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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
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Cancer arises from mutations in the critical genes that allow healthy cells to escape cell cycle regulation and acquire the ability to proliferate indefinitely. Though originating from a single mutation event in one of the originator cells, cancer progresses when the mutant cell lines continue to gain more and more mutations, and finally, become malignant. For example, chronic myelogenous leukemia (CML) develops initially as a non-lethal increase in white blood cells, which progressively...
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Genes usually encode proteins necessary for the proper functioning of a healthy cell. Mutations can often cause changes to the gene expression pattern, thereby altering the phenotype.
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Multi-Omics Model Applied to Cancer Genetics.

Francesco Pettini1, Anna Visibelli2, Vittoria Cicaloni3

  • 1Department of Medical Biotechnology, University of Siena, Via M. Bracci 2, 53100 Siena, Italy.

International Journal of Molecular Sciences
|June 2, 2021
PubMed
Summary

Bioinformatic oncology integrates diverse fields to advance cancer research. This review explains system biology, multi-omics approaches, and future directions in precision medicine for better cancer understanding.

Keywords:
artificial intelligencecancer diseasecomputational oncologydata analysismachine learning modelsomics toolsprecision medicine

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Area of Science:

  • Bioinformatics
  • Computational Biology
  • Cancer Research

Background:

  • Precision medicine requires understanding complex biological systems.
  • Cancer's heterogeneity necessitates integrative approaches.
  • Genomic, epigenomic, and transcriptomic data are crucial.

Purpose of the Study:

  • To review bioinformatic oncology as an integrative discipline.
  • To explain system biology frameworks and genetic connections in cancer.
  • To detail multi-omics approaches and model creation.

Main Methods:

  • Review of current literature on bioinformatics in oncology.
  • Explanation of theoretical concepts in genomics, epigenomics, and transcriptomics.
  • Discussion on multi-omics data integration and modeling.

Main Results:

  • Bioinformatic oncology offers a powerful framework for cancer research.
  • Understanding system biology and multi-omics is key to precision medicine.
  • The field is rapidly evolving with new frontiers and future perspectives.

Conclusions:

  • Bioinformatic oncology is essential for advancing biomedical understanding of cancer.
  • Multi-omics approaches are critical for personalized cancer treatment.
  • Future research will focus on novel computational tools and integrative models.