Cargando…
An Optimal Time for Treatment—Predicting Circadian Time by Machine Learning and Mathematical Modelling
SIMPLE SUMMARY: Personalized cancer treatments show decreased side-effects and improved treatment success. One aspect of individualized treatment is the timing of medicine intake, which may be optimized based on the biological diurnal rhythm of the patient. The personal biological time can be assess...
Autores principales: | Hesse, Janina, Malhan, Deeksha, Yalҫin, Müge, Aboumanify, Ouda, Basti, Alireza, Relógio, Angela |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7690897/ https://www.ncbi.nlm.nih.gov/pubmed/33114254 http://dx.doi.org/10.3390/cancers12113103 |
Ejemplares similares
-
A mathematical model of the circadian clock and drug pharmacology to optimize irinotecan administration timing in colorectal cancer
por: Hesse, Janina, et al.
Publicado: (2021) -
Transcriptome analysis of clock disrupted cancer cells reveals differential alternative splicing of cancer hallmarks genes
por: Malhan, Deeksha, et al.
Publicado: (2022) -
Diurnal variations in the expression of core-clock genes correlate with resting muscle properties and predict fluctuations in exercise performance across the day
por: Basti, Alireza, et al.
Publicado: (2021) -
A Computational Analysis in a Cohort of Parkinson’s Disease Patients and Clock-Modified Colorectal Cancer Cells Reveals Common Expression Alterations in Clock-Regulated Genes
por: Yalçin, Müge, et al.
Publicado: (2021) -
The Core-Clock Gene NR1D1 Impacts Cell Motility In Vitro and Invasiveness in a Zebrafish Xenograft Colon Cancer Model
por: Basti, Alireza, et al.
Publicado: (2020)