Machine Learning Clustering for Cancer Analysis Employing Gene Expression Data

Camilo Andres Perez Ospino, Jorman Arbey Castro Rivera, Alvaro D. Orjuela-Canon

Research output: Chapter in Book/ReportConference contribution

Abstract

The idea that cancer types vary in their molecular structure (DNA, RNA, proteins, and epigenetics) depending on the origin and location of the cancer, has been worked on. The Cancer Genome Atlas (TCGA) has generated an initiative to carefully create a database to ensure quality data in the profiling of different tumors to promote research, a part of this large database was called Pan-Cancer, which has the genomic, epigenetic, transcriptional and proteomic profiling of 12 different types of cancer. In this research we took one of the profiling, RNA profiling, in 5 cancer types, in order to determine the possibility of segmenting in an unsupervised manner and to evaluate the difference of them by their origin. The results indicate that the number of clusters can vary from 5 to 7, with 5 clusters being established by the database labels, however, the division of 6 or 7 clusters is due to the clustering of breast cancer (BRCA) which has several origins.

Translated title of the contributionAgrupación de aprendizaje automático para el análisis del cáncer mediante datos de expresión génica
Original languageEnglish (US)
Title of host publication2023 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2023 - Proceedings
EditorsAlvaro David Orjuela-Canon
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350316599
DOIs
StatePublished - Aug 28 2023
Event2023 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2023 - Bogota, Colombia
Duration: Jul 26 2023Jul 28 2023

Publication series

Name2023 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2023 - Proceedings

Conference

Conference2023 IEEE Colombian Conference on Applications of Computational Intelligence, ColCACI 2023
Country/TerritoryColombia
CityBogota
Period7/26/237/28/23

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Control and Optimization

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