Casey M. Daniels

516 total citations
9 papers, 422 citations indexed

About

Casey M. Daniels is a scholar working on Oncology, Physiology and Immunology. According to data from OpenAlex, Casey M. Daniels has authored 9 papers receiving a total of 422 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Oncology, 4 papers in Physiology and 4 papers in Immunology. Recurrent topics in Casey M. Daniels's work include PARP inhibition in cancer therapy (8 papers), Calcium signaling and nucleotide metabolism (4 papers) and Neutropenia and Cancer Infections (2 papers). Casey M. Daniels is often cited by papers focused on PARP inhibition in cancer therapy (8 papers), Calcium signaling and nucleotide metabolism (4 papers) and Neutropenia and Cancer Infections (2 papers). Casey M. Daniels collaborates with scholars based in United States, Australia and Japan. Casey M. Daniels's co-authors include Anthony K. L. Leung, Shao‐En Ong, Sandra B. Gabelli, Luca Palazzo, Joanne E. Nettleship, Nahid Rahman, Kazuki Kato, Osamu Nureki, Robert Lyle McPherson and Ivan Ahel and has published in prestigious journals such as Molecular Cell, Scientific Reports and FEBS Journal.

In The Last Decade

Casey M. Daniels

8 papers receiving 419 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Casey M. Daniels United States	7	326	202	167	126	65	9	422
Nadia Dani Italy	8	195 0.6×	140 0.7×	120 0.7×	109 0.9×	33 0.5×	13	299
Zhihua Tao United States	11	252 0.8×	231 1.1×	111 0.7×	37 0.3×	65 1.0×	13	457
Nasreen Aboul-Ela United States	9	438 1.3×	279 1.4×	228 1.4×	147 1.2×	65 1.0×	11	525
Phyllis L. Panzeter Switzerland	11	485 1.5×	380 1.9×	171 1.0×	103 0.8×	64 1.0×	17	570
Harikanth Venkannagari Finland	12	240 0.7×	311 1.5×	127 0.8×	47 0.4×	49 0.8×	17	477
Morgan Dasovich United States	7	166 0.5×	161 0.8×	75 0.4×	47 0.4×	24 0.4×	11	270
Donald D. Ruhl United States	7	288 0.9×	468 2.3×	63 0.4×	57 0.5×	77 1.2×	8	616
Stefan Kernstock Norway	8	203 0.6×	281 1.4×	99 0.6×	82 0.7×	25 0.4×	8	433
Hilda Mendoza‐Alvarez United States	10	458 1.4×	350 1.7×	113 0.7×	79 0.6×	86 1.3×	12	528
Annika Krüger Germany	12	194 0.6×	287 1.4×	44 0.3×	31 0.2×	51 0.8×	15	403

Countries citing papers authored by Casey M. Daniels

Since Specialization

Citations

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

Fields of papers citing papers by Casey M. Daniels

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Casey M. Daniels. 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 Casey M. Daniels. The network helps show where Casey M. Daniels may publish in the future.

Co-authorship network of co-authors of Casey M. Daniels

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

All Works

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9 of 9 papers shown

1.

Daniels, Casey M., et al.. (2025). PARP Inhibition Shifts Murine Myeloid Cells Toward a More Tolerogenic Profile In Vivo. Biomolecules. 15(8). 1149–1149.

2.

Suh, Moo‐Jin, Joshua B. Powers, Casey M. Daniels, & Yuling Wu. (2023). Enhanced Pharmacokinetic Bioanalysis of Antibody–drug Conjugates using Hybrid Immunoaffinity Capture and Microflow LC-MS/MS. The AAPS Journal. 25(4). 68–68. 8 indexed citations

3.

Daniels, Casey M., Clinton J. Bradfield, Trisha Tucholski, et al.. (2020). Dynamic ADP-Ribosylome, Phosphoproteome, and Interactome in LPS-Activated Macrophages. Journal of Proteome Research. 19(9). 3716–3731. 16 indexed citations

4.

Daniels, Casey M., et al.. (2020). Simultaneous, Quantitative Characterization of Protein ADP-Ribosylation and Protein Phosphorylation in Macrophages. Methods in molecular biology. 2184. 145–160. 1 indexed citations

5.

Daniels, Casey M., Shao‐En Ong, & Anthony K. L. Leung. (2017). ADP-Ribosylated Peptide Enrichment and Site Identification: The Phosphodiesterase-Based Method. Methods in molecular biology. 1608. 79–93. 18 indexed citations

6.

Palazzo, Luca, Casey M. Daniels, Joanne E. Nettleship, et al.. (2016). ENPP1 processes protein ADP‐ribosylation in vitro. FEBS Journal. 283(18). 3371–3388. 67 indexed citations

7.

Daniels, Casey M., et al.. (2015). Nudix hydrolases degrade protein-conjugated ADP-ribose. Scientific Reports. 5(1). 18271–18271. 53 indexed citations

8.

Daniels, Casey M., et al.. (2015). The Promise of Proteomics for the Study of ADP-Ribosylation. Molecular Cell. 58(6). 911–924. 157 indexed citations

9.

Daniels, Casey M., Shao‐En Ong, & Anthony K. L. Leung. (2014). Phosphoproteomic Approach to Characterize Protein Mono- and Poly(ADP-ribosyl)ation Sites from Cells. Journal of Proteome Research. 13(8). 3510–3522. 102 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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