Shannon Eaker

1.1k total citations
22 papers, 807 citations indexed

About

Shannon Eaker is a scholar working on Molecular Biology, Biomedical Engineering and Physiology. According to data from OpenAlex, Shannon Eaker has authored 22 papers receiving a total of 807 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Molecular Biology, 7 papers in Biomedical Engineering and 4 papers in Physiology. Recurrent topics in Shannon Eaker's work include DNA Repair Mechanisms (5 papers), Biomedical Ethics and Regulation (4 papers) and Pluripotent Stem Cells Research (4 papers). Shannon Eaker is often cited by papers focused on DNA Repair Mechanisms (5 papers), Biomedical Ethics and Regulation (4 papers) and Pluripotent Stem Cells Research (4 papers). Shannon Eaker collaborates with scholars based in United States, Germany and United Kingdom. Shannon Eaker's co-authors include Mary Ann Handel, John Cobb, April D. Pyle, Amy L. Inselman, Eytan Abraham, Julie Allickson, Ohad Karnieli, Nan Zhang, Sarah Griffiths and Sunghoon Jung and has published in prestigious journals such as Oncogene, Biochemical and Biophysical Research Communications and Journal of Cell Science.

In The Last Decade

Shannon Eaker

21 papers receiving 794 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shannon Eaker United States 13 479 159 150 136 114 22 807
Seyedeh‐Nafiseh Hassani Iran 22 785 1.6× 153 1.0× 124 0.8× 137 1.0× 135 1.2× 68 1.2k
Karsten Gavénis Germany 20 268 0.6× 64 0.4× 110 0.7× 42 0.3× 110 1.0× 42 1000
Huayu Zhu China 22 792 1.7× 83 0.5× 120 0.8× 58 0.4× 23 0.2× 37 1.2k
Daiji Okamura Japan 16 1.1k 2.4× 205 1.3× 303 2.0× 38 0.3× 117 1.0× 25 1.3k
Sung‐Keun Kang South Korea 13 377 0.8× 345 2.2× 233 1.6× 190 1.4× 29 0.3× 25 782
Rajesh V. Kamath United States 15 425 0.9× 253 1.6× 142 0.9× 47 0.3× 26 0.2× 24 1.1k
Monika Vishnoi United States 15 316 0.7× 65 0.4× 151 1.0× 35 0.3× 68 0.6× 21 809
Eduardo Mitrani Israel 19 852 1.8× 150 0.9× 390 2.6× 33 0.2× 54 0.5× 51 1.2k
Xiao-Rong An China 12 673 1.4× 89 0.6× 259 1.7× 42 0.3× 51 0.4× 30 957
Sun‐A Ock South Korea 21 530 1.1× 421 2.6× 205 1.4× 405 3.0× 53 0.5× 56 1.2k

Countries citing papers authored by Shannon Eaker

Since Specialization
Citations

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

Fields of papers citing papers by Shannon Eaker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Shannon Eaker. 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 Shannon Eaker. The network helps show where Shannon Eaker may publish in the future.

