A supervised machine learning-based methodology for analyzing dysregulation in splicing machinery: An application in cancer diagnosis
Sign Up to like & getrecommendations! Published in 2020 at "Artificial intelligence in medicine"
DOI: 10.1016/j.artmed.2020.101950
Abstract: Deregulated splicing machinery components have shown to be associated with the development of several types of cancer and, therefore, the determination of such alterations can help the development of tumor-specific molecular targets for early prognosis… read more here.
Keywords: methodology; machine learning; splicing machinery; supervised machine ... See more keywords
Splicing machinery dysregulation drives glioblastoma development/aggressiveness: oncogenic role of SRSF3
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DOI: 10.1093/brain/awaa273
Abstract: Fuentes-Fayos et al. show that the expression of spliceosome components and splicing factors is dysregulated in high-grade astrocytomas and glioblastomas. The splicing machinery could be a new source of diagnostic and prognostic biomarkers as well… read more here.
Keywords: splicing machinery; machinery; drives glioblastoma; dysregulation drives ... See more keywords
Dietary Intervention Modulates the Expression of Splicing Machinery in Cardiovascular Patients at High Risk of Type 2 Diabetes Development: From the CORDIOPREV Study
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DOI: 10.3390/nu12113528
Abstract: Type-2 diabetes mellitus (T2DM) has become a major health problem worldwide. T2DM risk can be reduced with healthy dietary interventions, but the precise molecular underpinnings behind this association are still incompletely understood. We recently discovered… read more here.
Keywords: t2dm; risk; splicing machinery; machinery ... See more keywords