Daniel R. Gulbranson

2.9k total citations · 1 hit paper
16 papers, 2.1k citations indexed

About

Daniel R. Gulbranson is a scholar working on Molecular Biology, Cell Biology and Surgery. According to data from OpenAlex, Daniel R. Gulbranson has authored 16 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 8 papers in Cell Biology and 2 papers in Surgery. Recurrent topics in Daniel R. Gulbranson's work include Cellular transport and secretion (8 papers), Pluripotent Stem Cells Research (6 papers) and CRISPR and Genetic Engineering (6 papers). Daniel R. Gulbranson is often cited by papers focused on Cellular transport and secretion (8 papers), Pluripotent Stem Cells Research (6 papers) and CRISPR and Genetic Engineering (6 papers). Daniel R. Gulbranson collaborates with scholars based in United States, China and Japan. Daniel R. Gulbranson's co-authors include James A. Thomson, Guokai Chen, Zhonggang Hou, Sara E. Howden, Mitchell D. Probasco, Nicholas E. Propson, Jennifer M. Bolin, Joyce Teng, Victor Ruotti and Jessica Antosiewicz‐Bourget and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Daniel R. Gulbranson

16 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 →

Peers

Daniel R. Gulbranson

SURGE

CMN

Mitchell D. Probasco United States

Jennifer M. Bolin United States

W. Travis Berggren United States

Sergey Rodin Sweden

Raymond C.B. Wong Australia

David A. Brafman United States

Nicole Dubois United States

Paul J. Gokhale United Kingdom

Luke M. Judge United States

Tenneille E. Ludwig United States

Mitchell D. Probasco United States

Daniel R. Gulbranson

1.8k ×1.0

632 ×1.0

393 ×1.0

SURGE

214 ×0.6

174 ×0.8

CMN

Citations per year, relative to Daniel R. Gulbranson Daniel R. Gulbranson (= 1×) peers Mitchell D. Probasco

Countries citing papers authored by Daniel R. Gulbranson

Since Specialization

Citations

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

Fields of papers citing papers by Daniel R. Gulbranson

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel R. Gulbranson. 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 Daniel R. Gulbranson. The network helps show where Daniel R. Gulbranson may publish in the future.

Co-authorship network of co-authors of Daniel R. Gulbranson

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

All Works

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16 of 16 papers shown

Gulbranson, Daniel R.. (2022). Generating Custom Pooled CRISPR Libraries for Genetic Dissection of Biological Pathways. Methods in molecular biology. 2473. 333–347. 1 indexed citations

Gulbranson, Daniel R., Kaitlyn Ho, Gui-Qiu Yu, et al.. (2021). Phenotypic Differences between the Alzheimer’s Disease-Related hAPP-J20 Model and HeterozygousZbtb20Knock-Out Mice. eNeuro. 8(3). ENEURO.0089–21.2021. 11 indexed citations

Miller, Jessica, Daniel R. Gulbranson, Yuan Tian, et al.. (2019). Inducible Exoc7/Exo70 knockout reveals a critical role of the exocyst in insulin-regulated GLUT4 exocytosis. Journal of Biological Chemistry. 294(52). 19988–19996. 23 indexed citations

Gulbranson, Daniel R., Myeongseon Lee, Yan Ouyang, et al.. (2019). AAGAB Controls AP2 Adaptor Assembly in Clathrin-Mediated Endocytosis. Developmental Cell. 50(4). 436–446.e5. 34 indexed citations

Shen, Chong, Yinghui Liu, Haijia Yu, et al.. (2018). The N-peptide–binding mode is critical to Munc18-1 function in synaptic exocytosis. Journal of Biological Chemistry. 293(47). 18309–18317. 7 indexed citations

Menasché, Bridget L., et al.. (2018). Fluorescence Activated Cell Sorting (FACS) in Genome‐Wide Genetic Screening of Membrane Trafficking. Current Protocols in Cell Biology. 82(1). e68–e68. 8 indexed citations

Gulbranson, Daniel R., Eric M. Davis, Brittany A. Demmitt, et al.. (2017). RABIF/MSS4 is a Rab-stabilizing holdase chaperone required for GLUT4 exocytosis. Proceedings of the National Academy of Sciences. 114(39). E8224–E8233. 50 indexed citations

Guan, Xiaoyang, Xiuli Wei, Daniel R. Gulbranson, et al.. (2017). Chemically Precise Glycoengineering Improves Human Insulin. ACS Chemical Biology. 13(1). 73–81. 29 indexed citations

Yu, Haijia, et al.. (2016). Extended synaptotagmins are Ca ²⁺ -dependent lipid transfer proteins at membrane contact sites. Proceedings of the National Academy of Sciences. 113(16). 4362–4367. 113 indexed citations

10.

Shen, Chong, Shailendra S. Rathore, Haijia Yu, et al.. (2015). The trans-SNARE-regulating function of Munc18-1 is essential to synaptic exocytosis. Nature Communications. 6(1). 8852–8852. 43 indexed citations

11.

Yu, Haijia, Shailendra S. Rathore, Daniel R. Gulbranson, & Jingshi Shen. (2014). The N- and C-terminal Domains of Tomosyn Play Distinct Roles in Soluble N-Ethylmaleimide-sensitive Factor Attachment Protein Receptor Binding and Fusion Regulation. Journal of Biological Chemistry. 289(37). 25571–25580. 21 indexed citations

12.

Beers, Jeanette, et al.. (2012). Passaging and colony expansion of human pluripotent stem cells by enzyme-free dissociation in chemically defined culture conditions. Nature Protocols. 7(11). 2029–2040. 271 indexed citations

13.

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 →

14.

Howden, Sara E., Athurva Gore, Zhe Li, et al.. (2011). Genetic correction and analysis of induced pluripotent stem cells from a patient with gyrate atrophy. Proceedings of the National Academy of Sciences. 108(16). 6537–6542. 118 indexed citations

15.

Chen, Guokai, Daniel R. Gulbranson, Pengzhi Yu, Zhonggang Hou, & James A. Thomson. (2011). Thermal Stability of Fibroblast Growth Factor Protein Is a Determinant Factor in Regulating Self-Renewal, Differentiation, and Reprogramming in Human Pluripotent Stem Cells. Stem Cells. 30(4). 623–630. 110 indexed citations

16.

Chen, Guokai, Zhonggang Hou, Daniel R. Gulbranson, & James A. Thomson. (2010). Actin-Myosin Contractility Is Responsible for the Reduced Viability of Dissociated Human Embryonic Stem Cells. Cell stem cell. 7(2). 240–248. 225 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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