 139
13 133
14 92
15 342
16 341
17 133
18 58
19 6
20 92

About Matthew T. Flowers

Matthew T. Flowers is a scholar working on Biochemistry, Behavioral Neuroscience and Reproductive Medicine, having authored 32 papers that have together received 2.2k indexed citations. Recurring topics across this work include Lipid metabolism and biosynthesis (13 papers), Peroxisome Proliferator-Activated Receptors (11 papers) and Fatty Acid Research and Health (7 papers). The work is most often cited by research in Biochemistry (503 citations), Nutrition and Dietetics (432 citations) and Physiology (576 citations). Matthew T. Flowers has collaborated with scholars based in United States, Netherlands and South Korea. Frequent co-authors include James M. Ntambi, Xueqing Liu, Kiki Chu, Harini Sampath, Makoto Miyazaki, Alan Attie, Lan Hong, Chad M. Paton, Michael A. Wells and Mark P. Keller. Their work appears in journals such as Journal of Biological Chemistry, Nature Genetics and PLoS ONE.

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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