Daniel Baird
Impact in
- Cell Biology top 5%
- 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
- Ubiquitin and proteasome pathways 1
-
- Cellular transport and secretion 3
- Endoplasmic Reticulum Stress and Disease 1
- Microtubule and mitosis dynamics 1
- Co-authors
- Yuxin Mao (1 shared paper)Christopher J. Stefan (1 shared paper)Scott D. Emr (1 shared paper)Andrew G. Manford (1 shared paper)Richard A. Cerione (3 shared papers)Qiyu Feng (3 shared papers)Qiong Lin (1 shared paper)Wannian Yang (1 shared paper)
- Journals
- Proceedings of the National Academy of Sciences (1 paper)Cell (1 paper)ACS Medicinal Chemistry Letters (1 paper)Journal of Biological Chemistry (1 paper)Methods in enzymology on CD-ROM/Methods in enzymology (1 paper)
- Partner nations
- United States
In The Last Decade
Daniel Baird
6 papers receiving 573 citations
Peers
Comparison fields: 5 of 63
- Cell Biology 361
- Physiology 46
- Molecular Biology 436
- Biochemistry 35
- Immunology and Allergy 23
Countries citing papers authored by Daniel Baird
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
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.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 401 | |
| 2 | 2004 | 77 | |
| 3 | 2006 | 50 | |
| 4 | 2004 | 28 | |
| 5 | 2019 | 12 | |
| 6 | 2006 | 11 |
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 579 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), Signaling Pathways in Disease (1 paper), Ubiquitin and proteasome pathways (1 paper), Endoplasmic Reticulum Stress and Disease (1 paper), Microtubule and mitosis dynamics (1 paper) and Calcium signaling and nucleotide metabolism (1 paper). The work is most often cited by research in Cell Biology (361 citations), Physiology (46 citations), Molecular Biology (436 citations), Biochemistry (35 citations) and Immunology and Allergy (23 citations). Daniel Baird has collaborated with scholars based in United States. Frequent co-authors include Yuxin Mao, Christopher J. Stefan, Scott D. Emr, Andrew G. Manford, Richard A. Cerione, Qiyu Feng, Qiong Lin, Wannian Yang, Jonas Korlach and Kyle R. Gee. Their work appears in journals such as Proceedings of the National Academy of Sciences, Cell, ACS Medicinal Chemistry Letters, Journal of Biological Chemistry and Methods in enzymology on CD-ROM/Methods in enzymology.
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.