Co-authorship network of co-authors of Shannon Eaker

This figure shows the co-authorship network connecting the top 25 collaborators of Shannon Eaker. A scholar is included among the top collaborators of Shannon Eaker 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 Shannon Eaker. Shannon Eaker 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.
Cerbo, Vincenzo Di, Hannah Song, Sean J. Hart, et al.. (2025). Artificial intelligence, machine learning, and digitalization systems in the cell and gene therapy sector: a guidance document from the ISCT industry committees. Cytotherapy. 27(8). 903–909. 1 indexed citations
2.
Culiat, Cymbeline T., Dharmendra Kumar Soni, Mark D. Wienhold, et al.. (2024). NELL1 variant protein (NV1) modulates hyper-inflammation, Th-1 mediated immune response, and the HIF-1α hypoxia pathway to promote healing in viral-induced lung injury. Biochemical and Biophysical Research Communications. 744. 151198–151198.
3.
Criswell, Tracy, et al.. (2022). Shipping and Logistics Considerations for Regenerative Medicine Therapies. Stem Cells Translational Medicine. 11(2). 107–113. 10 indexed citations
4.
Zhang, Hu, David E. Kent, Mohammad Z. Albanna, et al.. (2021). Bioreactor Technology for Cell Therapy Manufacturing in Regenerative Medicine. Current Stem Cell Reports. 7(4). 212–218. 4 indexed citations
5.
Atala, Anthony, et al.. (2020). Regen med therapeutic opportunities for fighting COVID-19. Stem Cells Translational Medicine. 10(1). 5–13. 10 indexed citations
6.
7.
Fedczyna, Tamara O., et al.. (2017). Integrating a 19F MRI Tracer Agent into the Clinical Scale Manufacturing of a T-Cell Immunotherapy. Contrast Media & Molecular Imaging. 2017. 1–7. 10 indexed citations
8.
Karnieli, Ohad, Julie Allickson, Nan Zhang, et al.. (2016). A consensus introduction to serum replacements and serum-free media for cellular therapies. Cytotherapy. 19(2). 155–169. 151 indexed citations
9.
Gehring, Andrew, Ted C. Chu, Chitrita DebRoy, et al.. (2013). A High-Throughput Antibody-Based Microarray Typing Platform. Sensors. 13(5). 5737–5748. 8 indexed citations
10.
Eaker, Shannon, Myriam Armant, Harvey Brandwein, et al.. (2013). Concise Review: Guidance in Developing Commercializable Autologous/Patient-Specific Cell Therapy Manufacturing. Stem Cells Translational Medicine. 2(11). 871–883. 45 indexed citations
11.
12.
Riz, Irene, Sergey Akimov, Shannon Eaker, et al.. (2007). TLX1/HOX11-induced hematopoietic differentiation blockade. Oncogene. 26(28). 4115–4123. 15 indexed citations
13.
Eaker, Shannon, et al.. (2005). Detection of CFTR mutations using ARMS and low-density microarrays. Biosensors and Bioelectronics. 21(6). 933–939. 3 indexed citations
14.
Eaker, Shannon, Teresa S. Hawley, Ali Ramezani, & Robert G. Hawley. (2004). Detection and Enrichment of Hematopoietic Stem Cells by Side Population Phenotype. Humana Press eBooks. 263. 161–180. 14 indexed citations
15.
Inselman, Amy L., Shannon Eaker, & Mary Ann Handel. (2003). Temporal expression of cell cycle-related proteins during spermatogenesis: establishing a timeline for onset of the meiotic divisions. Cytogenetic and Genome Research. 103(3-4). 277–284. 63 indexed citations
16.
Libby, Brian, Rabindranath De La Fuente, Marilyn J. O’Brien, et al.. (2002). The Mouse Meiotic Mutation mei1 Disrupts Chromosome Synapsis with Sexually Dimorphic Consequences for Meiotic Progression. Developmental Biology. 242(2). 174–187. 110 indexed citations
17.
Eaker, Shannon, John Cobb, April D. Pyle, & Mary Ann Handel. (2002). Meiotic Prophase Abnormalities and Metaphase Cell Death in MLH1-Deficient Mouse Spermatocytes: Insights into Regulation of Spermatogenic Progress. Developmental Biology. 249(1). 85–95. 90 indexed citations
18.
Eaker, Shannon, April D. Pyle, John Cobb, & Mary Ann Handel. (2001). Evidence for meiotic spindle checkpoint from analysis of spermatocytes from Robertsonian-chromosome heterozygous mice. Journal of Cell Science. 114(16). 2953–2965. 122 indexed citations
19.
Handel, Mary Ann, John Cobb, & Shannon Eaker. (1999). What are the spermatocyte's requirements for successful meiotic division?. Journal of Experimental Zoology. 285(3). 243–250. 32 indexed citations
20.
Handel, Mary Ann, John B. Cobb, & Shannon Eaker. (1999). What are the spermatocyte's requirements for successful meiotic division?. Journal of Experimental Zoology. 285(3). 243–250. 2 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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