Ming Gang Lin

1.9k total citations
17 papers, 1.4k citations indexed

About

Ming Gang Lin is a scholar working on Molecular Biology, Cancer Research and Genetics. According to data from OpenAlex, Ming Gang Lin has authored 17 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 10 papers in Cancer Research and 8 papers in Genetics. Recurrent topics in Ming Gang Lin's work include Breast Cancer Treatment Studies (5 papers), Cancer Genomics and Diagnostics (4 papers) and Gene expression and cancer classification (4 papers). Ming Gang Lin is often cited by papers focused on Breast Cancer Treatment Studies (5 papers), Cancer Genomics and Diagnostics (4 papers) and Gene expression and cancer classification (4 papers). Ming Gang Lin collaborates with scholars based in United States, China and Norway. Ming Gang Lin's co-authors include Cheng Li, William R. Sellers, Wing Hung Wong, Lee‐Jen Wei, Matthew Meyerson, Peggy L. Porter, Xiaopu Yuan, Levi A. Garraway, Rameen Beroukhim and Xiaojun Zhao and has published in prestigious journals such as Bioinformatics, JNCI Journal of the National Cancer Institute and Cancer.

In The Last Decade

Ming Gang Lin

17 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ming Gang Lin United States 16 777 561 516 410 168 17 1.4k
Farahnaz Forozan United States 7 662 0.9× 320 0.6× 275 0.5× 340 0.8× 114 0.7× 8 1.0k
Barbara Wappenschmidt Germany 27 1.1k 1.4× 732 1.3× 536 1.0× 364 0.9× 71 0.4× 62 1.7k
Chiyomi Egawa Japan 20 740 1.0× 471 0.8× 302 0.6× 628 1.5× 157 0.9× 69 1.4k
Zdeněk Kleibl Czechia 23 745 1.0× 557 1.0× 326 0.6× 473 1.2× 115 0.7× 77 1.4k
Eija Mahlamäki Finland 19 781 1.0× 309 0.6× 417 0.8× 641 1.6× 155 0.9× 35 1.7k
Steven G. Brodie United States 20 1.4k 1.8× 660 1.2× 276 0.5× 558 1.4× 88 0.5× 32 1.9k
L.W. Chu United States 10 357 0.5× 368 0.7× 349 0.7× 252 0.6× 147 0.9× 14 944
Einav Nili Gal‐Yam Israel 16 1.2k 1.6× 282 0.5× 344 0.7× 317 0.8× 155 0.9× 53 1.6k
Ina Rhee United States 12 1.8k 2.3× 310 0.6× 273 0.5× 520 1.3× 218 1.3× 14 2.3k
Sophie Gad France 20 1.0k 1.3× 502 0.9× 619 1.2× 362 0.9× 394 2.3× 38 1.7k

Countries citing papers authored by Ming Gang Lin

Since Specialization
Citations

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

Fields of papers citing papers by Ming Gang Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ming Gang Lin

