Siheng Xiang

2.4k total citations · 1 hit paper
9 papers, 1.7k citations indexed

About

Siheng Xiang is a scholar working on Molecular Biology, Genetics and Neurology. According to data from OpenAlex, Siheng Xiang has authored 9 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 2 papers in Genetics and 2 papers in Neurology. Recurrent topics in Siheng Xiang's work include RNA Research and Splicing (7 papers), RNA modifications and cancer (2 papers) and Genomics and Chromatin Dynamics (2 papers). Siheng Xiang is often cited by papers focused on RNA Research and Splicing (7 papers), RNA modifications and cancer (2 papers) and Genomics and Chromatin Dynamics (2 papers). Siheng Xiang collaborates with scholars based in United States, South Korea and China. Siheng Xiang's co-authors include Masato Kato, Steven L. McKnight, Leeju C. Wu, Ilmin Kwon, Yi Lin, Eiichiro Mori, Tao Wang, Yang Xie, Jiwoong Kim and Jonghyun Yun and has published in prestigious journals such as Science, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Siheng Xiang

9 papers receiving 1.7k citations

Hit Papers

Poly-dipeptides encoded by the C9orf72 repeats bind nucle... 2014 2026 2018 2022 2014 100 200 300 400
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.

  1. Poly-dipeptides encoded by the C9orf72 repeats bind nucleoli, impede RNA biogenesis, and kill cells
    2014 465 citations Ilmin Kwon, Siheng Xiang et al. Science profile →

Peers

Siheng Xiang
Edward Gomes United States
Anaïs Aulas France
Marc‐David Ruepp Switzerland
Alexander E. Conicella United States
Brian A. Maxwell United States
Andrea D’Ambrogio Italy
Sebastian Markmiller United States
Alberto T. Gatta United Kingdom
Lara Marrone Germany
Edward Gomes United States
Siheng Xiang
Citations per year, relative to Siheng Xiang Siheng Xiang (= 1×) peers Edward Gomes

Countries citing papers authored by Siheng Xiang

Since Specialization
Citations

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

Fields of papers citing papers by Siheng Xiang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Siheng Xiang

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

All Works

9 of 9 papers shown
1.
Xiang, Siheng, et al.. (2023). A model for Scc2p stimulation of cohesin's ATPase and its inhibition by acetylation of Smc3p. Genes & Development. 37(7-8). 277–290. 3 indexed citations
2.
Murray, Dylan T., Xiaoming Zhou, Masato Kato, et al.. (2018). Structural characterization of the D290V mutation site in hnRNPA2 low-complexity–domain polymers. Proceedings of the National Academy of Sciences. 115(42). E9782–E9791. 38 indexed citations
3.
Shi, Kevin, Eiichiro Mori, Zehra F. Nizami, et al.. (2017). Toxic PR n poly-dipeptides encoded by the C9orf72 repeat expansion block nuclear import and export. Proceedings of the National Academy of Sciences. 114(7). E1111–E1117. 176 indexed citations
4.
Lin, Yi, Eiichiro Mori, Masato Kato, et al.. (2016). Toxic PR Poly-Dipeptides Encoded by the C9orf72 Repeat Expansion Target LC Domain Polymers. Cell. 167(3). 789–802.e12. 312 indexed citations
5.
Xiang, Siheng, Masato Kato, Leeju C. Wu, et al.. (2015). The LC Domain of hnRNPA2 Adopts Similar Conformations in Hydrogel Polymers, Liquid-like Droplets, and Nuclei. Cell. 163(4). 829–839. 226 indexed citations
6.
Kwon, Ilmin, Siheng Xiang, Masato Kato, et al.. (2014). Poly-dipeptides encoded by the C9orf72 repeats bind nucleoli, impede RNA biogenesis, and kill cells. Science. 345(6201). 1139–1145. 465 indexed citations breakdown →
7.
Kwon, Ilmin, Masato Kato, Siheng Xiang, et al.. (2014). Phosphorylation-Regulated Binding of RNA Polymerase II to Fibrous Polymers of Low-Complexity Domains. Cell. 156(1-2). 374–374. 7 indexed citations
8.
Kwon, Ilmin, Masato Kato, Siheng Xiang, et al.. (2013). Phosphorylation-Regulated Binding of RNA Polymerase II to Fibrous Polymers of Low-Complexity Domains. Cell. 155(5). 1049–1060. 428 indexed citations
9.
Wang, Feng, Ziqing Mei, Chuangye Yan, et al.. (2009). Crystal Structure of the MecA Degradation Tag. Journal of Biological Chemistry. 284(49). 34376–34381. 12 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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