Mike Z. Lin

601 total citations
13 papers, 475 citations indexed

About

Mike Z. Lin is a scholar working on Molecular Biology, Endocrinology, Diabetes and Metabolism and Oncology. According to data from OpenAlex, Mike Z. Lin has authored 13 papers receiving a total of 475 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 6 papers in Endocrinology, Diabetes and Metabolism and 5 papers in Oncology. Recurrent topics in Mike Z. Lin's work include Growth Hormone and Insulin-like Growth Factors (6 papers), Cancer-related Molecular Pathways (4 papers) and Cancer, Hypoxia, and Metabolism (3 papers). Mike Z. Lin is often cited by papers focused on Growth Hormone and Insulin-like Growth Factors (6 papers), Cancer-related Molecular Pathways (4 papers) and Cancer, Hypoxia, and Metabolism (3 papers). Mike Z. Lin collaborates with scholars based in Australia, China and United States. Mike Z. Lin's co-authors include Robert C. Baxter, Janet L. Martin, Carol A. Pollock, Chunling Huang, Delfine Cheng, Xinming Chen, Filip Braet, Eileen McGowan, Leo Phillips and Carolyn D. Scott and has published in prestigious journals such as Journal of Biological Chemistry, Oncogene and Scientific Reports.

In The Last Decade

Mike Z. Lin

13 papers receiving 472 citations

Peers

Countries citing papers authored by Mike Z. Lin

Since Specialization

Citations

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

Fields of papers citing papers by Mike Z. Lin

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mike Z. Lin. 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 Mike Z. Lin. The network helps show where Mike Z. Lin may publish in the future.

Co-authorship network of co-authors of Mike Z. Lin

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

All Works

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13 of 13 papers shown

#	Work	Indexed citations
1	Infiltrative lymphocytic hypophysitis successfully treated with rituximab and mycophenolate mofetil 2020 ·Endocrinology Diabetes and Metabolism Case Reports ·Mike Z. Lin, Venessa Tsang, Janice Brewer, Roderick Clifton‐Bligh, Matti L. Gild	2
2	IGFBP-3 interacts with NONO and SFPQ in PARP-dependent DNA damage repair in triple-negative breast cancer 2019 ·Cellular and Molecular Life Sciences ·(unknown), Mike Z. Lin, Leo Phillips, Janet L. Martin, Robert C. Baxter	61
3	Inhibition of basal-like breast cancer growth by FTY720 in combination with epidermal growth factor receptor kinase blockade 2017 ·Breast Cancer Research ·Janet L. Martin, Sohel M. Julovi, Mike Z. Lin, (unknown), Frances Boyle, Robert C. Baxter	24
4	KCa3.1 mediates dysfunction of tubular autophagy in diabetic kidneys via PI3k/Akt/mTOR signaling pathways 2016 ·Scientific Reports ·Chunling Huang, Mike Z. Lin, Delfine Cheng, Filip Braet, Carol A. Pollock, Xinming Chen	59
5	Involvement of the insulin-like growth factor binding proteins in the cancer cell response to DNA damage 2015 ·Journal of Cell Communication and Signaling ·(unknown), Mike Z. Lin, Janet L. Martin, Robert C. Baxter	18
6	A novel truncated form of S100P predicts disease-free survival in patients with lymph node positive breast cancer 2015 ·Cancer Letters ·Liping Chung, Leo Phillips, Mike Z. Lin, Katrina Moore, Deborah J. Marsh, Frances Boyle, Robert C. Baxter	14
7	Involvement of p53 in insulin-like growth factor binding protein-3 regulation in the breast cancer cell response to DNA damage 2015 ·Oncotarget ·(unknown), Mike Z. Lin, Janet L. Martin, Robert C. Baxter	18
8	Proximity Ligation Assay (PLA) to Detect Protein-protein Interactions in Breast Cancer 2015 ·BIO-PROTOCOL ·Mike Z. Lin, J. L. Martin, Robert C. Baxter	7
9	Thioredoxin-interacting protein mediates dysfunction of tubular autophagy in diabetic kidneys through inhibiting autophagic flux 2014 ·Laboratory Investigation ·Chunling Huang, Mike Z. Lin, Delfine Cheng, Filip Braet, Carol A. Pollock, Xinming Chen	57
10	Inhibition of Insulin-like Growth Factor–Binding Protein-3 Signaling through Sphingosine Kinase-1 Sensitizes Triple-Negative Breast Cancer Cells to EGF Receptor Blockade 2013 ·Molecular Cancer Therapeutics ·Janet L. Martin, (unknown), Mike Z. Lin, Carolyn D. Scott, Robert C. Baxter	62
11	The role of insulin-like growth factor binding protein-3 in the breast cancer cell response to DNA-damaging agents 2012 ·Oncogene ·Mike Z. Lin, (unknown), Janet L. Martin, Robert C. Baxter	61
12	iTRAQ-Based Proteomic Profiling of Breast Cancer Cell Response to Doxorubicin and TRAIL 2012 ·Journal of Proteome Research ·(unknown), Andrea C. Nunez, Mike Z. Lin, Ben Crossett, Richard I. Christopherson, Robert C. Baxter	22
13	Potentiation of Growth Factor Signaling by Insulin-like Growth Factor-binding Protein-3 in Breast Epithelial Cells Requires Sphingosine Kinase Activity 2009 ·Journal of Biological Chemistry ·Janet L. Martin, Mike Z. Lin, Eileen McGowan, Robert C. Baxter	70

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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