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

All Works

17 of 17 papers shown
1.
Sakoda, Lori C., Jennifer A. Doherty, Roberta M. Ray, et al.. (2010). Selected estrogen receptor 1 and androgen receptor gene polymorphisms in relation to risk of breast cancer and fibrocystic breast conditions among Chinese women. Cancer Epidemiology. 35(1). 48–55. 24 indexed citations
2.
Li, Christopher I., Kathleen E. Malone, Peggy L. Porter, et al.. (2008). Relationship between Menopausal Hormone Therapy and Risk of Ductal, Lobular, and Ductal-Lobular Breast Carcinomas. Cancer Epidemiology Biomarkers & Prevention. 17(1). 43–50. 55 indexed citations
3.
Sakoda, Lori C., Jennifer A. Doherty, Roberta M. Ray, et al.. (2008). Polymorphisms in Steroid Hormone Biosynthesis Genes and Risk of Breast Cancer and Fibrocystic Breast Conditions in Chinese Women. Cancer Epidemiology Biomarkers & Prevention. 17(5). 1066–1073. 25 indexed citations
4.
Chen, Chu, Lori C. Sakoda, Jennifer A. Doherty, et al.. (2008). Genetic Variation inCYP19A1and Risk of Breast Cancer and Fibrocystic Breast Conditions among Women in Shanghai, China. Cancer Epidemiology Biomarkers & Prevention. 17(12). 3457–3466. 16 indexed citations
5.
Sakoda, Lori C., Kan Xue, Jennifer A. Doherty, et al.. (2007). Glutathione S-transferase M1 and P1 polymorphisms and risk of breast cancer and fibrocystic breast conditions in Chinese women. Breast Cancer Research and Treatment. 109(1). 143–155. 29 indexed citations
6.
Beroukhim, Rameen, Ming Gang Lin, Yuhyun Park, et al.. (2006). Inferring Loss-of-Heterozygosity from Unpaired Tumors Using High-Density Oligonucleotide SNP Arrays. PLoS Computational Biology. 2(5). e41–e41. 119 indexed citations
7.
Porter, Peggy L., William E. Barlow, I‐Tien Yeh, et al.. (2006). p27 Kip1 and Cyclin E Expression and Breast Cancer Survival After Treatment With Adjuvant Chemotherapy. JNCI Journal of the National Cancer Institute. 98(23). 1723–1731. 54 indexed citations
8.
Zhao, Xiaojun, Barbara A. Weir, Thomas LaFramboise, et al.. (2005). Homozygous Deletions and Chromosome Amplifications in Human Lung Carcinomas Revealed by Single Nucleotide Polymorphism Array Analysis. Cancer Research. 65(13). 5561–5570. 242 indexed citations
9.
Wang, Vivian, Cheng Li, Ming Gang Lin, et al.. (2005). Ovarian cancer is a heterogeneous disease. Cancer Genetics and Cytogenetics. 161(2). 170–173. 37 indexed citations
10.
Gao, Dao Li, David B. Thomas, Roberta M. Ray, et al.. (2005). [Randomized trial of breast self-examination in 266,064 women in Shanghai].. PubMed. 27(6). 350–4. 8 indexed citations
11.
Sparks, Rachel, Cornelia M. Ulrich, Jeannette Bigler, et al.. (2004). UDP-glucuronosyltransferase and sulfotransferase polymorphisms, sex hormone concentrations, and tumor receptor status in breast cancer patients. Breast Cancer Research. 6(5). R488–98. 64 indexed citations
12.
Tsuda, Hiroshi, Michael J. Birrer, Yoichi M. Ito, et al.. (2004). Identification of DNA copy number changes in microdissected serous ovarian cancer tissue using a cDNA microarray platform. Cancer Genetics and Cytogenetics. 155(2). 97–107. 25 indexed citations
13.
Lin, Ming Gang, et al.. (2004). dChipSNP: significance curve and clustering of SNP-array-based loss-of-heterozygosity data. Bioinformatics. 20(8). 1233–1240. 292 indexed citations
14.
Porter, Peggy L., Mary Jo Lund, Ming Gang Lin, et al.. (2004). Racial differences in the expression of cell cycle–regulatory proteins in breast carcinoma. Cancer. 100(12). 2533–2542. 111 indexed citations
15.
Suter, Nicola M., Roberta M. Ray, Ming Gang Lin, et al.. (2004). BRCA1 and BRCA2 Mutations in Women from Shanghai China. Cancer Epidemiology Biomarkers & Prevention. 13(2). 181–189. 59 indexed citations
16.
Wang, Zhigang C., Ming Gang Lin, L. J. Wei, et al.. (2004). Loss of Heterozygosity and Its Correlation with Expression Profiles in Subclasses of Invasive Breast Cancers. Cancer Research. 64(1). 64–71. 150 indexed citations
17.
Lin, Ming Gang, Mirna Lechpammer, Cheng Li, et al.. (2003). Genome-wide loss of heterozygosity analysis from laser capture microdissected prostate cancer using single nucleotide polymorphic allele (SNP) arrays and a novel bioinformatics platform dChipSNP.. PubMed. 63(16). 4781–5. 95 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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