Machine learning and multi-omics data in chronic lymphocytic leukemia: the future of precision medicine?

被引：6

作者：

Tsagiopoulou, Maria ^{[1
]}

Gut, Ivo G. ^{[1
,2
]}

机构：

[1] Ctr Nacl Anal Genom CNAG, Barcelona, Spain

[2] Univ Barcelona UB, Barcelona, Spain

来源：

FRONTIERS IN GENETICS | 2024年 / 14卷

关键词：

machine Learning; omics; multi-omics analysis; precision medicine; chronic lymphocytic leukemia (CLL); bioinformatics; NGS -next generation sequencing; SUBGROUPS; FORM;

D O I：

10.3389/fgene.2023.1304661

中图分类号：

Q3 [遗传学];

学科分类号：

071007 ; 090102 ;

摘要：

Chronic lymphocytic leukemia is a complex and heterogeneous hematological malignancy. The advance of high-throughput multi-omics technologies has significantly influenced chronic lymphocytic leukemia research and paved the way for precision medicine approaches. In this review, we explore the role of machine learning in the analysis of multi-omics data in this hematological malignancy. We discuss recent literature on different machine learning models applied to single omic studies in chronic lymphocytic leukemia, with a special focus on the potential contributions to precision medicine. Finally, we highlight the recently published machine learning applications in multi-omics data in this area of research as well as their potential and limitations.

引用

页数：7

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