DeepHisCoM: deep learning pathway analysis using hierarchical structural component models

计算生物学 生物途径 信号转导 MAPK/ERK通路 生物 代谢途径 生物信息学 基因 遗传学 基因表达
作者
Chanwoo Park,Boram Kim,Taesung Park
出处
期刊:Briefings in Bioinformatics [Oxford University Press]
卷期号:23 (5)
标识
DOI:10.1093/bib/bbac171
摘要

Many statistical methods for pathway analysis have been used to identify pathways associated with the disease along with biological factors such as genes and proteins. However, most pathway analysis methods neglect the complex nonlinear relationship between biological factors and pathways. In this study, we propose a Deep-learning pathway analysis using Hierarchical structured CoMponent models (DeepHisCoM) that utilize deep learning to consider a nonlinear complex contribution of biological factors to pathways by constructing a multilayered model which accounts for hierarchical biological structure. Through simulation studies, DeepHisCoM was shown to have a higher power in the nonlinear pathway effect and comparable power for the linear pathway effect when compared to the conventional pathway methods. Application to hepatocellular carcinoma (HCC) omics datasets, including metabolomic, transcriptomic and metagenomic datasets, demonstrated that DeepHisCoM successfully identified three well-known pathways that are highly associated with HCC, such as lysine degradation, valine, leucine and isoleucine biosynthesis and phenylalanine, tyrosine and tryptophan. Application to the coronavirus disease-2019 (COVID-19) single-nucleotide polymorphism (SNP) dataset also showed that DeepHisCoM identified four pathways that are highly associated with the severity of COVID-19, such as mitogen-activated protein kinase (MAPK) signaling pathway, gonadotropin-releasing hormone (GnRH) signaling pathway, hypertrophic cardiomyopathy and dilated cardiomyopathy. Codes are available at https://github.com/chanwoo-park-official/DeepHisCoM.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
wjx关闭了wjx文献求助
1秒前
芙卡洛斯完成签到,获得积分20
2秒前
爱听歌初曼完成签到,获得积分10
2秒前
星辰大海应助可耐的青雪采纳,获得10
3秒前
ZM发布了新的文献求助10
3秒前
活力的青枫完成签到,获得积分10
4秒前
勤恳紫霜完成签到,获得积分10
4秒前
wjx关闭了wjx文献求助
5秒前
5秒前
莲枳榴莲完成签到,获得积分10
5秒前
6秒前
6秒前
8秒前
9秒前
wjx关闭了wjx文献求助
10秒前
10秒前
顾矜应助Eve采纳,获得10
10秒前
勤恳紫霜发布了新的文献求助10
10秒前
11秒前
大个应助农大彭于晏采纳,获得10
11秒前
Maisie发布了新的文献求助30
11秒前
无奈镜子发布了新的文献求助10
12秒前
12秒前
早茶可口完成签到,获得积分10
12秒前
所所应助shuo采纳,获得10
12秒前
一枝完成签到 ,获得积分10
13秒前
精明的沅应助mysci采纳,获得10
13秒前
wjx关闭了wjx文献求助
15秒前
weilai发布了新的文献求助10
15秒前
15秒前
17秒前
sail完成签到,获得积分10
17秒前
17秒前
脑洞疼应助ccq采纳,获得10
17秒前
eirainal001给eirainal001的求助进行了留言
18秒前
19秒前
wjx关闭了wjx文献求助
19秒前
shuo完成签到,获得积分10
19秒前
Ava应助花生什么树采纳,获得10
19秒前
领导范儿应助梅伊斯采纳,获得10
20秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
Picture Books with Same-sex Parented Families: Unintentional Censorship 700
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 500
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
不知道标题是什么 500
Indomethacinのヒトにおける経皮吸収 400
Phylogenetic study of the order Polydesmida (Myriapoda: Diplopoda) 370
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3975378
求助须知:如何正确求助?哪些是违规求助? 3519775
关于积分的说明 11199621
捐赠科研通 3256067
什么是DOI,文献DOI怎么找? 1798124
邀请新用户注册赠送积分活动 877386
科研通“疑难数据库(出版商)”最低求助积分说明 806305