Mark A. DeWitt

4.0k total citations · 2 hit papers
22 papers, 2.1k citations indexed

About

Mark A. DeWitt is a scholar working on Molecular Biology, Cell Biology and Genetics. According to data from OpenAlex, Mark A. DeWitt has authored 22 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Molecular Biology, 7 papers in Cell Biology and 4 papers in Genetics. Recurrent topics in Mark A. DeWitt's work include CRISPR and Genetic Engineering (10 papers), Microtubule and mitosis dynamics (6 papers) and Hemoglobinopathies and Related Disorders (4 papers). Mark A. DeWitt is often cited by papers focused on CRISPR and Genetic Engineering (10 papers), Microtubule and mitosis dynamics (6 papers) and Hemoglobinopathies and Related Disorders (4 papers). Mark A. DeWitt collaborates with scholars based in United States, Switzerland and Japan. Mark A. DeWitt's co-authors include Jacob E. Corn, Gemma L. Curie, Chris D. Richardson, Graham J. Ray, Ahmet Yıldız, Dana Carroll, David Farrens, Amy Chang, Peter A. Combs and Mark C. Walters and has published in prestigious journals such as Science, Nature Communications and ACS Nano.

In The Last Decade

Mark A. DeWitt

22 papers receiving 2.1k citations

Hit Papers

Enhancing homology-direct... 2016 2026 2019 2022 2016 2016 250 500 750

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Mark A. DeWitt 1.9k 451 308 151 144 22 2.1k
Kyle A. Barlow 1.8k 1.0× 475 1.1× 53 0.2× 15 0.1× 104 0.7× 8 2.0k
Wulan Deng 1.8k 1.0× 206 0.5× 56 0.2× 233 1.5× 36 0.3× 21 2.0k
Joao Matos 2.7k 1.4× 390 0.9× 811 2.6× 8 0.1× 24 0.2× 41 2.8k
Leifu Chang 1.5k 0.8× 99 0.2× 674 2.2× 7 0.0× 60 0.4× 31 1.7k
Jens Kleinjung 1.3k 0.7× 173 0.4× 106 0.3× 28 0.2× 26 0.2× 40 1.6k
Justin A. Bosch 1.3k 0.7× 181 0.4× 858 2.8× 10 0.1× 7 0.0× 23 1.8k
Alexander P. Fields 1.3k 0.7× 115 0.3× 77 0.3× 13 0.1× 11 0.1× 13 1.6k
Pablo Huertas 3.1k 1.7× 319 0.7× 382 1.2× 31 0.2× 3 0.0× 66 3.3k
Keith T. Gagnon 1.7k 0.9× 104 0.2× 30 0.1× 111 0.7× 23 0.2× 46 1.9k
Yolanda Markaki 1.6k 0.8× 227 0.5× 146 0.5× 15 0.1× 5 0.0× 25 2.0k

Countries citing papers authored by Mark A. DeWitt

Since Specialization
Citations

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

Fields of papers citing papers by Mark A. DeWitt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mark A. DeWitt. 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 Mark A. DeWitt. The network helps show where Mark A. DeWitt may publish in the future.

