Susan B. Hipkens

1.2k total citations
17 papers, 891 citations indexed

About

Susan B. Hipkens is a scholar working on Surgery, Molecular Biology and Genetics. According to data from OpenAlex, Susan B. Hipkens has authored 17 papers receiving a total of 891 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Surgery, 8 papers in Molecular Biology and 5 papers in Genetics. Recurrent topics in Susan B. Hipkens's work include Pancreatic function and diabetes (7 papers), Genetics and Neurodevelopmental Disorders (4 papers) and Congenital heart defects research (3 papers). Susan B. Hipkens is often cited by papers focused on Pancreatic function and diabetes (7 papers), Genetics and Neurodevelopmental Disorders (4 papers) and Congenital heart defects research (3 papers). Susan B. Hipkens collaborates with scholars based in United States, Japan and Canada. Susan B. Hipkens's co-authors include David M. Yurek, Mark A. Magnuson, Stanley J. Wiegand, William Lu, Lori Sussel, James B. Papizan, Anil Bhushan, Ruth A. Singer, Sangeeta Dhawan and Robert J. Dempsey and has published in prestigious journals such as Circulation, Journal of Neuroscience and Genes & Development.

In The Last Decade

Susan B. Hipkens

17 papers receiving 884 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Susan B. Hipkens United States 15 418 401 235 190 120 17 891
Irene Stolte‐Dijkstra Netherlands 13 501 1.2× 253 0.6× 379 1.6× 56 0.3× 124 1.0× 20 898
Ivana Matera Italy 16 290 0.7× 281 0.7× 192 0.8× 42 0.2× 43 0.4× 26 804
Susana González-Granero Spain 13 218 0.5× 127 0.3× 78 0.3× 70 0.4× 85 0.7× 31 624
Thea Shavlakadze Australia 16 861 2.1× 100 0.2× 69 0.3× 118 0.6× 91 0.8× 21 1.1k
Megan A. Waldrop United States 17 432 1.0× 191 0.5× 163 0.7× 78 0.4× 29 0.2× 48 677
Katja Eggermann Germany 20 703 1.7× 239 0.6× 527 2.2× 135 0.7× 22 0.2× 44 1.2k
Daniel M. Warthen United States 7 311 0.7× 297 0.7× 118 0.5× 98 0.5× 45 0.4× 7 751
Seumas McCroskery New Zealand 6 745 1.8× 156 0.4× 108 0.5× 90 0.5× 31 0.3× 6 894
Natacha Roblot France 11 542 1.3× 180 0.4× 71 0.3× 198 1.0× 13 0.1× 14 939
Miranda Splitt United Kingdom 15 598 1.4× 173 0.4× 435 1.9× 65 0.3× 7 0.1× 29 1.1k

Countries citing papers authored by Susan B. Hipkens

Since Specialization
Citations

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

Fields of papers citing papers by Susan B. Hipkens

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Susan B. Hipkens. 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 Susan B. Hipkens. The network helps show where Susan B. Hipkens may publish in the future.

Co-authorship network of co-authors of Susan B. Hipkens

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

All Works

17 of 17 papers shown
1.
Bechard, Matthew E., Eric D. Bankaitis, Susan B. Hipkens, et al.. (2016). Precommitment low-level Neurog3 expression defines a long-lived mitotic endocrine-biased progenitor pool that drives production of endocrine-committed cells. Genes & Development. 30(16). 1852–1865. 46 indexed citations
2.
Osipovich, Anna B., Qiaoming Long, Elisabetta Manduchi, et al.. (2014). Insm1 promotes endocrine cell differentiation by modulating the expression of a network of genes that includes Neurog3 and Ripply3. Development. 141(15). 2939–2949. 54 indexed citations
3.
Arnes, Luís, et al.. (2012). Generation of Nkx2.2:lacZ mice using recombination‐mediated cassette exchange technology. genesis. 50(8). 612–624. 14 indexed citations
4.
Atack, Thomas C., Dina Myers Stroud, Hiroshi Watanabe, et al.. (2011). Informatic and Functional Approaches to Identifying a Regulatory Region for the Cardiac Sodium Channel. Circulation Research. 109(1). 38–46. 10 indexed citations
5.
Watanabe, Hiroshi, Tao Yang, Dina Myers Stroud, et al.. (2011). Striking In Vivo Phenotype of a Disease-Associated Human SCN5A Mutation Producing Minimal Changes in Vitro. Circulation. 124(9). 1001–1011. 90 indexed citations
6.
Papizan, James B., Ruth A. Singer, Sangeeta Dhawan, et al.. (2011). Nkx2.2 repressor complex regulates islet β-cell specification and prevents β-to-α-cell reprogramming. Genes & Development. 25(21). 2291–2305. 152 indexed citations
7.
Choi, Eunyoung, et al.. (2011). A recombinase‐mediated cassette exchange‐derived cyan fluorescent protein reporter allele for Pdx1. genesis. 50(4). 384–392. 8 indexed citations
8.
Osipovich, Anna B., Alessandro Ustione, Susan B. Hipkens, et al.. (2011). Quantification of factors influencing fluorescent protein expression using RMCE to generate an allelic series in theROSA26locus in mice. Disease Models & Mechanisms. 4(4). 537–547. 38 indexed citations
9.
Zhang, Hongjie, Elizabeth T. Ables, M. Kay Washington, et al.. (2009). Multiple, temporal-specific roles for HNF6 in pancreatic endocrine and ductal differentiation. Mechanisms of Development. 126(11-12). 958–973. 84 indexed citations
10.
Wang, Sui, Jia Zhang, Aizhen Zhao, et al.. (2007). Loss of Myt1 function partially compromises endocrine islet cell differentiation and pancreatic physiological function in the mouse. Mechanisms of Development. 124(11-12). 898–910. 57 indexed citations
11.
Oottamasathien, Siam, Yongqing Wang, Karin Williams, et al.. (2007). Directed differentiation of embryonic stem cells into bladder tissue. Developmental Biology. 304(2). 556–566. 74 indexed citations
12.
Liu, Kai, Susan B. Hipkens, Tao Yang, et al.. (2006). Recombinase‐mediated cassette exchange to rapidly and efficiently generate mice with human cardiac sodium channels. genesis. 44(11). 556–564. 16 indexed citations
13.
Yurek, David M., Susan B. Hipkens, Stanley J. Wiegand, & C. Anthony Altar. (1998). Optimal Effectiveness of BDNF for Fetal Nigral Transplants Coincides with the Ontogenic Appearance of BDNF in the Striatum. Journal of Neuroscience. 18(15). 6040–6047. 22 indexed citations
14.
Yurek, David M., William Lu, Susan B. Hipkens, & Stanley J. Wiegand. (1996). BDNF Enhances the Functional Reinnervation of the Striatum by Grafted Fetal Dopamine Neurons. Experimental Neurology. 137(1). 105–118. 119 indexed citations
15.
Yurek, David M. & Susan B. Hipkens. (1994). Intranigral injections of SCH 23390 inhibit SKF 82958-induced rotational behavior. Brain Research. 639(2). 329–332. 20 indexed citations
16.
Prasad, M. Renuka, et al.. (1994). Regional Levels of Lactate and Norepinephrine After Experimental Brain Injury. Journal of Neurochemistry. 63(3). 1086–1094. 64 indexed citations
17.
Yurek, David M. & Susan B. Hipkens. (1993). Intranigral injections of SCH 23390 inhibit amphetamine-induced rotational behavior. Brain Research. 623(1). 56–64. 23 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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