Blake J. Cochran

1.8k total citations
51 papers, 972 citations indexed

About

Blake J. Cochran is a scholar working on Surgery, Endocrinology, Diabetes and Metabolism and Molecular Biology. According to data from OpenAlex, Blake J. Cochran has authored 51 papers receiving a total of 972 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Surgery, 15 papers in Endocrinology, Diabetes and Metabolism and 13 papers in Molecular Biology. Recurrent topics in Blake J. Cochran's work include Pancreatic function and diabetes (12 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (11 papers) and Cholesterol and Lipid Metabolism (9 papers). Blake J. Cochran is often cited by papers focused on Pancreatic function and diabetes (12 papers), Diabetes, Cardiovascular Risks, and Lipoproteins (11 papers) and Cholesterol and Lipid Metabolism (9 papers). Blake J. Cochran collaborates with scholars based in Australia, United States and United Kingdom. Blake J. Cochran's co-authors include Kerry‐Anne Rye, Bikash Manandhar, Kwok Leung Ong, Philip J. Barter, Bradley Tucker, Sanjay Patel, Shane R. Thomas, Kaivan Vaidya, Fatiha Tabet and Sergei Lobov and has published in prestigious journals such as Journal of Biological Chemistry, SHILAP Revista de lepidopterología and Journal of the American College of Cardiology.

In The Last Decade

Blake J. Cochran

49 papers receiving 955 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Blake J. Cochran Australia 20 329 319 261 188 158 51 972
Danielle Duffy United States 17 326 1.0× 587 1.8× 465 1.8× 250 1.3× 213 1.3× 42 1.2k
Hideto Ishii Japan 14 350 1.1× 274 0.9× 145 0.6× 158 0.8× 86 0.5× 23 893
G. Tibolla Italy 13 256 0.8× 540 1.7× 218 0.8× 110 0.6× 115 0.7× 21 1.1k
Nianping Hu Canada 11 514 1.6× 191 0.6× 317 1.2× 172 0.9× 84 0.5× 21 1.2k
Patrizia Uboldi Italy 18 268 0.8× 450 1.4× 171 0.7× 111 0.6× 134 0.8× 41 1.0k
Jonathan Vigne France 17 407 1.2× 314 1.0× 289 1.1× 146 0.8× 149 0.9× 47 1.1k
Seung Ho Hong South Korea 17 236 0.7× 242 0.8× 204 0.8× 102 0.5× 204 1.3× 40 860
P Lohse Germany 27 586 1.8× 450 1.4× 295 1.1× 147 0.8× 176 1.1× 57 1.4k
Muhidien Soufi Germany 15 215 0.7× 246 0.8× 236 0.9× 116 0.6× 201 1.3× 29 839
Kimberly Reidy United States 14 573 1.7× 186 0.6× 172 0.7× 83 0.4× 98 0.6× 28 1.5k

Countries citing papers authored by Blake J. Cochran

Since Specialization
Citations

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

Fields of papers citing papers by Blake J. Cochran

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Blake J. Cochran. 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 Blake J. Cochran. The network helps show where Blake J. Cochran may publish in the future.

