John G. Cogan

437 total citations
8 papers, 386 citations indexed

About

John G. Cogan is a scholar working on Molecular Biology, Cancer Research and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, John G. Cogan has authored 8 papers receiving a total of 386 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Cancer Research and 2 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in John G. Cogan's work include RNA Research and Splicing (4 papers), TGF-β signaling in diseases (2 papers) and Cancer-related gene regulation (2 papers). John G. Cogan is often cited by papers focused on RNA Research and Splicing (4 papers), TGF-β signaling in diseases (2 papers) and Cancer-related gene regulation (2 papers). John G. Cogan collaborates with scholars based in United States. John G. Cogan's co-authors include Arthur R. Strauch, Michael J. Getz, Steven W. Rissing, Robert J. Kelm, Siquan Sun, John A. Polikandriotis, Paula K. Elder, Sukanya Subramanian, Lucy J. Schmidt and Aiwen Zhang and has published in prestigious journals such as Journal of Biological Chemistry, Molecular and Cellular Biology and Molecular Biology of the Cell.

In The Last Decade

John G. Cogan

8 papers receiving 376 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
John G. Cogan United States	6	260	49	45	40	36	8	386
J. Mareš Czechia	10	178 0.7×	26 0.5×	1 0.0×	9 0.2×	49 1.4×	21	354
Melissa Gonzalez United States	5	139 0.5×	31 0.6×	4 0.1×	3 0.1×	12 0.3×	9	279
Chein Tai Taiwan	9	219 0.8×	2 0.0×	6 0.1×	10 0.3×	21 0.6×	11	314
R Kramer United States	4	226 0.9×		41 0.9×	104 2.6×	42 1.2×	6	376
David T. Stolow United States	9	271 1.0×	8 0.2×	14 0.3×	1 0.0×	39 1.1×	10	381
X. Mao China	5	315 1.2×		18 0.4×	28 0.7×	33 0.9×	11	414
Xiaochun Chi China	11	275 1.1×		17 0.4×	75 1.9×	35 1.0×	14	381
Eric Martens United States	3	452 1.7×		12 0.3×	43 1.1×	44 1.2×	3	511
Dong Hong Cai United States	8	231 0.9×		34 0.8×	16 0.4×	54 1.5×	13	352

Countries citing papers authored by John G. Cogan

Since Specialization

Citations

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

Fields of papers citing papers by John G. Cogan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John G. Cogan. 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 John G. Cogan. The network helps show where John G. Cogan may publish in the future.

Co-authorship network of co-authors of John G. Cogan

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

All Works

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8 of 8 papers shown

Rissing, Steven W. & John G. Cogan. (2009). Can an Inquiry Approach Improve College Student Learning in a Teaching Laboratory?. CBE—Life Sciences Education. 8(1). 55–61. 71 indexed citations

Zhang, Aiwen, Xiaoying Liu, John G. Cogan, et al.. (2005). YB-1 Coordinates Vascular Smooth Muscle α-Actin Gene Activation by Transforming Growth Factor β1 and Thrombin during Differentiation of Human Pulmonary Myofibroblasts. Molecular Biology of the Cell. 16(10). 4931–4940. 48 indexed citations

Cogan, John G., Sukanya Subramanian, John A. Polikandriotis, Robert J. Kelm, & Arthur R. Strauch. (2002). Vascular Smooth Muscle α-Actin Gene Transcription during Myofibroblast Differentiation Requires Sp1/3 Protein Binding Proximal to the MCAT Enhancer. Journal of Biological Chemistry. 277(39). 36433–36442. 61 indexed citations

Kelm, Robert J., John G. Cogan, Paula K. Elder, Arthur R. Strauch, & Michael J. Getz. (1999). Molecular Interactions between Single-stranded DNA-binding Proteins Associated with an Essential MCAT Element in the Mouse Smooth Muscle α-Actin Promoter. Journal of Biological Chemistry. 274(20). 14238–14245. 78 indexed citations

Strauch, Arthur R., John G. Cogan, Robert J. Kelm, Sukanya Subramanian, & Michael J. Getz. (1999). Transgenic and therapeutic targeting of smooth muscle cells and the challenges presented by phenotypic diversity. 3(2). 279–306. 1 indexed citations

Strauch, Arthur R., John G. Cogan, Sukanya Subramanian, et al.. (1997). Transcriptional activity of the vascular α-actin gene as an indicator of cellular injury following cardiac transplant. Transplant Immunology. 5(4). 261–266. 4 indexed citations

Cogan, John G., et al.. (1995). Plasticity of Vascular Smooth Muscle α-Actin Gene Transcription. Journal of Biological Chemistry. 270(19). 11310–11321. 57 indexed citations

Sun, Siquan, et al.. (1995). Negative Regulation of the Vascular Smooth Muscle α-Actin Gene in Fibroblasts and Myoblasts: Disruption of Enhancer Function by Sequence-Specific Single-Stranded-DNA-Binding Proteins. Molecular and Cellular Biology. 15(5). 2429–2436. 66 indexed citations

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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