Peggy I. Wang

2.9k total citations · 2 hit papers
10 papers, 1.4k citations indexed

About

Peggy I. Wang is a scholar working on Molecular Biology, Genetics and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Peggy I. Wang has authored 10 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 3 papers in Genetics and 1 paper in Pulmonary and Respiratory Medicine. Recurrent topics in Peggy I. Wang's work include Genomics and Chromatin Dynamics (5 papers), Epigenetics and DNA Methylation (3 papers) and Bioinformatics and Genomic Networks (3 papers). Peggy I. Wang is often cited by papers focused on Genomics and Chromatin Dynamics (5 papers), Epigenetics and DNA Methylation (3 papers) and Bioinformatics and Genomic Networks (3 papers). Peggy I. Wang collaborates with scholars based in United States, South Korea and Netherlands. Peggy I. Wang's co-authors include Edward M. Marcotte, Insuk Lee, Jung Eun Shim, Ruslan I. Sadreyev, Robert E. Kingston, Jason A. West, Christopher P. Davis, Hongjae Sunwoo, Matthew D. Simon and Michael Tolstorukov and has published in prestigious journals such as Science, Molecular Cell and PLoS ONE.

In The Last Decade

Peggy I. Wang

10 papers receiving 1.4k citations

Hit Papers

The Long Noncoding RNAs NEAT1 and MALAT1 Bind Active Chro... 2011 2026 2016 2021 2014 2011 100 200 300 400 500
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. The Long Noncoding RNAs NEAT1 and MALAT1 Bind Active Chromatin Sites
    2014 524 citations Jason A. West, Christopher P. Davis et al. Molecular Cell profile →
  2. Prioritizing candidate disease genes by network-based boosting of genome-wide association data
    2011 498 citations Insuk Lee, Peggy I. Wang et al. Genome Research profile →

Peers

Peggy I. Wang
Eiru Kim South Korea
Lee Sam United States
Jung Eun Shim South Korea
Fuxiao Xin United States
Kane Tse Canada
Yedael Y. Waldman Israel
Emanuel Gonçalves United Kingdom
Julien Lagarde Spain
Stan Letovsky United States
Liran Juan China
Eiru Kim South Korea
Peggy I. Wang
Citations per year, relative to Peggy I. Wang Peggy I. Wang (= 1×) peers Eiru Kim

Countries citing papers authored by Peggy I. Wang

Since Specialization
Citations

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

Fields of papers citing papers by Peggy I. Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peggy I. Wang. 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 Peggy I. Wang. The network helps show where Peggy I. Wang may publish in the future.

Co-authorship network of co-authors of Peggy I. Wang

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

All Works

10 of 10 papers shown
1.
2.
Rosario, Brian C. Del, Amanda Del Rosario, Anthony Anselmo, et al.. (2017). Genetic Intersection of Tsix and Hedgehog Signaling during the Initiation of X-Chromosome Inactivation. Developmental Cell. 43(3). 359–371.e6. 13 indexed citations
3.
Savol, Andrej, Peggy I. Wang, Yesu Jeon, et al.. (2017). Genome-wide identification of autosomal genes with allelic imbalance of chromatin state. PLoS ONE. 12(8). e0182568–e0182568. 6 indexed citations
4.
Schwartz, Matthew G., Sharmistha Kundu, Andrej Savol, et al.. (2017). Mutation of a nucleosome compaction region disrupts Polycomb-mediated axial patterning. Science. 355(6329). 1081–1084. 108 indexed citations
5.
West, Jason A., Christopher P. Davis, Hongjae Sunwoo, et al.. (2014). The Long Noncoding RNAs NEAT1 and MALAT1 Bind Active Chromatin Sites. Molecular Cell. 55(5). 791–802. 524 indexed citations breakdown →
6.
Bowman, Sarah, Aimée M. Deaton, Peggy I. Wang, et al.. (2014). H3K27 modifications define segmental regulatory domains in the Drosophila bithorax complex. eLife. 3. e02833–e02833. 95 indexed citations
7.
Wang, Peggy I., Sohyun Hwang, Rodney P. Kincaid, et al.. (2012). RIDDLE: reflective diffusion and local extension reveal functional associations for unannotated gene sets via proximity in a gene network. Genome biology. 13(12). R125–R125. 15 indexed citations
8.
Lee, Insuk, et al.. (2011). Prioritizing candidate disease genes by network-based boosting of genome-wide association data. Genome Research. 21(7). 1109–1121. 498 indexed citations breakdown →
9.
Smith, Katherine R., Peggy I. Wang, Sander Basten, et al.. (2010). A role for central spindle proteins in cilia structure and function. Cytoskeleton. 68(2). 112–124. 31 indexed citations
10.
Wang, Peggy I. & Edward M. Marcotte. (2010). It's the machine that matters: Predicting gene function and phenotype from protein networks. Journal of Proteomics. 73(11). 2277–2289. 87 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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