Dan Baird
Impact in
- Cell Biology top 5%
- Cellular transport and secretion
- Cellular Mechanics and Interactions
- Microtubule and mitosis dynamics
- Endoplasmic Reticulum Stress and Disease
- Immunology and Allergy top 10%
- Cell Adhesion Molecules Research
Papers in
-
- Protein Kinase Regulation and GTPase Signaling 2
- Viral Infectious Diseases and Gene Expression in Insects 1
- Glycosylation and Glycoproteins Research 1
- Ubiquitin and proteasome pathways 1
- Pineapple and bromelain studies 1
- Gene Regulatory Network Analysis 1
- Oncology 1
- Co-authors
- Qiyu Feng (5 shared papers)Richard A. Cerione (4 shared papers)Christopher J. Stefan (1 shared paper)Sabine Weys (1 shared paper)Anjon Audhya (1 shared paper)Scott D. Emr (1 shared paper)Peng Xu (1 shared paper)Jianbin Wang (1 shared paper)
- Journals
- Current Biology (1 paper)The Journal of Cell Biology (1 paper)IET Systems Biology (1 paper)Journal of Biological Chemistry (1 paper)Nature Cell Biology (1 paper)
- Partner nations
- United StatesFrance
In The Last Decade
Dan Baird
6 papers receiving 468 citations
Peers
Comparison fields: 5 of 84
- Cell Biology 214
- Immunology and Allergy 39
- Molecular Biology 306
- Physiology 19
- Cellular and Molecular Neuroscience 47
Countries citing papers authored by Dan Baird
This map shows the geographic impact of Dan 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 Dan Baird with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Baird more than expected).
Fields of papers citing papers by Dan Baird
This network shows the impact of papers produced by Dan 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 Dan Baird. The network helps show where Dan Baird may publish in the future.
Co-authors
The 17 scholars most cited alongside Dan 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 | 2005 | 145 | |
| 2 | 2008 | 125 | |
| 3 | 2006 | 101 | |
| 4 | 2007 | 59 | |
| 5 | 2010 | 40 | |
| 6 | signal transduction Novel regulatory mechanisms for the Dbl family guanine nucleotide exchange factor Cool-2/alpha-Pix | 2004 | 6 |
| 7 | 2025 | 0 |
About Dan Baird
Dan Baird is a scholar working on Molecular Biology, Oncology, Management Science and Operations Research, Cell Biology and Immunology and Allergy, having authored 7 papers that have together received 476 indexed citations. Recurring topics across this work include Protein Kinase Regulation and GTPase Signaling (2 papers), Cell Adhesion Molecules Research (1 paper), Viral Infectious Diseases and Gene Expression in Insects (1 paper), Glycosylation and Glycoproteins Research (1 paper), Ubiquitin and proteasome pathways (1 paper), Pineapple and bromelain studies (1 paper), Gene Regulatory Network Analysis (1 paper) and Endoplasmic Reticulum Stress and Disease (1 paper). The work is most often cited by research in Cell Biology (214 citations), Immunology and Allergy (39 citations), Molecular Biology (306 citations), Physiology (19 citations) and Cellular and Molecular Neuroscience (47 citations). Dan Baird has collaborated with scholars based in United States and France. Frequent co-authors include Qiyu Feng, Richard A. Cerione, Christopher J. Stefan, Sabine Weys, Anjon Audhya, Scott D. Emr, Peng Xu, Jianbin Wang, Jun‐Lin Guan and Thi Ly. Their work appears in journals such as Current Biology, The Journal of Cell Biology, IET Systems Biology, Journal of Biological Chemistry and Nature Cell Biology.
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.