Daniel Shoemaker

17.6k total citations · 1 hit paper
26 papers, 3.2k citations indexed

About

Daniel Shoemaker is a scholar working on Molecular Biology, Oncology and Hematology. According to data from OpenAlex, Daniel Shoemaker has authored 26 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Molecular Biology, 6 papers in Oncology and 4 papers in Hematology. Recurrent topics in Daniel Shoemaker's work include CAR-T cell therapy research (5 papers), Fungal and yeast genetics research (5 papers) and RNA and protein synthesis mechanisms (5 papers). Daniel Shoemaker is often cited by papers focused on CAR-T cell therapy research (5 papers), Fungal and yeast genetics research (5 papers) and RNA and protein synthesis mechanisms (5 papers). Daniel Shoemaker collaborates with scholars based in United States, Italy and Japan. Daniel Shoemaker's co-authors include Eric E. Schadt, Jason M. Johnson, Ronald W. Davis, Christopher D. Armour, Philip W. Garrett-Engele, Roland Stoughton, John C. Castle, Patrick Loerch, Zhengyan Kan and Jef D. Boeke and has published in prestigious journals such as Science, Cell and Nature Genetics.

In The Last Decade

Daniel Shoemaker

26 papers receiving 3.2k citations

Hit Papers

Genome-Wide Survey of Human Alternative Pre-mRNA Splicing... 2003 2026 2010 2018 2003 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daniel Shoemaker United States 14 2.8k 332 275 258 154 26 3.2k
Christopher D. Armour United States 17 2.3k 0.8× 453 1.4× 443 1.6× 181 0.7× 83 0.5× 17 2.8k
Douglas E. Bassett United States 14 2.3k 0.8× 312 0.9× 178 0.6× 166 0.6× 59 0.4× 18 2.7k
Lawrence E. Heisler Canada 21 1.5k 0.5× 359 1.1× 166 0.6× 185 0.7× 97 0.6× 31 2.2k
Sarah E. Pierce United States 13 1.7k 0.6× 279 0.8× 277 1.0× 131 0.5× 91 0.6× 20 2.1k
Melissa S. Jurica United States 25 3.2k 1.1× 264 0.8× 234 0.9× 169 0.7× 63 0.4× 54 3.5k
Attila Reményi Hungary 26 2.7k 1.0× 292 0.9× 158 0.6× 257 1.0× 133 0.9× 50 3.3k
Joseph C. Reese United States 32 2.7k 1.0× 574 1.7× 107 0.4× 306 1.2× 52 0.3× 64 3.2k
Barbara Garvik United States 15 2.8k 1.0× 261 0.8× 177 0.6× 297 1.2× 45 0.3× 17 3.6k
Nathalie Méthot Canada 28 2.4k 0.8× 506 1.5× 188 0.7× 114 0.4× 427 2.8× 32 3.2k
Fulai Jin United States 20 3.3k 1.2× 464 1.4× 329 1.2× 377 1.5× 55 0.4× 30 3.8k

Countries citing papers authored by Daniel Shoemaker

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Shoemaker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Daniel Shoemaker

