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An integrated computational strategy to predict personalized cancer drug combinations by reversing drug resistance signatures.
Wang, Xun; Yang, Lele; Yu, Chuang; Ling, Xinping; Guo, Congcong; Chen, Ruzhen; Li, Dong; Liu, Zhongyang.
Afiliación
  • Wang X; State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China.
  • Yang L; State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China; College of Chemistry and Environmental Science, Hebei University, Baoding, 071002, China.
  • Yu C; China Astronaut Research and Training Center, Beijing, 100094, China.
  • Ling X; State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China.
  • Guo C; State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China.
  • Chen R; State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China.
  • Li D; State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China; College of Chemistry and Environmental Science, Hebei University, Baoding, 071002, China. Electronic address: lidong.bprc@foxm
  • Liu Z; State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China; College of Chemistry and Environmental Science, Hebei University, Baoding, 071002, China. Electronic address: liuzy1984@163.co
Comput Biol Med ; 163: 107230, 2023 09.
Article en En | MEDLINE | ID: mdl-37418899
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Comput Biol Med Año: 2023 Tipo del documento: Article País de afiliación: China
Texto completo
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PubMed Links
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Neoplasias Tipo de estudio: Prognostic_studies / Risk_factors_studies Límite: Humans Idioma: En Revista: Comput Biol Med Año: 2023 Tipo del documento: Article País de afiliación: China