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Systems Biology of the Cancer Cell
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DOI：10.1146/annurev-bioeng-103122-030552.png)
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Abstract
En 中文
Questions in cancer have engaged systems biologists for decades. During that time, the quantity of molecular data has exploded, but the need for abstractions, formal models, and simplifying insights has remained the same. This review brings together classic breakthroughs and recent findings in the field of cancer systems biology, focusing on cancer cell pathways for tumorigenesis and therapeutic response. Cancer cells mutate and transduce information from their environment to alter gene expression, metabolism, and phenotypic states. Understanding the molecular architectures that make each of these steps possible is a long-term goal of cancer systems biology pursued by iterating between quantitative models and experiments. We argue that such iteration is the best path to deploying targeted therapies intelligently so that each patient receives the maximum benefit for their cancer.
Keywords:
mathematical model
differential equation
partial least squares
regression
Boolean networks
signal transduction
Journal
IF:
9.6
Papers:
482
Citations:
5.6K
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