A Bayesian Approach to Determine the Composition of Heterogeneous Cancer Tissue Conference Paper uri icon

abstract

  • 2017 Copyright held by the owner/author(s). Cancer Tissue Heterogeneity is an important consideration in cancer research as it can give insights into the causes and progression of cancer. It is known to play a significant role in cancer cell survival, growth and metastasis. Determining the compositional breakup of a heterogeneous cancer tissue can also help address the therapeutic challenges posed by heterogeneity. This necessitates a low cost, scalable algorithm to address the challenge of accurate estimation of the composition of a heterogeneous cancer tissue. In this paper, we propose an algorithm to tackle this problem by utilizing the data of accurate, but high cost, single cell line cell-by-cell observation methods in low cost ensemble observation method for heterogeneous cancer cell mixtures to obtain their composition in a Bayesian framework. The algorithm is analyzed and validated using synthetic data and experimental data obtained from mixtures of cancer cell lines.

name of conference

  • Proceedings of the 8th ACM International Conference on Bioinformatics, Computational Biology,and Health Informatics

published proceedings

  • ACM-BCB' 2017: PROCEEDINGS OF THE 8TH ACM INTERNATIONAL CONFERENCE ON BIOINFORMATICS, COMPUTATIONAL BIOLOGY,AND HEALTH INFORMATICS

author list (cited authors)

  • Katiyar, A., Mohanty, A., Sima, C., Hua, J., Lopes, R., Datta, A., & Bittner, M. L.

citation count

  • 0

complete list of authors

  • Katiyar, Ashish||Mohanty, Anwoy||Sima, Chao||Hua, Jianping||Lopes, Rosana||Datta, Aniruddha||Bittner, Michael L

publication date

  • August 2017