His primary scientific interests are in Cancer research, Internal medicine, Cell biology, Genetics and Gene. His research in Cancer research intersects with topics in Cancer, Mutation, Immunology, microRNA and Lung cancer. He has included themes like Epithelial–mesenchymal transition, Targeted therapy and KRAS in his Lung cancer study.
His Internal medicine study incorporates themes from Placebo, Endocrinology and Oncology. His studies in Cell biology integrate themes in fields like Cell cycle, Ubiquitin ligase and Transplantation. DNA methylation, Oncogene and Proteomics are the subjects of his Gene studies.
His primary areas of study are Cancer research, Internal medicine, Cancer, Artificial intelligence and Lung cancer. His Cancer research research is multidisciplinary, incorporating elements of Cell growth, Immune system, Immunology, PI3K/AKT/mTOR pathway and Adenocarcinoma. His biological study spans a wide range of topics, including Endocrinology, Oncology and Cardiology.
Cancer is closely attributed to Pathology in his study. His Artificial intelligence research includes themes of Computer vision and Pattern recognition. His research in Iterative reconstruction tackles topics such as Imaging phantom which are related to areas like Cone beam computed tomography.
Jing Wang focuses on Cancer research, Internal medicine, Cancer, Oncology and Lung cancer. His Cancer research study also includes
All of his Cancer and Breast cancer and KRAS investigations are sub-components of the entire Cancer study. His study focuses on the intersection of Oncology and fields such as Avelumab with connections in the field of Axitinib, Sunitinib and Renal cell carcinoma. His Lung cancer study frequently links to related topics such as Metastasis.
Jing Wang mostly deals with Cancer research, Internal medicine, Oncology, Lung cancer and Artificial intelligence. His Cancer research study integrates concerns from other disciplines, such as Epithelial–mesenchymal transition, Downregulation and upregulation and Cancer, Immune system, Immunotherapy. Jing Wang interconnects Microarray, Microarray analysis techniques and Gene duplication, Gene in the investigation of issues within Cancer.
His study in the fields of Ruxolitinib under the domain of Internal medicine overlaps with other disciplines such as Active control. His Lung cancer research includes elements of Immunohistochemistry, Targeted therapy and Metastasis. The concepts of his Artificial intelligence study are interwoven with issues in Receiver operating characteristic and Pattern recognition.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Comprehensive molecular profiling of lung adenocarcinoma: The cancer genome atlas research network
Eric A. Collisson;Joshua D. Campbell;Angela N. Brooks;Angela N. Brooks;Alice H. Berger.
Synthesis of Large Arrays of Well-Aligned Carbon Nanotubes on Glass
Z. F. Ren;Z. P. Huang;J. W. Xu;J. H. Wang.
WEGO: a web tool for plotting GO annotations
Jia Ye;Lin Fang;Hongkun Zheng;Yong Zhang.
Nucleic Acids Research (2006)
Exome sequencing of head and neck squamous cell carcinoma reveals inactivating mutations in NOTCH1
Nishant Agrawal;Mitchell J. Frederick;Curtis R. Pickering;Chetan Bettegowda.
Comprehensive genomic characterization of head and neck squamous cell carcinomas
Michael S. Lawrence;Carrie Sougnez;Lee Lichtenstein;Kristian Cibulskis.
WEB-based GEne SeT AnaLysis Toolkit (WebGestalt): update 2013
Jing Wang;Dexter T. Duncan;Zhiao Shi;Bing Zhang.
Nucleic Acids Research (2013)
Self-Monitoring in Weight Loss: A Systematic Review of the Literature
Lora E. Burke;Jing Wang;Mary Ann Sevick;Mary Ann Sevick.
Journal of The American Dietetic Association (2011)
Proteogenomics connects somatic mutations to signalling in breast cancer
Philipp Mertins;D. R. Mani;Kelly V. Ruggles;Michael A. Gillette;Michael A. Gillette.
Avelumab plus Axitinib versus Sunitinib for Advanced Renal-Cell Carcinoma
Robert J. Motzer;Konstantin Penkov;John Haanen;Brian Rini.
The New England Journal of Medicine (2019)
An Epithelial–Mesenchymal Transition Gene Signature Predicts Resistance to EGFR and PI3K Inhibitors and Identifies Axl as a Therapeutic Target for Overcoming EGFR Inhibitor Resistance
Lauren Averett Byers;Lixia Diao;Jing Wang;Pierre Saintigny.
Clinical Cancer Research (2013)
Profile was last updated on December 6th, 2021.
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