Daniel Baird

1.1k citations
6 papers · 560 · h-index 5

Impact in

    • Cellular transport and secretion
    • Endoplasmic Reticulum Stress and Disease
    • Microtubule and mitosis dynamics
  • Physiology top 10%
    • Calcium signaling and nucleotide metabolism

Papers in

    • Protein Kinase Regulation and GTPase Signaling 4
    • Signaling Pathways in Disease 1
    • Cellular transport and secretion 3
    • Endoplasmic Reticulum Stress and Disease 1

Daniel Baird

6 papers receiving 555 citations

Peers

Daniel Baird
Comparison fields: 5 of 63
  • Cell Biology 351
  • Physiology 46
  • Molecular Biology 430
  • Biochemistry 33
  • Aging 7
Replace Claudia Cericola with:
Claudia Cericola Italy
Léa P. Wilhelm United Kingdom
Oforiwa A. Gorleku United Kingdom
Brady D. Goulden United States
Kaori Masai Japan
Darcy P. Pomerleau United States
Piroska Dévay Hungary
Zhenyuan Tang United States
Jacob M. Serfass United States
Thomas Strahl United States
Daniel Baird relative to Claudia Cericola Italy Claudia Cericola's profile →
Citations per field
00.5×4.3×
Claudia Cericola · 1×
Citations per year

Countries citing papers authored by Daniel Baird

Since Specialization
Citations

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

Fields of papers citing papers by Daniel Baird

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 24 scholars most cited alongside Daniel Baird, 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 Baird Line = papers co-authored together Daniel Baird links everyone, so they are left out of the graph.

All Works

6 of 6 papers shown
#Work
1 2011390
2 200476
3 200650
4 200428
5 201912
6 20064

About Daniel Baird

Daniel Baird is a scholar working on Molecular Biology, Cell Biology, Genetics, Geriatrics and Gerontology and Oncology, having authored 6 papers that have together received 560 indexed citations. Recurring topics across this work include Protein Kinase Regulation and GTPase Signaling (4 papers), Cellular transport and secretion (3 papers), Genetics and Neurodevelopmental Disorders (2 papers), Sirtuins and Resveratrol in Medicine (1 paper), Signaling Pathways in Disease (1 paper), PARP inhibition in cancer therapy (1 paper), Calcium signaling and nucleotide metabolism (1 paper) and Endoplasmic Reticulum Stress and Disease (1 paper). The work is most often cited by research in Cell Biology (351 citations), Physiology (46 citations), Molecular Biology (430 citations), Biochemistry (33 citations) and Aging (7 citations). Daniel Baird has collaborated with scholars based in United States. Frequent co-authors include Christopher J. Stefan, Scott D. Emr, Andrew G. Manford, Yuxin Mao, Qiyu Feng, Richard A. Cerione, Wannian Yang, Qiong Lin, Jonas Korlach and Kyle R. Gee. Their work appears in journals such as ACS Medicinal Chemistry Letters, Cell, The EMBO Journal, Proceedings of the National Academy of Sciences 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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