Hattie Chung

2.6k total citations · 1 hit paper
7 papers, 867 citations indexed

About

Hattie Chung is a scholar working on Molecular Biology, Genetics and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Hattie Chung has authored 7 papers receiving a total of 867 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 2 papers in Genetics and 1 paper in Pulmonary and Respiratory Medicine. Recurrent topics in Hattie Chung's work include CRISPR and Genetic Engineering (2 papers), Evolution and Genetic Dynamics (2 papers) and Gene Regulatory Network Analysis (2 papers). Hattie Chung is often cited by papers focused on CRISPR and Genetic Engineering (2 papers), Evolution and Genetic Dynamics (2 papers) and Gene Regulatory Network Analysis (2 papers). Hattie Chung collaborates with scholars based in United States, Israel and Canada. Hattie Chung's co-authors include Roy Kishony, Tami D. Lieberman, Michael Baym, Sergey Kryazhimskiy, Michael M. Desai, José I. Jiménez, Domitilla Del Vecchio, András György, Ron Weiss and Christopher N. Parkhurst and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and PLoS ONE.

In The Last Decade

Hattie Chung

6 papers receiving 858 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.

Inexpensive Multiplexed Library Preparation for Megabase-Sized Genomes

2015 457 citations Michael Baym, Sergey Kryazhimskiy et al. PLoS ONE profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Hattie Chung United States	6	624	224	123	85	76	7	867
Khai Luong United States	16	694 1.1×	136 0.6×	257 2.1×	78 0.9×	76 1.0×	19	993
Martin Madera United Kingdom	11	968 1.6×	173 0.8×	93 0.8×	56 0.7×	78 1.0×	12	1.3k
Grégory Boël France	17	823 1.3×	383 1.7×	170 1.4×	169 2.0×	106 1.4×	24	1.2k
Donna M. Muzny United States	7	580 0.9×	328 1.5×	140 1.1×	51 0.6×	119 1.6×	8	1.1k
Agnieszka Sierakowska Juncker Denmark	12	951 1.5×	238 1.1×	258 2.1×	135 1.6×	101 1.3×	15	1.5k
O. Barábas Germany	21	882 1.4×	248 1.1×	181 1.5×	107 1.3×	51 0.7×	42	1.2k
Rute G. Matos Portugal	17	663 1.1×	292 1.3×	226 1.8×	125 1.5×	32 0.4×	41	905
Daniel Dar Israel	15	797 1.3×	353 1.6×	264 2.1×	63 0.7×	55 0.7×	19	1.0k
Fabian Amman Austria	20	1.1k 1.7×	291 1.3×	187 1.5×	108 1.3×	140 1.8×	47	1.4k
Mihail Halachev United Kingdom	9	386 0.6×	109 0.5×	137 1.1×	65 0.8×	84 1.1×	15	638

Countries citing papers authored by Hattie Chung

Since Specialization

Citations

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

Fields of papers citing papers by Hattie Chung

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Hattie Chung

This figure shows the co-authorship network connecting the top 25 collaborators of Hattie Chung. A scholar is included among the top collaborators of Hattie Chung 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 Hattie Chung. Hattie Chung 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:

7 of 7 papers shown

1.

Chung, Hattie, Christopher N. Parkhurst, Devan Phillips, et al.. (2021). Joint single-cell measurements of nuclear proteins and RNA in vivo. Nature Methods. 18(10). 1204–1212. 84 indexed citations

2.

Chung, Hattie, Tami D. Lieberman, Sara O. Vargas, et al.. (2017). Global and local selection acting on the pathogen Stenotrophomonas maltophilia in the human lung. Nature Communications. 8(1). 14078–14078. 38 indexed citations

3.

Kelsic, Eric D., et al.. (2016). RNA Structural Determinants of Optimal Codons Revealed by MAGE-Seq. Cell Systems. 3(6). 563–571.e6. 41 indexed citations

4.

György, András, et al.. (2015). Isocost Lines Describe the Cellular Economy of Genetic Circuits. Biophysical Journal. 109(3). 639–646. 164 indexed citations

5.

Baym, Michael, Sergey Kryazhimskiy, Tami D. Lieberman, et al.. (2015). Inexpensive Multiplexed Library Preparation for Megabase-Sized Genomes. PLoS ONE. 10(5). e0128036–e0128036. 457 indexed citations breakdown →

6.

Huang, Hsin-Ho, et al.. (2015). Isocost Lines Describe the Cellular Economy of Genetic Circuits. DSpace@MIT (Massachusetts Institute of Technology).

7.

Nguyen, David N., Kerry P. Mahon, Ghania Chikh, et al.. (2012). Lipid-derived nanoparticles for immunostimulatory RNA adjuvant delivery. Proceedings of the National Academy of Sciences. 109(14). 83 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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