Max W. Shen

3.4k total citations · 2 hit papers
18 papers, 1.9k citations indexed

About

Max W. Shen is a scholar working on Molecular Biology, Cardiology and Cardiovascular Medicine and Genetics. According to data from OpenAlex, Max W. Shen has authored 18 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 2 papers in Cardiology and Cardiovascular Medicine and 2 papers in Genetics. Recurrent topics in Max W. Shen's work include CRISPR and Genetic Engineering (11 papers), RNA and protein synthesis mechanisms (10 papers) and Advanced biosensing and bioanalysis techniques (4 papers). Max W. Shen is often cited by papers focused on CRISPR and Genetic Engineering (11 papers), RNA and protein synthesis mechanisms (10 papers) and Advanced biosensing and bioanalysis techniques (4 papers). Max W. Shen collaborates with scholars based in United States, Netherlands and Canada. Max W. Shen's co-authors include David R. Liu, Mandana Arbab, Pavel A. Pevzner, Dmitry Antipov, Mikhail Raiko, Nolan T. Hartwick, Alla Lapidus, Christopher A. Cassa, Żaneta Matuszek and Jonathan Y. Hsu and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Max W. Shen

18 papers receiving 1.9k citations

Hit Papers

plasmidSPAdes: assembling plasmids from whole genome sequ... 2016 2026 2019 2022 2016 2018 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Max W. Shen United States 12 1.6k 368 245 189 180 18 1.9k
Gregory W. Goldberg United States 9 1.4k 0.9× 343 0.9× 90 0.4× 113 0.6× 391 2.2× 10 1.6k
Christopher A. Vakulskas United States 26 2.7k 1.7× 1.4k 3.7× 335 1.4× 209 1.1× 348 1.9× 38 3.2k
Zaid Ahmed Pirzada Pakistan 8 1.9k 1.2× 425 1.2× 185 0.8× 31 0.2× 185 1.0× 11 2.1k
Manuela Villion Canada 13 2.1k 1.3× 485 1.3× 230 0.9× 47 0.2× 659 3.7× 19 2.4k
April Pawluk Canada 10 1.4k 0.9× 279 0.8× 182 0.7× 70 0.4× 601 3.3× 14 1.6k
Raymond H.J. Staals Netherlands 27 3.0k 1.9× 663 1.8× 375 1.5× 88 0.5× 873 4.8× 44 3.4k
Elena Soria Spain 10 1.6k 1.0× 376 1.0× 214 0.9× 14 0.1× 272 1.5× 23 1.9k
Frank Hille Germany 3 897 0.6× 167 0.5× 110 0.4× 22 0.1× 183 1.0× 9 1.0k
Poulami Samai United States 12 1.9k 1.2× 501 1.4× 128 0.5× 14 0.1× 245 1.4× 12 2.0k
Casey A. Gifford United States 15 1.7k 1.1× 477 1.3× 179 0.7× 373 2.0× 142 0.8× 21 2.5k

Countries citing papers authored by Max W. Shen

Since Specialization
Citations

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

Fields of papers citing papers by Max W. Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Max W. Shen. 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 Max W. Shen. The network helps show where Max W. Shen may publish in the future.