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Shoemaker. A scholar is included among the top collaborators of Daniel Shoemaker 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 Shoemaker. Daniel Shoemaker 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.
Clarke, Raedun, Chia‐Wei Chang, Tom Lee, et al.. (2017). Generation of Clonal Antigen Specific CD8αβ+ Cytotoxic T Lymphocytes from Renewable Pluripotent Stem Cells for Off-the-Shelf T Cell Therapeutics. Blood. 130. 163–163. 1 indexed citations
2.
Bjordahl, Ryan, Raedun Clarke, Svetlana Gaidarova, et al.. (2017). Multi-Functional Genetic Engineering of Pluripotent Cell Lines for Universal Off-the-Shelf Natural Killer Cell Cancer Immunotherapy. Blood. 130. 3187–3187. 1 indexed citations
4.
Mitchell, Leah, Thuy Le, Betsy Rezner, et al.. (2015). Ex Vivo Modulation of Donor Cells Results in Enhanced Survival and Reduced Gvhd Mortality. Blood. 126(23). 1884–1884. 2 indexed citations
5.
Robbins, David, Thuy Le, Heather Foster, et al.. (2014). Ex Vivo Modulation of Mobilized Peripheral Blood: Characterization of HSC and T-Cell Responses to Prostaglandin E2. Blood. 124(21). 1092–1092. 1 indexed citations
6.
Valamehr, Bahram, Ramzey Abujarour, Megan Robinson, et al.. (2012). A novel platform to enable the high-throughput derivation and characterization of feeder-free human iPSCs. Scientific Reports. 2(1). 213–213. 62 indexed citations
7.
Cutler, Corey, Caroline Desponts, David Robbins, et al.. (2011). Ex Vivo Treatment of Hematopoietic Stem Cells With 16,16-Dimethyl Prostaglandin E2 (FT1050) Improves Engraftment and Hematopoietic Reconstitution. Biology of Blood and Marrow Transplantation. 17(2). S226–S226. 2 indexed citations
9.
Lum, Pek Yee, Christopher D. Armour, S. Stepaniants, et al.. (2004). Discovering Modes of Action for Therapeutic Compounds Using a Genome-Wide Screen of Yeast Heterozygotes. Cell. 116(1). 121–137. 374 indexed citations
10.
Johnson, Jason M., Stephen W. Edwards, Daniel Shoemaker, & Eric E. Schadt. (2004). Dark matter in the genome: evidence of widespread transcription detected by microarray tiling experiments. Trends in Genetics. 21(2). 93–102. 289 indexed citations
11.
Castle, John C., Christopher D. Armour, Sven Duenwald, et al.. (2003). Optimization of oligonucleotide arrays and RNA amplification protocols for analysis of transcript structure and alternative splicing. Genome biology. 4(10). R66–R66. 70 indexed citations
12.
Wright, Robin, Mark L Parrish, Clinton K. Matson, et al.. (2003). Parallel analysis of tagged deletion mutants efficiently identifies genes involved in endoplasmic reticulum biogenesis. Yeast. 20(10). 881–892. 22 indexed citations
13.
He, Yudong D., Hongyue Dai, Eric E. Schadt, et al.. (2003). Microarray standard data set and figures of meritfor comparing data processing methods and experiment designs. Bioinformatics. 19(8). 956–965. 66 indexed citations
14.
Shoemaker, Daniel & Peter S. Linsley. (2002). Recent developments in DNA microarrays. Current Opinion in Microbiology. 5(3). 334–337. 58 indexed citations
15.
Ooi, Siew Loon, Daniel Shoemaker, & Jef D. Boeke. (2001). A DNA Microarray-Based Genetic Screen for Nonhomologous End-Joining Mutants in Saccharomyces cerevisiae. Science. 294(5551). 2552–2556. 115 indexed citations
16.
Hughes, Timothy R. & Daniel Shoemaker. (2001). DNA microarrays for expression profiling. Current Opinion in Chemical Biology. 5(1). 21–25. 39 indexed citations
17.
Winzeler, Elizabeth A., Hong Liang, Daniel Shoemaker, & Ronald W. Davis. (2000). Functional Analysis of the Yeast Genome by Precise Deletion and Parallel Phenotypic Characterization. Novartis Foundation symposium. 229. 105–111. 16 indexed citations
18.
Giaever, Guri, Daniel Shoemaker, Ted Jones, et al.. (1999). Genomic profiling of drug sensitivities via induced haploinsufficiency. Nature Genetics. 21(3). 278–283. 417 indexed citations
19.
Shoemaker, Daniel, et al.. (1996). Quantitative phenotypic analysis of yeast deletion mutants using a highly parallel molecular bar–coding strategy. Nature Genetics. 14(4). 450–456. 413 indexed citations
20.
Pritchard, G. O., et al.. (1990). Disproportionation reactions between alkyl and fluoroalkyl radicals. V. Perfluoro‐n‐propyl and ethyl radicals revisited. International Journal of Chemical Kinetics. 22(10). 1051–1069. 5 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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