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Integrative Multi-Omics Data-Driven Approach for Metastasis Prediction in Cancer
(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 ...
Prediction of Peptide Vascularization Inhibitory Activity in Tumor Tissue as a Possible Target for Cancer Treatment
(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 ...
Molecular Docking and Machine Learning Analysis of Abemaciclib in Colon Cancer
(BioMed Central Ltd., 2020-07-08)
[Abstract]
Background -
The main challenge in cancer research is the identification of different omic variables that present a prognostic value and personalised diagnosis for each tumour. The fact that the diagnosis is ...
Gene Signatures Research Involved in Cancer Using Machine Learning
(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, ...
Identification of Prevotella, Anaerotruncus and Eubacterium Genera by Machine Learning Analysis of Metagenomic Profiles for Stratification of Patients Affected by Type I Diabetes
(MDPI AG, 2020-08-27)
[Abstract]
Previous works have reported different bacterial strains and genera as the cause of different clinical pathological conditions. In our approach, using the fecal metagenomic profiles of newborns, a machine ...