Don S. Daly

1.3k total citations
39 papers, 975 citations indexed

About

Don S. Daly is a scholar working on Molecular Biology, Spectroscopy and Biomedical Engineering. According to data from OpenAlex, Don S. Daly has authored 39 papers receiving a total of 975 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Molecular Biology, 12 papers in Spectroscopy and 4 papers in Biomedical Engineering. Recurrent topics in Don S. Daly's work include Advanced Proteomics Techniques and Applications (10 papers), Advanced Biosensing Techniques and Applications (9 papers) and Gene expression and cancer classification (8 papers). Don S. Daly is often cited by papers focused on Advanced Proteomics Techniques and Applications (10 papers), Advanced Biosensing Techniques and Applications (9 papers) and Gene expression and cancer classification (8 papers). Don S. Daly collaborates with scholars based in United States, France and Canada. Don S. Daly's co-authors include Kevin K. Anderson, Matthew Monroe, Richard C. Zangar, Ricardo Murga, Philip S. Stewart, Richard Smith, Joshua Adkins, A. M. White, Darrell P. Chandler and Kristin H. Jarman and has published in prestigious journals such as Bioinformatics, Applied and Environmental Microbiology and Journal of Clinical Microbiology.

In The Last Decade

Don S. Daly

37 papers receiving 955 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Don S. Daly United States 14 556 214 142 106 70 39 975
Yu Fu China 21 989 1.8× 217 1.0× 248 1.7× 69 0.7× 69 1.0× 81 1.9k
Wen Ding China 21 599 1.1× 82 0.4× 57 0.4× 129 1.2× 16 0.2× 43 1.1k
Andreas Jakob Germany 19 457 0.8× 217 1.0× 222 1.6× 88 0.8× 33 0.5× 28 1.5k
Manmilan Singh United States 16 603 1.1× 118 0.6× 84 0.6× 120 1.1× 39 0.6× 25 1.1k
Delphine Debois Belgium 21 572 1.0× 459 2.1× 57 0.4× 56 0.5× 55 0.8× 28 1.4k
Qian Dong China 22 389 0.7× 139 0.6× 430 3.0× 144 1.4× 17 0.2× 66 1.8k
Saw Yen Ow United Kingdom 20 1.2k 2.1× 592 2.8× 82 0.6× 198 1.9× 13 0.2× 36 1.6k
Johannes Müller Germany 18 1.1k 1.9× 361 1.7× 253 1.8× 156 1.5× 19 0.3× 27 1.7k
Josselin Noirel United Kingdom 21 1.2k 2.1× 553 2.6× 117 0.8× 149 1.4× 11 0.2× 47 1.7k
Peter Hufnagel Germany 11 600 1.1× 302 1.4× 44 0.3× 123 1.2× 27 0.4× 13 1.0k

Countries citing papers authored by Don S. Daly

Since Specialization
Citations

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

Fields of papers citing papers by Don S. Daly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Don S. Daly. 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 Don S. Daly. The network helps show where Don S. Daly may publish in the future.

