C. E. Baird

1.8k total citations · 1 hit paper
8 papers, 1.4k citations indexed

About

C. E. Baird is a scholar working on Molecular Biology, Cell Biology and Oncology. According to data from OpenAlex, C. E. Baird has authored 8 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Molecular Biology, 3 papers in Cell Biology and 2 papers in Oncology. Recurrent topics in C. E. Baird's work include Adenosine and Purinergic Signaling (2 papers), Enzyme function and inhibition (2 papers) and Peptidase Inhibition and Analysis (2 papers). C. E. Baird is often cited by papers focused on Adenosine and Purinergic Signaling (2 papers), Enzyme function and inhibition (2 papers) and Peptidase Inhibition and Analysis (2 papers). C. E. Baird collaborates with scholars based in United States. C. E. Baird's co-authors include R.W. Butcher, Earl W. Sutherland, J. G. Hardman, Jack N. Wells, Yuejin Wu, G. Schultz, Karin Schultz, Wendell E. Nicholson, Grant W. Liddle and Kaoru Abe and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Endocrinology.

In The Last Decade

C. E. Baird

8 papers receiving 1.3k citations

Hit Papers

Effects of Lipolytic and Antilipolytic Substances on Aden... 1968 2026 1987 2006 1968 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
C. E. Baird United States 8 788 390 301 181 171 8 1.4k
Bruce McL. Breckenridge United States 21 1.1k 1.4× 300 0.8× 584 1.9× 109 0.6× 113 0.7× 29 1.8k
Alfred Goldstone United States 28 1.1k 1.4× 398 1.0× 238 0.8× 90 0.5× 211 1.2× 52 1.9k
J. G. Hardman United States 17 969 1.2× 377 1.0× 239 0.8× 93 0.5× 99 0.6× 24 1.4k
Harper Jf United States 5 740 0.9× 278 0.7× 383 1.3× 82 0.5× 82 0.5× 7 1.5k
F. H. Schneider United States 15 616 0.8× 185 0.5× 368 1.2× 180 1.0× 48 0.3× 26 1.2k
Stefaan Keppens Belgium 24 916 1.2× 287 0.7× 202 0.7× 480 2.7× 64 0.4× 47 1.9k
Naomi Friedmann United States 21 713 0.9× 380 1.0× 185 0.6× 306 1.7× 59 0.3× 30 1.4k
P P Godfrey United Kingdom 21 1000 1.3× 235 0.6× 410 1.4× 322 1.8× 64 0.4× 26 1.9k
Joseph Eichberg United States 28 973 1.2× 440 1.1× 452 1.5× 215 1.2× 58 0.3× 76 1.9k
André De Léan Canada 27 1.5k 1.9× 360 0.9× 736 2.4× 112 0.6× 171 1.0× 64 2.5k

Countries citing papers authored by C. E. Baird

Since Specialization
Citations

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

Fields of papers citing papers by C. E. Baird

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of C. E. Baird

This figure shows the co-authorship network connecting the top 25 collaborators of C. E. Baird. A scholar is included among the top collaborators of C. E. Baird 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 C. E. Baird. C. E. Baird is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

8 of 8 papers shown
1.
Wells, Jack N., C. E. Baird, Yuejin Wu, & J. G. Hardman. (1975). Cyclic nucleotide phosphodiesterase activities of pig coronary arteries. Biochimica et Biophysica Acta (BBA) - Enzymology. 384(2). 430–442. 123 indexed citations
2.
Wells, Jack N., Yuejin Wu, C. E. Baird, & J. G. Hardman. (1975). Phosphodiesterases from Porcine Coronary Arteries: Inhibition of Separated Forms by Xanthines, Papaverine, and Cyclic Nucleotides. Molecular Pharmacology. 11(6). 775–783. 80 indexed citations
3.
Schultz, G., J. G. Hardman, Karin Schultz, C. E. Baird, & Earl W. Sutherland. (1973). The Importance of Calcium Ions for the Regulation of Guanosine 3′:5′-Cyclic Monophosphate Levels. Proceedings of the National Academy of Sciences. 70(12). 3889–3893. 199 indexed citations
4.
Beavo, Joseph A., Nancy L. Rogers, Oscar B. Crofford, et al.. (1971). EFFECTS OF PHOSPHODIESTERASE INHIBITORS ON CYCLIC AMP LEVELS AND ON LIPOLYSIS*. Annals of the New York Academy of Sciences. 185(1). 129–136. 47 indexed citations
5.
Abe, Kaoru, R.W. Butcher, Wendell E. Nicholson, et al.. (1969). Adenosine 3′,5′-Monophosphate (Cyclic AMP) as the Mediator of the Actions of Melanocyte Stimulating Hormone (MSH) and Norepinephrine on the Frog Skin1. Endocrinology. 84(2). 362–368. 103 indexed citations
6.
Abe, Kaoru, G. Alan Robison, Grant W. Liddle, et al.. (1969). Role of Cyclic AMP in Mediating the Effects of MSH, Norepinephrine, and Melatonin on Frog Skin Color. Endocrinology. 85(4). 674–682. 131 indexed citations
7.
Butcher, R.W. & C. E. Baird. (1968). Effects of Prostaglandins on Adenosine 3′,5′-Monophosphate Levels in Fat and Other Tissues. Journal of Biological Chemistry. 243(8). 1713–1717. 300 indexed citations
8.
Butcher, R.W., C. E. Baird, & Earl W. Sutherland. (1968). Effects of Lipolytic and Antilipolytic Substances on Adenosine 3′,5′-Monophosphate Levels in Isolated Fat Cells. Journal of Biological Chemistry. 243(8). 1705–1712. 466 indexed citations breakdown →

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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