Faculty Collaboration Database

Estimating an oncogenetic tree when false negatives and positives are present. Math Biosci 2002 Apr;176(2):219-36

Date

03/28/2002

Pubmed ID

11916510

DOI

10.1016/s0025-5564(02)00086-x

Scopus ID

2-s2.0-0036224045 (requires institutional sign-in at Scopus site)   41 Citations

Abstract

Human solid tumors are believed to be caused by a sequence of genetic abnormalities arising in the tumor cells. The understanding of these sequences is extremely important for improving cancer treatment. Models for the occurrence of the abnormalities include linear structure and a recently proposed tree-based structure. In this paper we extend the pure oncogenetic tree model by introducing false positive and false negative observations. We state conditions sufficient for the reconstruction of the generating tree. As an example we analyze a comparative genomic hybridization data set and show that addition of the error model significantly improves the ability of the model to describe the data.

Author List

Szabo A, Boucher K

Author

Aniko Szabo PhD Professor in the Data Science Institute department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Adenocarcinoma, Clear Cell
Algorithms
Chromosome Aberrations
False Negative Reactions
False Positive Reactions
Female
Humans
Kidney Neoplasms
Male
Models, Genetic
Neoplasms
Nucleic Acid Hybridization
Oncogenes