Data-driven systems biology approaches

Systems Biology Approaches to Mining High Throughput Biological Data

With advances in high throughput measurement techniques, large-scale biological data have been and will continuously be produced, for example, gene expression data, protein-protein interaction (PPI) data, tandem mass spectra data, microRNA expression data, lncRNA expression data, and biomolecule-disease association data. Such data contain insightful information for understanding the mechanism o...

Multiobjective approaches to the data driven analysis of biological systems

Systems Approaches to Cancer Biology.

Cancer systems biology aims to understand cancer as an integrated system of genes, proteins, networks, and interactions rather than an entity of isolated molecular and cellular components. The inaugural Systems Approaches to Cancer Biology Conference, cosponsored by the Association of Early Career Cancer Systems Biologists and the National Cancer Institute of the NIH, focused on the interdiscip...

Data-Driven Approaches to Improve the Quality of Clinical Processes: A Systematic Review

Background: Considering the emergence of electronic health records and their related technologies, an increasing attention is paid to data driven approaches like machine learning, data mining, and process mining. The aim of this paper was to identify and classify these approaches to enhance the quality of clinical processes. Methods: In order to determine the knowledge related to the research ...

Personalized medicine approaches for colon cancer driven by genomics and systems biology: OncoTrack

The post-genomic era promises to pave the way to a personalized understanding of disease processes, with technological and analytical advances helping to solve some of the world's health challenges. Despite extraordinary progress in our understanding of cancer pathogenesis, the disease remains one of the world's major medical problems. New therapies and diagnostic procedures to guide their clin...