Faquan Liang

1.5k total citations
18 papers, 1.2k citations indexed

About

Faquan Liang is a scholar working on Cardiology and Cardiovascular Medicine, Molecular Biology and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Faquan Liang has authored 18 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Cardiology and Cardiovascular Medicine, 11 papers in Molecular Biology and 3 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Faquan Liang's work include Cardiac Fibrosis and Remodeling (8 papers), Signaling Pathways in Disease (5 papers) and Heart Failure Treatment and Management (4 papers). Faquan Liang is often cited by papers focused on Cardiac Fibrosis and Remodeling (8 papers), Signaling Pathways in Disease (5 papers) and Heart Failure Treatment and Management (4 papers). Faquan Liang collaborates with scholars based in United States and United Kingdom. Faquan Liang's co-authors include David G. Gardner, Andrew A. Protter, George F. Schreiner, Sumei Zhang, Ann M. Kapoun, Andrew Lam, Shan Lu, Gilbert O’Young, Deborah Damm and Roger White and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Investigation and Journal of the American College of Cardiology.

In The Last Decade

Faquan Liang

18 papers receiving 1.1k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Faquan Liang United States 14 798 494 153 134 109 18 1.2k
G. Takemura Japan 16 710 0.9× 317 0.6× 182 1.2× 91 0.7× 113 1.0× 36 1.2k
Daiji Miura Japan 21 838 1.1× 547 1.1× 131 0.9× 246 1.8× 68 0.6× 46 1.3k
Akihiko Karibe Japan 16 896 1.1× 658 1.3× 155 1.0× 132 1.0× 60 0.6× 23 1.5k
Brenda K. Huntley United States 22 1.1k 1.4× 426 0.9× 168 1.1× 227 1.7× 204 1.9× 48 1.6k
Keisuke Tokuda Japan 11 933 1.2× 468 0.9× 237 1.5× 167 1.2× 158 1.4× 16 1.4k
Takashi Minase Japan 15 790 1.0× 389 0.8× 184 1.2× 104 0.8× 135 1.2× 44 1.6k
Daniel P. Griese Germany 18 569 0.7× 699 1.4× 330 2.2× 231 1.7× 93 0.9× 32 1.5k
Hugues Gosselin Canada 19 582 0.7× 409 0.8× 178 1.2× 68 0.5× 91 0.8× 33 983
Toshio Igaki Japan 14 504 0.6× 556 1.1× 209 1.4× 194 1.4× 72 0.7× 18 1.2k
Yuanjian Chen United States 17 403 0.5× 401 0.8× 166 1.1× 74 0.6× 109 1.0× 24 914

Countries citing papers authored by Faquan Liang

Since Specialization
Citations

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

Fields of papers citing papers by Faquan Liang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Faquan Liang

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

All Works

18 of 18 papers shown
1.
Liang, Faquan, Peidong Fan, Suya Yang, et al.. (2016). Inhibitions of late I Na and CaMKII act synergistically to prevent ATX-II-induced atrial fibrillation in isolated rat right atria. Journal of Molecular and Cellular Cardiology. 94. 122–130. 16 indexed citations
2.
Budas, Grant R., Faquan Liang, Dillon Phan, et al.. (2014). ASK1 promotes maladaptive remodeling in a rodent model of pulmonary hypertension. European Respiratory Journal. 44(Suppl 58). P2298–P2298. 3 indexed citations
3.
Liang, Faquan, Suya Yang, Lina Yao, Luiz Belardinelli, & John C. Shryock. (2012). Ambrisentan and Tadalafil Synergistically Relax Endothelin-Induced Contraction of Rat Pulmonary Arteries. Hypertension. 59(3). 705–711. 22 indexed citations
5.
Liang, Faquan, Jessica O’Rear, Ute Schellenberger, et al.. (2007). Evidence for Functional Heterogeneity of Circulating B-Type Natriuretic Peptide. Journal of the American College of Cardiology. 49(10). 1071–1078. 200 indexed citations
6.
Liang, Faquan, Ann M. Kapoun, Andrew Lam, et al.. (2007). B-Type Natriuretic Peptide Inhibited Angiotensin II-Stimulated Cholesterol Biosynthesis, Cholesterol Transfer, and Steroidogenesis in Primary Human Adrenocortical Cells. Endocrinology. 148(8). 3722–3729. 29 indexed citations
7.
Kapoun, Ann M., Faquan Liang, Gilbert O’Young, et al.. (2004). B-Type Natriuretic Peptide Exerts Broad Functional Opposition to Transforming Growth Factor-β in Primary Human Cardiac Fibroblasts. Circulation Research. 94(4). 453–461. 239 indexed citations
8.
Liang, Faquan, Paul Webb, Adhirai Marimuthu, Sumei Zhang, & David G. Gardner. (2003). Triiodothyronine Increases Brain Natriuretic Peptide (BNP) Gene Transcription and Amplifies Endothelin-dependent BNP Gene Transcription and Hypertrophy in Neonatal Rat Ventricular Myocytes. Journal of Biological Chemistry. 278(17). 15073–15083. 69 indexed citations
9.
Liang, Faquan, et al.. (2003). Peroxisome Proliferator Activated Receptor (PPAR)α Agonists Inhibit Hypertrophy of Neonatal Rat Cardiac Myocytes. Endocrinology. 144(9). 4187–4194. 69 indexed citations
10.
Liang, Faquan, Fred Schaufele, & David G. Gardner. (2001). Functional Interaction of NF-Y and Sp1 Is Required for Type A Natriuretic Peptide Receptor Gene Transcription. Journal of Biological Chemistry. 276(2). 1516–1522. 53 indexed citations
11.
Liang, Faquan, et al.. (2001). Signaling mechanisms underlying strain-dependent brain natriuretic peptide gene transcription. Canadian Journal of Physiology and Pharmacology. 79(8). 640–645. 7 indexed citations
12.
Liang, Faquan, et al.. (2001). Signaling mechanisms underlying strain-dependent brain natriuretic peptide gene transcription. Canadian Journal of Physiology and Pharmacology. 79(8). 640–645. 8 indexed citations
13.
Liang, Faquan, Amha Atakilit, & David G. Gardner. (2000). Integrin Dependence of Brain Natriuretic Peptide Gene Promoter Activation by Mechanical Strain. Journal of Biological Chemistry. 275(27). 20355–20360. 32 indexed citations
15.
Liang, Faquan, Fred Schaufele, & David G. Gardner. (1999). Sp1 Dependence of Natriuretic Peptide Receptor A Gene Transcription in Rat Aortic Smooth Muscle Cells1. Endocrinology. 140(4). 1695–1701. 18 indexed citations
16.
Liang, Faquan & David G. Gardner. (1999). Mechanical strain activates BNP gene transcription through a p38/NF-κB–dependent mechanism. Journal of Clinical Investigation. 104(11). 1603–1612. 181 indexed citations
17.
Liang, Faquan & David G. Gardner. (1998). Autocrine/Paracrine Determinants of Strain-activated Brain Natriuretic Peptide Gene Expression in Cultured Cardiac Myocytes. Journal of Biological Chemistry. 273(23). 14612–14619. 76 indexed citations
18.
Liang, Faquan, Jianming Wu, Miklós Garami, & David G. Gardner. (1997). Mechanical Strain Increases Expression of the Brain Natriuretic Peptide Gene in Rat Cardiac Myocytes. Journal of Biological Chemistry. 272(44). 28050–28056. 74 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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