Suxing Liu

2.2k total citations · 1 hit paper
24 papers, 1.6k citations indexed

About

Suxing Liu is a scholar working on Molecular Biology, Plant Science and Oncology. According to data from OpenAlex, Suxing Liu has authored 24 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Molecular Biology, 8 papers in Plant Science and 6 papers in Oncology. Recurrent topics in Suxing Liu's work include Cancer-related Molecular Pathways (5 papers), Gene expression and cancer classification (4 papers) and Genomics and Chromatin Dynamics (4 papers). Suxing Liu is often cited by papers focused on Cancer-related Molecular Pathways (5 papers), Gene expression and cancer classification (4 papers) and Genomics and Chromatin Dynamics (4 papers). Suxing Liu collaborates with scholars based in United States, China and United Kingdom. Suxing Liu's co-authors include Luquan Wang, Jonathan Greene, Marianne Schroeder, Paula Fernández, Scott R. Frank, Bruno Amati, Andrea Cocito, Cecil B. Pickett, Asra Mirza and Qun Wu and has published in prestigious journals such as Journal of Biological Chemistry, Nature Genetics and Genes & Development.

In The Last Decade

Suxing Liu

24 papers receiving 1.5k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Genomic targets of the human c-Myc protein

2003 764 citations Paula Fernández, Scott R. Frank et al. Genes & Development profile →

Peers

Suxing Liu

MB

ONCOL

PS

CR

GENET

Chaim Linhart Israel

Ming‐Chung Li United States

Oliver Frings Sweden

Florian Battke Germany

Heikki Lehväslaiho Finland

Greg Schuler United States

Joern Toedling Germany

Matthew L. Tomlinson United Kingdom

Qian Song China

M.S. Lakshmi United Kingdom

Chaim Linhart Israel

Suxing Liu

1.1k ×1.0

MB

215 ×0.6

ONCOL

158 ×0.6

PS

252 ×1.1

CR

122 ×0.9

GENET

Citations per year, relative to Suxing Liu Suxing Liu (= 1×) peers Chaim Linhart

Countries citing papers authored by Suxing Liu

Since Specialization

Citations

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

Fields of papers citing papers by Suxing Liu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suxing Liu

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Liu, Suxing, et al.. (2023). OPEN leaf : an open‐source cloud‐based phenotyping system for tracking dynamic changes at leaf‐specific resolution in Arabidopsis. The Plant Journal. 116(6). 1600–1616. 3 indexed citations

2.

Liu, Suxing, et al.. (2023). Comparison of open‐source three‐dimensional reconstruction pipelines for maize‐root phenotyping. SHILAP Revista de lepidopterología. 6(1). 3 indexed citations

3.

Liu, Suxing, et al.. (2023). Segmentation of Arabidopsis thaliana Using Segment-Anything. 1–5. 3 indexed citations

4.

Liu, Suxing, et al.. (2021). DIRT/3D: 3D root phenotyping for field-grown maize ( Zea mays ). PLANT PHYSIOLOGY. 187(2). 739–757. 37 indexed citations

5.

Liu, Suxing, et al.. (2020). Characterization of the response to abiotic stresses of high ascorbate Arabidopsis lines using phenomic approaches. Plant Physiology and Biochemistry. 151. 500–515. 6 indexed citations

6.

Liu, Suxing, et al.. (2016). Moderate to severe water limitation differentially affects the phenome and ionome of Arabidopsis. Functional Plant Biology. 44(1). 94–106. 27 indexed citations

7.

Shen, Liquan, Zhi Liu, Suxing Liu, Zhaoyang Zhang, & Ping An. (2009). Selective Disparity Estimation and Variable Size Motion Estimation Based on Motion Homogeneity for Multi-View Coding. IEEE Transactions on Broadcasting. 55(4). 761–766. 53 indexed citations

8.

Zhang, Qian, Suxing Liu, Ping An, & Zhaoyang Zhang. (2009). Object segmentation based on disparity estimation. 1053–1056. 2 indexed citations

9.

Liu, Suxing. (2008). 3D Multi-View Stereoscopic Display and Its Key Technologies. Dianzi qijian. 2 indexed citations

10.

Liu, Suxing, Paul T. Kirschmeier, Jason S. Simon, Cynthia Seidel‐Dugan, & Markus Puhlmann. (2008). Prognostic and Predictive Molecular Markers in Cutaneous Malignant Melanoma: The First Step Toward Personalized Medicine. Current pharmacogenomics and personalized medicine (Online). 6(4). 272–294. 3 indexed citations

11.

Liu, Suxing & Cynthia Seidel‐Dugan. (2006). In search of p53 target genes for the therapeutic manipulation of cancer.. PubMed. 9(2). 176–83. 6 indexed citations

12.

Wu, Qun, Wei Ding, Asra Mirza, et al.. (2005). Integrative Genomics Revealed RAI3 Is a Cell Growth-promoting Gene and a Novel P53 Transcriptional Target. Journal of Biological Chemistry. 280(13). 12935–12943. 36 indexed citations

13.

Liu, Suxing, Asra Mirza, & Luquan Wang. (2004). Generation of p53 Target Database Via Integration of Microarray and Global p53 DNA-Binding Site Analysis. Humana Press eBooks. 281. 33–54. 10 indexed citations

14.

Fernández, Paula, Scott R. Frank, Luquan Wang, et al.. (2003). Genomic targets of the human c-Myc protein. Genes & Development. 17(9). 1115–1129. 764 indexed citations breakdown →

15.

Mirza, Asra, Qun Wu, Luquan Wang, et al.. (2003). Global transcriptional program of p53 target genes during the process of apoptosis and cell cycle progression. Oncogene. 22(23). 3645–3654. 143 indexed citations

16.

Qiu, Ping, et al.. (2002). Analysis of a human brain transcriptome map. BMC Genomics. 3(1). 10–10. 17 indexed citations

17.

Wang, Y. Lynn, Maureen Laverty, Suxing Liu, et al.. (2002). A reference database for tumor-related genes co-expressed with interleukin-8 using genome-scale in silico analysis. BMC Genomics. 3(1). 29–29. 5 indexed citations

18.

Wang, Luquan, Qun Wu, Ping Qiu, et al.. (2001). Analyses of p53 Target Genes in the Human Genome by Bioinformatic and Microarray Approaches. Journal of Biological Chemistry. 276(47). 43604–43610. 131 indexed citations

19.

Liu, Suxing, Qun Wu, Paul T. Kirschmeier, et al.. (2001). Genome-wide gene expression analysis of human breast cancer cells. Nature Genetics. 27(S4). 90–90. 1 indexed citations

20.

Liu, Suxing, S.P. Stoesz, & Cecil B. Pickett. (1998). Identification of a Novel Human GlutathioneS-Transferase Using Bioinformatics. Archives of Biochemistry and Biophysics. 352(2). 306–313. 30 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.

Explore authors with similar magnitude of impact