#Book📚

Bioinformatics and Machine Learning for Cancer Biology
Year : (2022)

Moreover, thanks to the influx of next-generation sequencing (NGS) data in the postgenomic era and multiple landmark cancer-focused projects, such as The Cancer Genome Atlas (TCGA) and Clinical Proteomic Tumor Analysis Consortium (CPTAC), machine learning has a uniquely advantageous role in boosting data-driven cancer research and unraveling novel methods for the prognosis, prediction, and treatment of cancer.
This book presents some of the latest progresses on leveraging bioinformatics and machine learning for cancer biology, which is particularly useful and attractive for cancer biologists, bioinformaticians, machine learning experts, computational biologists and other scientists or researchers in life sciences and biology.
#Bioinformatics #MachineLearning
#CancerBiology
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