Co-authorship network of co-authors of Max W. Shen

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

All Works

18 of 18 papers shown
1.
Shen, Max W., Zhongheng Zhang, Chao Liu, et al.. (2024). Evaluating Prognostic Bias of Critical Illness Severity Scores Based on Age, Sex, and Primary Language in the United States: A Retrospective Multicenter Study. Critical Care Explorations. 6(1). e1033–e1033. 2 indexed citations
2.
Arbab, Mandana, Żaneta Matuszek, Gregory A. Newby, et al.. (2023). Base editing rescue of spinal muscular atrophy in cells and in mice. Science. 380(6642). eadg6518–eadg6518. 74 indexed citations
3.
Chiu, Leonard, Ronald Chow, Nicholas Chiu, et al.. (2022). Meta-Analysis of Point-of-Care Lung Ultrasonography Versus Chest Radiography in Adults With Symptoms of Acute Decompensated Heart Failure. The American Journal of Cardiology. 174. 89–95. 33 indexed citations
4.
Zanetti, Larissa C., Max W. Shen, Lin Lin, et al.. (2022). Peptide fusion improves prime editing efficiency. Nature Communications. 13(1). 3512–3512. 43 indexed citations
5.
Chen, Jonathan C., Max W. Shen, Michael Wornow, et al.. (2022). Generating experimentally unrelated target molecule-binding highly functionalized nucleic-acid polymers using machine learning. Nature Communications. 13(1). 4541–4541. 15 indexed citations
6.
Koblan, Luke W., Mandana Arbab, Max W. Shen, et al.. (2021). Efficient C•G-to-G•C base editors developed using CRISPRi screens, target-library analysis, and machine learning. Nature Biotechnology. 39(11). 1414–1425. 155 indexed citations
7.
Shen, Max W., Kevin T. Zhao, & David Liu. (2021). Reconstruction of evolving gene variants and fitness from short sequencing reads. Nature Chemical Biology. 17(11). 1188–1198. 6 indexed citations
8.
Hsu, Jonathan Y., Julian Grünewald, Andrew V. Anzalone, et al.. (2021). PrimeDesign software for rapid and simplified design of prime editing guide RNAs. Nature Communications. 12(1). 1034–1034. 130 indexed citations
9.
Shen, Max W., et al.. (2021). Machine learning based CRISPR gRNA design for therapeutic exon skipping. PLoS Computational Biology. 17(1). e1008605–e1008605. 7 indexed citations
10.
Culbertson, Sannie J., Benjamin Holmes, Max W. Shen, et al.. (2021). Small molecule inhibition of ATM kinase increases CRISPR-Cas9 1-bp insertion frequency. Nature Communications. 12(1). 5111–5111. 13 indexed citations
11.
Lin, Lin, Benjamin Holmes, Max W. Shen, et al.. (2020). Comprehensive Mapping of Key Regulatory Networks that Drive Oncogene Expression. Cell Reports. 33(8). 108426–108426. 11 indexed citations
12.
Miller, Shannon M., Tina Wang, Peyton B. Randolph, et al.. (2020). Continuous evolution of SpCas9 variants compatible with non-G PAMs. Nature Biotechnology. 38(4). 471–481. 257 indexed citations
13.
Arbab, Mandana, Max W. Shen, Beverly Mok, et al.. (2020). Determinants of Base Editing Outcomes from Target Library Analysis and Machine Learning. Cell. 182(2). 463–480.e30. 185 indexed citations
14.
Shen, Max W., Mandana Arbab, Jonathan Y. Hsu, et al.. (2018). Predictable and precise template-free CRISPR editing of pathogenic variants. Nature. 563(7733). 646–651. 380 indexed citations breakdown →
15.
Bossi, Flavia, Jue Fan, Max W. Shen, et al.. (2017). Systematic discovery of novel eukaryotic transcriptional regulators using sequence homology independent prediction. BMC Genomics. 18(1). 480–480. 7 indexed citations
16.
Lin, Yu, Jeffrey Yuan, Mikhail Kolmogorov, et al.. (2016). Assembly of long error-prone reads using de Bruijn graphs. Proceedings of the National Academy of Sciences. 113(52). E8396–E8405. 209 indexed citations
17.
Antipov, Dmitry, Nolan T. Hartwick, Max W. Shen, et al.. (2016). plasmidSPAdes: assembling plasmids from whole genome sequencing data. Bioinformatics. 32(22). 3380–3387. 397 indexed citations breakdown →
18.
Lin, Yu, et al.. (2016). Assembly of Long Error-Prone Reads Using de Bruijn Graphs. bioRxiv (Cold Spring Harbor Laboratory). 265. 1 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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