Co-authorship network of co-authors of Blake J. Cochran

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

All Works

20 of 20 papers shown
1.
2.
Cochran, Blake J., et al.. (2023). ApoA-I and Diabetes. Arteriosclerosis Thrombosis and Vascular Biology. 43(8). 1362–1368. 13 indexed citations
3.
Cochran, Blake J., et al.. (2023). Impact of Reperfusion on Temporal Immune Cell Dynamics After Myocardial Infarction. Journal of the American Heart Association. 12(4). e027600–e027600. 22 indexed citations
4.
Tucker, Bradley, et al.. (2023). Impact of Impaired Cholesterol Homeostasis on Neutrophils in Atherosclerosis. Arteriosclerosis Thrombosis and Vascular Biology. 43(5). 618–627. 21 indexed citations
5.
Manandhar, Bikash, Elvis Pandžić, Nandan Deshpande, et al.. (2023). ApoA-I Protects Pancreatic β-Cells From Cholesterol-Induced Mitochondrial Damage and Restores Their Ability to Secrete Insulin. Arteriosclerosis Thrombosis and Vascular Biology. 44(2). e20–e38. 3 indexed citations
6.
Beretta, Martina, Ellen M. Olzomer, Stephanie J. Alexopoulos, et al.. (2023). Targeting negative energy balance with calorie restriction and mitochondrial uncoupling in db/db mice. Molecular Metabolism. 69. 101684–101684. 11 indexed citations
7.
Jonnagaddala, Jitendra, et al.. (2022). Statin Prescription Patterns and Associations with Subclinical Inflammation. Medicina. 58(8). 1096–1096. 2 indexed citations
8.
Richardson, Alexander, et al.. (2022). Use of High-Refractive Index Hydrogels and Tissue Clearing for Large Biological Sample Imaging. Gels. 8(1). 32–32. 3 indexed citations
9.
Ong, Kwok Leung, Blake J. Cochran, Bikash Manandhar, Shane R. Thomas, & Kerry‐Anne Rye. (2022). HDL maturation and remodelling. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids. 1867(4). 159119–159119. 19 indexed citations
10.
Aflatounian, Ali, Valentina Rodriguez Paris, Dulama Richani, et al.. (2022). Declining muscle NAD+ in a hyperandrogenism PCOS mouse model: Possible role in metabolic dysregulation. Molecular Metabolism. 65. 101583–101583. 15 indexed citations
11.
Cochran, Blake J., et al.. (2022). Atorvastatin improves cisplatin sensitivity through modulation of cholesteryl ester homeostasis in breast cancer cells. Discover Oncology. 13(1). 135–135. 10 indexed citations
12.
Hoque, Monira, Syed Sultan Beevi, Kendelle J. Murphy, et al.. (2022). Annexin A6 and NPC1 regulate LDL-inducible cell migration and distribution of focal adhesions. Scientific Reports. 12(1). 596–596. 15 indexed citations
13.
Cochran, Blake J., Kwok Leung Ong, Bikash Manandhar, & Kerry‐Anne Rye. (2021). APOA1: a Protein with Multiple Therapeutic Functions. Current Atherosclerosis Reports. 23(3). 11–11. 117 indexed citations
14.
Cochran, Blake J., Kwok Leung Ong, Bikash Manandhar, & Kerry‐Anne Rye. (2021). High Density Lipoproteins and Diabetes. Cells. 10(4). 850–850. 33 indexed citations
15.
Wang, Hui‐Xin, Michael G. Leeming, Blake J. Cochran, et al.. (2020). Nontargeted Identification of Plasma Proteins O-, N-, and S-Transmethylated by O-Methyl Organophosphates. Analytical Chemistry. 92(23). 15420–15428. 8 indexed citations
16.
Vaidya, Kaivan, Bradley Tucker, R. Kurup, et al.. (2020). Colchicine Inhibits Neutrophil Extracellular Trap Formation in Patients With Acute Coronary Syndrome After Percutaneous Coronary Intervention. Journal of the American Heart Association. 10(1). e018993–e018993. 96 indexed citations
17.
18.
Tabet, Fatiha, Blake J. Cochran, Luisa Torres, et al.. (2019). Apolipoprotein A-I enhances insulin-dependent and insulin-independent glucose uptake by skeletal muscle. Scientific Reports. 9(1). 1350–1350. 51 indexed citations
19.
Woollard, Kevin, Robyn L. McClelland, Matthew Allison, et al.. (2019). The association of plasma lipids with white blood cell counts: Results from the Multi-Ethnic Study of Atherosclerosis. Journal of clinical lipidology. 13(5). 812–820. 21 indexed citations
20.
Cochran, Blake J., et al.. (2009). The CD-loop of PAI-2 (SERPINB2) is redundant in the targeting, inhibition and clearance of cell surface uPA activity. BMC Biotechnology. 9(1). 43–43. 18 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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