Daniel T. Ladror

483 citations
14 papers · 401 · h-index 10

Impact in

  • Neurology top 10%
    • Parkinson's Disease Mechanisms and Treatments
    • Neurological disorders and treatments
  • Spectroscopy top 10%
    • Advanced NMR Techniques and Applications
    • Mass Spectrometry Techniques and Applications
    • Advanced Proteomics Techniques and Applications

Papers in

    • Advanced Proteomics Techniques and Applications 3
    • Mass Spectrometry Techniques and Applications 3
    • Advanced NMR Techniques and Applications 2

Daniel T. Ladror

14 papers receiving 396 citations

Peers

Daniel T. Ladror
Comparison fields: 5 of 73
  • Neurology 141
  • Spectroscopy 102
  • Physiology 133
  • Cellular and Molecular Neuroscience 56
  • Molecular Biology 167
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Fabrizio Chiti Italy
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Citations per field
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Citations per year

Countries citing papers authored by Daniel T. Ladror

Since Specialization
Citations

This map shows the geographic impact of Daniel T. Ladror'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 T. Ladror with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel T. Ladror more than expected).

Fields of papers citing papers by Daniel T. Ladror

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Daniel T. Ladror, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel T. Ladror Line = papers co-authored together Daniel T. Ladror links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2011132
2 200768
3 200738
4 201338
5 202226
6 201421
7 201320
8 201116
9 200815
10 201711
11 20076
12 20235
13 20234
14 20221

About Daniel T. Ladror

Daniel T. Ladror is a scholar working on Molecular Biology, Spectroscopy, Oncology, Immunology and Neurology, having authored 14 papers that have together received 401 indexed citations. Recurring topics across this work include Advanced Proteomics Techniques and Applications (3 papers), Mass Spectrometry Techniques and Applications (3 papers), Advanced Neuroimaging Techniques and Applications (2 papers), Advanced NMR Techniques and Applications (2 papers), Parkinson's Disease Mechanisms and Treatments (2 papers), Biosimilars and Bioanalytical Methods (2 papers), Cellular transport and secretion (2 papers) and Peptidase Inhibition and Analysis (2 papers). The work is most often cited by research in Neurology (141 citations), Spectroscopy (102 citations), Physiology (133 citations), Cellular and Molecular Neuroscience (56 citations) and Molecular Biology (167 citations). Daniel T. Ladror has collaborated with scholars based in United States. Frequent co-authors include Chad M. Rienstra, Kathryn D. Kloepper, Wendy S. Woods, Julia M. George, Kevin Hartman, Lloyd M. Smith, Andrew Lipton, Gemma Comellas, Luisel Lemkau and Andrew J. Nieuwkoop. Their work appears in journals such as Journal of Exposure Science & Environmental Epidemiology, Biomarkers, Journal of the American Society for Mass Spectrometry, Analytical Chemistry and Journal of Biological Chemistry.

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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