Data science using the human epigenome for predicting multifactorial diseases and symptoms.

IF 3 4区医学 Q2 GENETICS & HEREDITY

Epigenomics Pub Date : 2024-03-01 Epub Date: 2024-02-05 DOI:10.2217/epi-2023-0321

Shota Nishitani, Alicia K Smith, Akemi Tomoda, Takashi X Fujisawa

引用次数: 0

Abstract

Tweetable abstract This article reviews machine learning models that leverages epigenomic data for predicting multifactorial diseases and symptoms as well as how such models can be utilized to explore new research questions.

查看原文本刊更多论文

利用人类表观基因组预测多因素疾病和症状的数据科学。

Tweetable 摘要本文回顾了利用表观基因组数据预测多因素疾病和症状的机器学习模型，以及如何利用这些模型探索新的研究问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Epigenomics GENETICS & HEREDITY-

CiteScore

5.80

自引率

2.60%

发文量

审稿时长

>12 weeks

期刊介绍： Epigenomics provides the forum to address the rapidly progressing research developments in this ever-expanding field; to report on the major challenges ahead and critical advances that are propelling the science forward. The journal delivers this information in concise, at-a-glance article formats – invaluable to a time constrained community. Substantial developments in our current knowledge and understanding of genomics and epigenetics are constantly being made, yet this field is still in its infancy. Epigenomics provides a critical overview of the latest and most significant advances as they unfold and explores their potential application in the clinical setting.