Co-authorship network of co-authors of Mark A. DeWitt

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

All Works

20 of 20 papers shown
1.
Magis, Wendy, Mark A. DeWitt, Stacia K. Wyman, et al.. (2022). High-level correction of the sickle mutation is amplified in vivo during erythroid differentiation. iScience. 25(6). 104374–104374. 29 indexed citations
2.
Magis, Wendy, Mark A. DeWitt, Stacia K. Wyman, et al.. (2021). High-Level Correction of the Sickle Mutation is Amplified in Vivo During Erythroid Differentiation. SSRN Electronic Journal. 1 indexed citations
3.
Parra, Marilyn, Weiguo Zhang, Jonathan T. Vu, Mark A. DeWitt, & John G. Conboy. (2020). Antisense targeting of decoy exons can reduce intron retention and increase protein expression in human erythroblasts. RNA. 26(8). 996–1005. 9 indexed citations
4.
Boontanrart, Mandy, Markus Schröder, Stacia K. Wyman, et al.. (2020). ATF4 Regulates MYB to Increase γ-Globin in Response to Loss of β-Globin. Cell Reports. 32(5). 107993–107993. 22 indexed citations
5.
Shin, Jiyung, Markus Schröder, Francisco Caiado, et al.. (2020). Controlled Cycling and Quiescence Enables Efficient HDR in Engraftment-Enriched Adult Hematopoietic Stem and Progenitor Cells. Cell Reports. 32(9). 108093–108093. 57 indexed citations
6.
Magis, Wendy, Jonathan T. Vu, Seok‐Jin Heo, et al.. (2019). CRISPR-Cas9 interrogation of a putative fetal globin repressor in human erythroid cells. PLoS ONE. 14(1). e0208237–e0208237. 21 indexed citations
7.
Lomova, Anastasia, Beatriz Campo-Fernández, Carmen Flores, et al.. (2018). Improving Gene Editing Outcomes in Human Hematopoietic Stem and Progenitor Cells by Temporal Control of DNA Repair. Stem Cells. 37(2). 284–294. 68 indexed citations
8.
Romero, Zulema, Mark A. DeWitt, & Mark C. Walters. (2018). Promise of gene therapy to treat sickle cell disease. Expert Opinion on Biological Therapy. 18(11). 1123–1136. 21 indexed citations
9.
10.
DeWitt, Mark A., Jacob E. Corn, & Dana Carroll. (2017). Genome editing via delivery of Cas9 ribonucleoprotein. Methods. 121-122. 9–15. 118 indexed citations
11.
Wichner, Sara, Alexander S. Powers, Mustafa Mir, et al.. (2017). Covalent Protein Labeling and Improved Single-Molecule Optical Properties of Aqueous CdSe/CdS Quantum Dots. ACS Nano. 11(7). 6773–6781. 39 indexed citations
12.
Richardson, Chris D., Graham J. Ray, Mark A. DeWitt, Gemma L. Curie, & Jacob E. Corn. (2016). Enhancing homology-directed genome editing by catalytically active and inactive CRISPR-Cas9 using asymmetric donor DNA. Nature Biotechnology. 34(3). 339–344. 775 indexed citations breakdown →
13.
DeWitt, Mark A., et al.. (2015). Bidirectional Helical Motility of Cytoplasmic Dynein around Microtubules. Biophysical Journal. 108(2). 22a–22a. 2 indexed citations
14.
DeWitt, Mark A., et al.. (2014). The AAA3 domain of cytoplasmic dynein acts as a switch to facilitate microtubule release. Nature Structural & Molecular Biology. 22(1). 73–80. 60 indexed citations
15.
DeWitt, Mark A., T. Schenkel, & Ahmet Yıldız. (2014). Fluorescence Tracking of Motor Proteins In Vitro. Proceedings of the Fourth International Symposium on Polarization Phenomena in Nuclear Reactions. 105. 211–234. 2 indexed citations
16.
DeWitt, Mark A., et al.. (2014). Tension on the linker gates the ATP-dependent release of dynein from microtubules. Nature Communications. 5(1). 4587–4587. 63 indexed citations
17.
DeWitt, Mark A., et al.. (2014). Bidirectional helical motility of cytoplasmic dynein around microtubules. eLife. 3. e03205–e03205. 50 indexed citations
18.
DeWitt, Mark A., Amy Chang, Peter A. Combs, & Ahmet Yıldız. (2011). Cytoplasmic Dynein Moves Through Uncoordinated Stepping of the AAA+ Ring Domains. Science. 335(6065). 221–225. 143 indexed citations
19.
Tsukamoto, Hisao, Abhinav Sinha, Mark A. DeWitt, & David Farrens. (2010). Monomeric Rhodopsin Is the Minimal Functional Unit Required for Arrestin Binding. Journal of Molecular Biology. 399(3). 501–511. 80 indexed citations
20.
DeWitt, Mark A., Joseph I. Kliegman, John D. Helmann, et al.. (2006). The Conformations of the Manganese Transport Regulator of Bacillus subtilis in its Metal-free State. Journal of Molecular Biology. 365(5). 1257–1265. 28 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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