Songrong Ren

3.2k citations
47 papers · 2.5k indexed · 1 hit paper · h-index 25

Songrong Ren

46 papers receiving 2.5k citations

Hit Papers

Hepatic Fatty Acid Transporter Cd36 Is a Common Target of...5052007202620132019100200300400500

Peers

Songrong Ren
Comparison fields: 5 of 96
  • Pharmacology 740
  • Endocrinology, Diabetes and Metabolism 599
  • Biochemistry 210
  • Oncology 666
  • Hepatology 174
Replace Taro E. Akiyama with:
Taro E. Akiyama United States
Kathleen K. Brown United States
Heidi R. Kast-Woelbern United States
Marie‐José Vilarem France
Julie Massart Sweden
Shogo Takahashi United States
Miki Shimada Japan
Marcelo G. Roma Argentina
Meishu Xu United States
Promsuk Jutabha Japan
Songrong Ren relative to Taro E. Akiyama United States Taro E. Akiyama's profile →
Citations per field
00.5×1.5×
Taro E. Akiyama · 1×
Citations per year

Countries citing papers authored by Songrong Ren

Since Specialization
Citations

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

Fields of papers citing papers by Songrong Ren

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Songrong Ren, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Songrong Ren Line = papers co-authored together Songrong Ren links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20260
2 20242
3 20232
4 20223
5 202125
6 202142
7 202150
8 202038
9 201987
10 20195
11 20176
12 201614
13 201324
14 201043
15 200859
16
Hepatic Fatty Acid Transporter Cd36 Is a Common Target of LXR, PXR, and PPARγ in Promoting Steatosisbreakdown →
2007505
17 2006301
18 200570
19 200588
20 2004200

About Songrong Ren

Songrong Ren is a scholar working on Pharmacology, Biochemistry and Endocrinology, Diabetes and Metabolism, having authored 47 papers that have together received 2.5k indexed citations. Recurring topics across this work include Drug Transport and Resistance Mechanisms (15 papers), Cholesterol and Lipid Metabolism (13 papers), Pharmacogenetics and Drug Metabolism (12 papers), Liver Disease Diagnosis and Treatment (9 papers), Hormonal Regulation and Hypertension (8 papers), Peroxisome Proliferator-Activated Receptors (5 papers), Genomics, phytochemicals, and oxidative stress (4 papers) and Eicosanoids and Hypertension Pharmacology (3 papers). The work is most often cited by research in Pharmacology (740 citations), Endocrinology, Diabetes and Metabolism (599 citations) and Biochemistry (210 citations). Songrong Ren has collaborated with scholars based in United States, China and Germany. Frequent co-authors include Wen Xie, David Toma, Hirdesh Uppal, Jie Zhou, Ying Mu, Meishu Xu, Jinhan He, Haibiao Gong, Shaheen Khadem and S. P. S. Saini. Their work appears in journals such as Molecular Pharmacology, Hepatology, Endocrinology, Gastroenterology and Molecular Endocrinology.

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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