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Prediction of Peptide Vascularization Inhibitory Activity in Tumor Tissue as a Possible Target for Cancer Treatment 

Liñares Blanco, José; Fernández-Lozano, Carlos (M D P I AG, 2019-07-31)
[Abstract]The prediction of metabolic activities in silico form is crucial to be able to address all research possibilities without exceeding the experimental costs. In particular, for cancer research, the prediction of ...
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Gene Signatures Research Involved in Cancer Using Machine Learning 

Liñares Blanco, José; Fernández-Lozano, Carlos (M D P I AG, 2019)
[Abstract] With the cheapening of mass sequencing techniques and the rise of computer technologies, capable of analyzing a huge amount of data, it is necessary nowadays that both branches mutually benefit. Transcriptomics, ...
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Integrative Multi-Omics Data-Driven Approach for Metastasis Prediction in Cancer 

Fernández-Lozano, Carlos; Liñares Blanco, José; Gestal, M.; Dorado, Julián; Pazos, A. (ACM, 2018)
[Abstract] Nowadays biomedical research is generating huge amounts of omic data, covering all levels of genetic information from nucleotide sequencing to protein metabolism. In the beginning, data were analyzed independently ...

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AuthorFernández-Lozano, Carlos (3)Liñares Blanco, José (3)Dorado, Julián (1)Gestal, M. (1)Pazos, A. (1)Subject
Cancer (3)
Machine learning (3)
Activity prediction (1)Data fusion (1)Data integration (1)Data-driven (1)Feature selection (1)Modelling (1)Multi-Omics (1)Peptides (1)... View MoreDate Issued2019 (2)2018 (1)
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