M Wang

1.2k total citations
14 papers, 758 citations indexed

About

M Wang is a scholar working on Molecular Biology, Oncology and Hematology. According to data from OpenAlex, M Wang has authored 14 papers receiving a total of 758 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Molecular Biology, 7 papers in Oncology and 5 papers in Hematology. Recurrent topics in M Wang's work include Multiple Myeloma Research and Treatments (5 papers), Peptidase Inhibition and Analysis (4 papers) and Protein Degradation and Inhibitors (3 papers). M Wang is often cited by papers focused on Multiple Myeloma Research and Treatments (5 papers), Peptidase Inhibition and Analysis (4 papers) and Protein Degradation and Inhibitors (3 papers). M Wang collaborates with scholars based in United States and Canada. M Wang's co-authors include Walter N. Hittelman, Kapil Dhingra, Mariza de Andrade, Joachim G. Liehr, Daniel J. Drucker, D. Weber, Robert Z. Orlowski, Jatin J. Shah, Sheeba K. Thomas and Raymond Alexanian and has published in prestigious journals such as Endocrinology, British Journal of Cancer and Molecular Endocrinology.

In The Last Decade

M Wang

14 papers receiving 731 citations

Peers

M Wang
Filippa Pettersson Canada
Dean J. Welsch United States
Jennifer M. Grad United States
Saeid Abroun Iran
Xun Cai China
Chaoxin Hu United States
Danian Nie China
Jean Sargent United States
Hanzhang Xu China
Jee‐Yeong Jeong South Korea
Filippa Pettersson Canada
M Wang
Citations per year, relative to M Wang M Wang (= 1×) peers Filippa Pettersson

Countries citing papers authored by M Wang

Since Specialization
Citations

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

Fields of papers citing papers by M Wang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M Wang. 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 M Wang. The network helps show where M Wang may publish in the future.

Co-authorship network of co-authors of M Wang

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

All Works

14 of 14 papers shown
1.
Sun, Baohua, Warren Fiskus, Yimin Qian, et al.. (2017). BET protein proteolysis targeting chimera (PROTAC) exerts potent lethal activity against mantle cell lymphoma cells. Leukemia. 32(2). 343–352. 136 indexed citations
2.
Shah, Jatin J., Feng Li, Sheeba K. Thomas, et al.. (2016). Siltuximab (CNTO 328) with lenalidomide, bortezomib and dexamethasone in newly-diagnosed, previously untreated multiple myeloma: an open-label phase I trial. Blood Cancer Journal. 6(2). e396–e396. 27 indexed citations
3.
Parmar, Simrit, Piyanuch Kongtim, Richard E. Champlin, et al.. (2014). Auto-SCT improves survival in systemic light chain amyloidosis: a retrospective analysis with 14-year follow-up. Bone Marrow Transplantation. 49(8). 1036–1041. 14 indexed citations
4.
Alexanian, Raymond, M Wang, Kay Delasalle, et al.. (2013). Value of novel agents and intensive therapy for patients with multiple myeloma. Bone Marrow Transplantation. 49(3). 422–425. 2 indexed citations
5.
Bjorklund, Chad C., Veerabhadran Baladandayuthapani, Hui‐Yi Lin, et al.. (2013). Evidence of a role for CD44 and cell adhesion in mediating resistance to lenalidomide in multiple myeloma: therapeutic implications. Leukemia. 28(2). 373–383. 99 indexed citations
6.
Wang, M, Kay Delasalle, Lei Feng, et al.. (2009). CR represents an early index of potential long survival in multiple myeloma. Bone Marrow Transplantation. 45(3). 498–504. 39 indexed citations
7.
Amit-Vazina, Mirit, Shishir Shishodia, David Harris, et al.. (2005). Atiprimod blocks STAT3 phosphorylation and induces apoptosis in multiple myeloma cells. British Journal of Cancer. 93(1). 70–80. 65 indexed citations
8.
Frederick, Mitchell J., et al.. (1999). Expression of apoptosis-related genes in human head and neck squamous cell carcinomas undergoing p53-mediated programmed cell death.. PubMed. 5(2). 361–9. 15 indexed citations
9.
Wang, M, James L. Abbruzzese, Helmut Friess, et al.. (1998). DNA adducts in human pancreatic tissues and their potential role in carcinogenesis.. PubMed. 58(1). 38–41. 61 indexed citations
10.
Liu, T.-J., Dorothy Taylor, M Wang, et al.. (1997). Head and neck squamous cell growth suppression using adenovirus-p53-FLAG: a potential marker for gene therapy trials.. PubMed. 3(2). 185–91. 13 indexed citations
11.
Clayman, Gary L., et al.. (1996). Gene Therapy for Head and Neck Cancer: Comparing the Tumor Suppressor Gene p53 and a Cell Cycle Regulator WAF1/CIP1 (p21). Archives of Otolaryngology - Head and Neck Surgery. 122(5). 489–493. 47 indexed citations
12.
Wang, M & Daniel J. Drucker. (1996). Activation of amylin gene transcription by LIM domain homeobox gene isl-1.. Molecular Endocrinology. 10(3). 243–251. 35 indexed citations
13.
Wang, M, et al.. (1996). Lipid peroxidation-induced putative malondialdehyde-DNA adducts in human breast tissues.. PubMed. 5(9). 705–10. 185 indexed citations
14.

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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