@inbook{acbb6ec4d41643ba8452bb457b799631,
title = "The Search for Cancer Drivers",
abstract = "During the past decade, significant technological and computational advances have provided unprecedented opportunities for gaining a better understanding of cancer biology and translating this knowledge into meaningful and concrete clinical benefits. Research has made considerable progress in identifying genes and molecular changes that promote cancer initiation and progression. Large-scale genomic and transcriptomic studies involving thousands of patients have prompted the development of sophisticated computational approaches and tools that enable identifying key driver alterations and characterizing their impact on tumor development. This chapter provides an overview of the basic principles that describe the complexity of cancer, which are known as cancer hallmarks, as well as the most relevant computational techniques and tools that have been designed to investigate the genes and genomic changes that contribute to these hallmarks.",
keywords = "Cancer hallmarks, copy number alteration, driver, gene fusion, multiomics, mutation, non-coding driver, oncogene, pathway, regulatory network, tumor suppressor",
author = "Alessandro Lagan{\`a}",
note = "Publisher Copyright: {\textcopyright} The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.",
year = "2024",
doi = "10.1007/978-3-031-55248-9\_8",
language = "English",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "145--171",
booktitle = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
address = "Germany",
}