Multi-Omics Model Applied to Cancer Genetics

被引:27
作者
Pettini, Francesco [1 ]
Visibelli, Anna [2 ]
Cicaloni, Vittoria [3 ]
Iovinelli, Daniele [2 ]
Spiga, Ottavia [2 ]
机构
[1] Univ Siena, Dept Med Biotechnol, Via M Bracci 2, I-53100 Siena, Italy
[2] Univ Siena, Dept Biotechnol Chem & Pharm, Via A Moro 2, I-53100 Siena, Italy
[3] Toscana Life Sci Fdn, Via Fiorentina 1, I-53100 Siena, Italy
关键词
data analysis; artificial intelligence; precision medicine; machine learning models; computational oncology; cancer disease; omics tools; SYSTEMS BIOLOGY; R PACKAGE; R/BIOCONDUCTOR PACKAGE; DATA INTEGRATION; DNA METHYLATION; READ ALIGNMENT; HISTONE; IDENTIFICATION; EXPRESSION; GENOME;
D O I
10.3390/ijms22115751
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
In this review, we focus on bioinformatic oncology as an integrative discipline that incorporates knowledge from the mathematical, physical, and computational fields to further the biomedical understanding of cancer. Before providing a deeper insight into the bioinformatics approach and utilities involved in oncology, we must understand what is a system biology framework and the genetic connection, because of the high heterogenicity of the backgrounds of people approaching precision medicine. In fact, it is essential to providing general theoretical information on genomics, epigenomics, and transcriptomics to understand the phases of multi-omics approach. We consider how to create a multi-omics model. In the last section, we describe the new frontiers and future perspectives of this field.
引用
收藏
页数:21
相关论文
共 50 条
  • [41] Identifying Multi-Omics Causers and Causal Pathways for Complex Traits
    Qin, Huaizhen
    Niu, Tianhua
    Zhao, Jinying
    [J]. FRONTIERS IN GENETICS, 2019, 10
  • [42] Multi-omics to predict changes during cold pressor test
    Kogelman, Lisette J. A.
    Ernst, Madeleine
    Falkenberg, Katrine
    Mazzoni, Gianluca
    Courraud, Julie
    Lundgren, Li Peng
    Laursen, Susan Svane
    Cohen, Arieh
    Olesen, Jes
    Hansen, Thomas Folkmann
    [J]. BMC GENOMICS, 2022, 23 (01)
  • [43] Multi-omics integration reveals molecular networks and regulators of psoriasis
    Zhao, Yuqi
    Jhamb, Deepali
    Shu, Le
    Arneson, Douglas
    Rajpal, Deepak K.
    Yang, Xia
    [J]. BMC SYSTEMS BIOLOGY, 2019, 13
  • [44] Microbiome Research and Multi-Omics Integration for Personalized Medicine in Asthma
    Logotheti, Marianthi
    Agioutantis, Panagiotis
    Katsaounou, Paraskevi
    Loutrari, Heleni
    [J]. JOURNAL OF PERSONALIZED MEDICINE, 2021, 11 (12):
  • [45] Multi-omics perspective on studying reproductive biology in Daphnia sinensis
    Jia, Jingyi
    Dong, Chenchen
    Han, Mengqi
    Ma, Siqi
    Chen, Wenkai
    Dou, Jun
    Feng, Cui
    Liu, Xiangjiang
    [J]. GENOMICS, 2022, 114 (02)
  • [46] Integrated Multi-Omics Maps of Lower-Grade Gliomas
    Binder, Hans
    Schmidt, Maria
    Hopp, Lydia
    Davitavyan, Suren
    Arakelyan, Arsen
    Loeffler-Wirth, Henry
    [J]. CANCERS, 2022, 14 (11)
  • [47] Machine learning and multi-omics in precision medicine for ME/CFS
    Huang, Katherine
    Lidbury, Brett A.
    Thomas, Natalie
    Gooley, Paul R.
    Armstrong, Christopher W.
    [J]. JOURNAL OF TRANSLATIONAL MEDICINE, 2025, 23 (01)
  • [48] Navigating Challenges and Opportunities in Multi-Omics Integration for Personalized Healthcare
    Mohr, Alex E.
    Ortega-Santos, Carmen P.
    Whisner, Corrie M.
    Klein-Seetharaman, Judith
    Jasbi, Paniz
    [J]. BIOMEDICINES, 2024, 12 (07)
  • [49] A Similarity Regression Fusion Model for Integrating Multi-Omics Data to Identify Cancer Subtypes
    Guo, Yang
    Zheng, Jianning
    Shang, Xuequn
    Li, Zhanhuai
    [J]. GENES, 2018, 9 (07):
  • [50] Integrative, multi-omics, analysis of blood samples improves model predictions: applications to cancer
    Erica Ponzi
    Magne Thoresen
    Therese Haugdahl Nøst
    Kajsa Møllersen
    [J]. BMC Bioinformatics, 22