Mitchell D. Probasco

2.9k total citations · 2 hit papers
12 papers, 2.1k citations indexed

About

Mitchell D. Probasco is a scholar working on Molecular Biology, Biomedical Engineering and Spectroscopy. According to data from OpenAlex, Mitchell D. Probasco has authored 12 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, 4 papers in Biomedical Engineering and 2 papers in Spectroscopy. Recurrent topics in Mitchell D. Probasco's work include Pluripotent Stem Cells Research (9 papers), 3D Printing in Biomedical Research (4 papers) and CRISPR and Genetic Engineering (3 papers). Mitchell D. Probasco is often cited by papers focused on Pluripotent Stem Cells Research (9 papers), 3D Printing in Biomedical Research (4 papers) and CRISPR and Genetic Engineering (3 papers). Mitchell D. Probasco collaborates with scholars based in United States and Germany. Mitchell D. Probasco's co-authors include James A. Thomson, Jennifer M. Bolin, Victor Ruotti, Mark E. Levenstein, Veit Bergendahl, Junying Yu, Tenneille E. Ludwig, Zhonggang Hou, Nicholas E. Propson and Guokai Chen and has published in prestigious journals such as Nature Methods, Cell Reports and PLoS Computational Biology.

In The Last Decade

Mitchell D. Probasco

11 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.

Chemically defined conditions for human iPSC derivation and culture

2011 1.1k citations Guokai Chen, Daniel R. Gulbranson et al. Nature Methods profile →
Feeder-independent culture of human embryonic stem cells

2006 507 citations Tenneille E. Ludwig, Veit Bergendahl et al. Nature Methods profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mitchell D. Probasco United States	8	1.8k	632	393	214	174	12	2.1k
Daniel R. Gulbranson United States	12	1.8k 1.0×	628 1.0×	378 1.0×	351 1.6×	222 1.3×	16	2.1k
Jennifer M. Bolin United States	16	1.8k 1.0×	727 1.2×	345 0.9×	139 0.6×	207 1.2×	23	2.2k
Ralph Brandenberger United States	13	2.0k 1.1×	613 1.0×	442 1.1×	199 0.9×	193 1.1×	16	2.4k
Miho Furue Japan	26	1.7k 0.9×	690 1.1×	729 1.9×	205 1.0×	98 0.6×	65	2.4k
Elizabeth Ng Australia	13	1.2k 0.7×	328 0.5×	470 1.2×	251 1.2×	188 1.1×	20	1.5k
Raymond C.B. Wong Australia	27	1.5k 0.8×	294 0.5×	235 0.6×	144 0.7×	280 1.6×	79	1.9k
Mudit Gupta United States	15	1.5k 0.8×	337 0.5×	303 0.8×	147 0.7×	125 0.7×	26	2.0k
Nicole Dubois United States	19	2.1k 1.2×	431 0.7×	898 2.3×	180 0.8×	314 1.8×	36	2.6k
Daniel Ortmann United Kingdom	18	1.4k 0.8×	428 0.7×	302 0.8×	142 0.7×	113 0.6×	28	1.9k
Paul J. Gokhale United Kingdom	23	2.6k 1.4×	512 0.8×	460 1.2×	187 0.9×	149 0.9×	38	2.9k

Countries citing papers authored by Mitchell D. Probasco

Since Specialization

Citations

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

Fields of papers citing papers by Mitchell D. Probasco

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mitchell D. Probasco. 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 Mitchell D. Probasco. The network helps show where Mitchell D. Probasco may publish in the future.

Co-authorship network of co-authors of Mitchell D. Probasco

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

All Works

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12 of 12 papers shown

Zhang, Jue, Diana M. Tabima, David Vereide, et al.. (2025). Small-diameter artery grafts engineered from pluripotent stem cells maintain 100% patency in an allogeneic rhesus macaque model. Cell Reports Medicine. 6(3). 102002–102002. 1 indexed citations

Probasco, Mitchell D., Vadim Demichev, Daniel A. Polasky, et al.. (2025). SynchroSep-MS: Parallel LC Separations for Multiplexed Proteomics. Journal of the American Society for Mass Spectrometry. 36(9). 1979–1987.

Barry, Christopher, Matthew T. Schmitz, Jennifer M. Bolin, et al.. (2019). Automated minute scale RNA-seq of pluripotent stem cell differentiation reveals early divergence of human and mouse gene expression kinetics. PLoS Computational Biology. 15(12). e1007543–e1007543. 7 indexed citations

Zhang, Jue, Brian E. McIntosh, Bowen Wang, et al.. (2019). A Human Pluripotent Stem Cell-Based Screen for Smooth Muscle Cell Differentiation and Maturation Identifies Inhibitors of Intimal Hyperplasia. Stem Cell Reports. 12(6). 1269–1281. 20 indexed citations

Chasman, Deborah, Nisha Iyer, Alireza Fotuhi Siahpirani, et al.. (2019). Inferring Regulatory Programs Governing Region Specificity of Neuroepithelial Stem Cells during Early Hindbrain and Spinal Cord Development. Cell Systems. 9(2). 167–186.e12. 11 indexed citations

Barry, Christopher, Matthew T. Schmitz, Nicholas E. Propson, et al.. (2017). Uniform neural tissue models produced on synthetic hydrogels using standard culture techniques. Experimental Biology and Medicine. 242(17). 1679–1689. 30 indexed citations

Stewart, Ron, Shulan Tian, Jeff Nie, et al.. (2013). Comparative RNA-seq Analysis in the Unsequenced Axolotl: The Oncogene Burst Highlights Early Gene Expression in the Blastema. PLoS Computational Biology. 9(3). e1002936–e1002936. 105 indexed citations

Vodyanik, Maxim A., Padma Priya Togarrati, Kran Suknuntha, et al.. (2012). Identification of the Hemogenic Endothelial Progenitor and Its Direct Precursor in Human Pluripotent Stem Cell Differentiation Cultures. Cell Reports. 2(3). 553–567. 157 indexed citations

Chen, Guokai, Daniel R. Gulbranson, Zhonggang Hou, et al.. (2011). Chemically defined conditions for human iPSC derivation and culture. Nature Methods. 8(5). 424–429. 1073 indexed citations breakdown →

10.

Phanstiel, Douglas H., Justin Brumbaugh, Craig D. Wenger, et al.. (2011). Proteomic and phosphoproteomic comparison of human ES and iPS cells. Nature Methods. 8(10). 821–827. 217 indexed citations

11.

Probasco, Mitchell D., Nancy E. Thompson, & Richard R. Burgess. (2007). Immunoaffinity purification and characterization of RNA polymerase from Shewanella oneidensis. Protein Expression and Purification. 55(1). 23–30. 5 indexed citations

12.

Ludwig, Tenneille E., Veit Bergendahl, Mark E. Levenstein, et al.. (2006). Feeder-independent culture of human embryonic stem cells. Nature Methods. 3(8). 637–646. 507 indexed citations breakdown →

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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