Co-authorship network of co-authors of Don S. Daly

This figure shows the co-authorship network connecting the top 25 collaborators of Don S. Daly. A scholar is included among the top collaborators of Don S. Daly 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 Don S. Daly. Don S. Daly 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.
Jin, Hongjun, Teal S. Hallstrand, Don S. Daly, et al.. (2013). A halotyrosine antibody that detects increased protein modifications in asthma patients. Journal of Immunological Methods. 403(1-2). 17–25. 11 indexed citations
2.
Jin, Hongjun, Don S. Daly, Jeffrey R. Marks, & Richard C. Zangar. (2013). Oxidatively modified proteins as plasma biomarkers in breast cancer. Cancer Biomarkers. 13(3). 193–200. 7 indexed citations
3.
Daly, Don S., et al.. (2011). Plasma Biomarker Profiles Differ Depending on Breast Cancer Subtype but RANTES Is Consistently Increased. Cancer Epidemiology Biomarkers & Prevention. 20(7). 1543–1551. 35 indexed citations
4.
Daly, Don S., et al.. (2010). An Internal Calibration Method for Protein-Array Studies. Statistical Applications in Genetics and Molecular Biology. 9(1). Article 14–Article 14. 11 indexed citations
5.
White, Amanda M., Don S. Daly, & Richard C. Zangar. (2010). Analysis of High-Throughput ELISA Microarray Data. Methods in molecular biology. 694. 191–211. 3 indexed citations
6.
Walsh, Stephen J., et al.. (2009). PREDICTION METRICS FOR CHEMICAL DETECTION IN LONG-WAVE INFRARED HYPERSPECTRAL IMAGERY. University of North Texas Digital Library (University of North Texas). 9(2). 3–3. 2 indexed citations
7.
Taylor, Ronald C., Mudita Singhal, Don S. Daly, et al.. (2009). An analysis pipeline for the inference of protein-protein interaction networks. International Journal of Data Mining and Bioinformatics. 3(4). 409–409. 1 indexed citations
8.
Daly, Don S., et al.. (2008). Predicting Protein Concentrations with ELISA Microarray Assays, Monotonic Splines and Monte Carlo Simulation. Statistical Applications in Genetics and Molecular Biology. 7(1). Article21–Article21. 6 indexed citations
9.
Monroe, Matthew, et al.. (2008). MASIC: A software program for fast quantitation and flexible visualization of chromatographic profiles from detected LC–MS(/MS) features. Computational Biology and Chemistry. 32(3). 215–217. 129 indexed citations
10.
Gilmore, Jason M., Deanna L. Auberry, Julia L. Sharp, et al.. (2008). A Bayesian estimator of protein–protein association probabilities. Bioinformatics. 24(13). 1554–1555. 6 indexed citations
11.
Anderson, Kevin K., Matthew Monroe, & Don S. Daly. (2006). Estimating probabilities of peptide database identifications to LC-FTICR-MS observations. Proteome Science. 4(1). 1–1. 45 indexed citations
12.
White, Amanda M., Don S. Daly, Susan M. Varnum, et al.. (2006). ProMAT: protein microarray analysis tool. Bioinformatics. 22(10). 1278–1279. 30 indexed citations
13.
Willse, Alan, et al.. (2005). Comparing Bacterial DNA Microarray Fingerprints. Statistical Applications in Genetics and Molecular Biology. 4(1). Article19–Article19. 5 indexed citations
14.
Daly, Don S., Amanda M. White, Susan M. Varnum, Kevin K. Anderson, & Richard C. Zangar. (2005). Evaluating concentration estimation errors in ELISA microarray experiments. BMC Bioinformatics. 6(1). 17–17. 30 indexed citations
15.
Anderson, Kevin K., Matthew Monroe, & Don S. Daly. (2004). Estimating Probabilities of Peptide Assignments to LC-FTICR-MS Observations.. 151–156. 5 indexed citations
16.
Wind, Robert A., Kevin R. Minard, Gary R. Holtom, et al.. (2000). An Integrated Confocal and Magnetic Resonance Microscope for Cellular Research. Journal of Magnetic Resonance. 147(2). 371–377. 31 indexed citations
17.
Jarman, Kristin H., et al.. (1999). Extracting and visualizing matrix-assisted laser desorption/ionization time-of-flight mass spectral fingerprints. Rapid Communications in Mass Spectrometry. 13(15). 1586–1594. 61 indexed citations
18.
Johnson, Robert L., et al.. (1997). A Novel Approach to Fish Behavior Evaluation Using Split-beam Hydroacoustic Techniques. 609–618. 1 indexed citations
19.
Murga, Ricardo, Philip S. Stewart, & Don S. Daly. (1995). Quantitative analysis of biofilm thickness variability. Biotechnology and Bioengineering. 45(6). 503–510. 123 indexed citations
20.
Beedlow, Peter A., et al.. (1986). A new device for measuring fluctuations in plant stem diameter: Implications for monitoring plant responses. Environmental Monitoring and Assessment. 6(3). 277–282. 9 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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