Michelle M. Chan

3.6k total citations · 3 hit papers
18 papers, 2.1k citations indexed

About

Michelle M. Chan is a scholar working on Molecular Biology, Genetics and Biophysics. According to data from OpenAlex, Michelle M. Chan has authored 18 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Molecular Biology, 3 papers in Genetics and 3 papers in Biophysics. Recurrent topics in Michelle M. Chan's work include Single-cell and spatial transcriptomics (4 papers), CRISPR and Genetic Engineering (4 papers) and Epigenetics and DNA Methylation (3 papers). Michelle M. Chan is often cited by papers focused on Single-cell and spatial transcriptomics (4 papers), CRISPR and Genetic Engineering (4 papers) and Epigenetics and DNA Methylation (3 papers). Michelle M. Chan collaborates with scholars based in United States, Germany and Austria. Michelle M. Chan's co-authors include Zachary D. Smith, Alexander Meissner, Aviv Regev, Tarjei S. Mikkelsen, Andreas Gnirke, Hongcang Gu, Kevin Eggan, Shila Mekhoubad, K.C. Humm and Rahul Karnik and has published in prestigious journals such as Nature, Science and Nature Genetics.

In The Last Decade

Michelle M. Chan

17 papers receiving 2.1k 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.

A unique regulatory phase of DNA methylation in the early mammalian embryo

2012 754 citations Zachary D. Smith, Michelle M. Chan et al. Nature profile →
DNA methylation dynamics of the human preimplantation embryo

2014 422 citations Zachary D. Smith, Michelle M. Chan et al. Nature profile →
Improving prime editing with an endogenous small RNA-binding protein

2024 107 citations Jun Yan, Paul Oyler et al. Nature profile →

Peers

Michelle M. Chan

MB

GENET

PPCH

CR

PS

Guoqiang Li China

Michael C. Golding United States

Tomasz P. Jurkowski Germany

Heather E. Peckham United States

Mark Wossidlo United States

Yuefen Du United States

Fátima Smagulova France

Max Greenberg France

Arie B. Brinkman Netherlands

Jialei Duan United States

Guoqiang Li China

Michelle M. Chan

1.5k ×0.8

MB

397 ×0.9

GENET

254 ×0.8

PPCH

185 ×0.8

CR

137 ×0.8

PS

Citations per year, relative to Michelle M. Chan Michelle M. Chan (= 1×) peers Guoqiang Li

Countries citing papers authored by Michelle M. Chan

Since Specialization

Citations

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

Fields of papers citing papers by Michelle M. Chan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michelle M. Chan. 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 Michelle M. Chan. The network helps show where Michelle M. Chan may publish in the future.

Co-authorship network of co-authors of Michelle M. Chan

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

All Works

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18 of 18 papers shown

1.

Yan, Jun, Paul Oyler, Purnima Ravisankar, et al.. (2024). Improving prime editing with an endogenous small RNA-binding protein. Nature. 628(8008). 639–647. 107 indexed citations breakdown →

2.

McNamara, Harold M., Sabrina C. Solley, Britt Adamson, Michelle M. Chan, & Jared E. Toettcher. (2024). Recording morphogen signals reveals mechanisms underlying gastruloid symmetry breaking. Nature Cell Biology. 26(11). 1832–1844. 23 indexed citations

3.

Bolondi, Adriano, Helene Kretzmer, René Buschow, et al.. (2024). Reconstructing axial progenitor field dynamics in mouse stem cell-derived embryoids. Developmental Cell. 59(12). 1489–1505.e14. 12 indexed citations

4.

Schmidt, Henri, et al.. (2023). Startle: A star homoplasy approach for CRISPR-Cas9 lineage tracing. Cell Systems. 14(12). 1113–1121.e9. 14 indexed citations

5.

Chan, Michelle M., et al.. (2023). Pharmacy Deserts and Pharmacies’ Roles Post-Extreme Weather and Climate Events in the United States: A Scoping Review. Journal of Primary Care & Community Health. 14. 4277806657–4277806657. 4 indexed citations

6.

Zhang, Pengfei & Michelle M. Chan. (2022). A multifaceted signal recorder of cellular experiences using Cas12a base-editing. Trends in biotechnology. 40(11). 1279–1281. 1 indexed citations

7.

Quinn, Jeffrey J., Matthew G. Jones, Ross A. Okimoto, et al.. (2021). Single-cell lineages reveal the rates, routes, and drivers of metastasis in cancer xenografts. Science. 371(6532). 183 indexed citations

8.

Jones, Matthew G., Alex Khodaverdian, Jeffrey J. Quinn, et al.. (2020). Inference of single-cell phylogenies from lineage tracing data using Cassiopeia. Genome biology. 21(1). 92–92. 69 indexed citations

9.

Quinn, Jeffrey J., Matthew G. Jones, Ross A. Okimoto, et al.. (2020). Single-cell lineages reveal the rates, routes, and drivers of metastasis in cancer xenografts. Zenodo (CERN European Organization for Nuclear Research).

10.

Chan, Michelle M., Zachary D. Smith, Stefanie Grosswendt, et al.. (2019). Molecular recording of mammalian embryogenesis. Nature. 570(7759). 77–82. 225 indexed citations

11.

Smith, Zachary D., Michelle M. Chan, K.C. Humm, et al.. (2014). DNA methylation dynamics of the human preimplantation embryo. Nature. 511(7511). 611–615. 422 indexed citations breakdown →

12.

Chan, Michelle M., Vincent Fazio, & Janet Newman. (2013). Using Graphs to Represent Crystallization Conditions. Crystal Growth & Design. 13(3). 1290–1294. 1 indexed citations

13.

Thompson, Dawn, Sushmita Roy, Michelle M. Chan, et al.. (2013). Evolutionary principles of modular gene regulation in yeasts. eLife. 2. e00603–e00603. 65 indexed citations

14.

Chan, Michelle M., Zachary D. Smith, Dieter Egli, Aviv Regev, & Alexander Meissner. (2012). Mouse ooplasm confers context-specific reprogramming capacity. Nature Genetics. 44(9). 978–980. 53 indexed citations

15.

Akopian, Veronika, Michelle M. Chan, Kendell Clement, et al.. (2012). Epigenomics and chromatin dynamics. Genome biology. 13(2). 313–313. 2 indexed citations

16.

Mende, Daniel R., Alison S. Waller, Shinichi Sunagawa, et al.. (2012). Assessment of Metagenomic Assembly Using Simulated Next Generation Sequencing Data. PLoS ONE. 7(2). e31386–e31386. 194 indexed citations

17.

Smith, Zachary D., Michelle M. Chan, Tarjei S. Mikkelsen, et al.. (2012). A unique regulatory phase of DNA methylation in the early mammalian embryo. Nature. 484(7394). 339–344. 754 indexed citations breakdown →

18.

Akopian, Veronika, Michelle M. Chan, Kendell Clement, et al.. (2012). Epigenomics and chromatin dynamics. Genome Biology. 13(2). 313–313. 2 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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