Identification of tumor evolution patterns by means of inductive logic programming

Vitoantonio Bevilacqua; Patrizia Chiarappa; Giuseppe Mastronardi; Filippo Menolascina; Angelo Paradiso; Stefania Tommasi

doi:10.1016/S1672-0229(08)60024-8

Identification of tumor evolution patterns by means of inductive logic programming

Vitoantonio Bevilacqua, Patrizia Chiarappa, Giuseppe Mastronardi, Filippo Menolascina, Angelo Paradiso, Stefania Tommasi

School of Engineering

Research output: Contribution to journal › Article › peer-review

Abstract / Description of output

In considering key events of genomic disorders in the development and progression of cancer, the correlation between genomic instability and carcinogenesis is currently under investigation. In this work, we propose an inductive logic programming approach to the problem of modeling evolution patterns for breast cancer. Using this approach, it is possible to extract fingerprints of stages of the disease that can be used in order to develop and deliver the most adequate therapies to patients. Furthermore, such a model can help physicians and biologists in the elucidation of molecular dynamics underlying the aberrations-waterfall model behind carcinogenesis. By showing results obtained on a real-world dataset, we try to give some hints about further approach to the knowledge-driven validations of such hypotheses.

Original language	English
Pages (from-to)	91-7
Number of pages	7
Journal	Genomics, Proteomics and Bioinformatics
Volume	6
Issue number	2
DOIs	https://doi.org/10.1016/S1672-0229(08)60024-8
Publication status	Published - Jun 2008

Keywords / Materials (for Non-textual outputs)

Adult
Aged
Algorithms
Breast Neoplasms
Comparative Genomic Hybridization
Computational Biology
DNA, Neoplasm
Databases, Genetic
Female
Humans
Logistic Models
Middle Aged
Models, Genetic
Oligonucleotide Array Sequence Analysis

Access to Document

10.1016/S1672-0229(08)60024-8

Cite this

@article{682e8d396085452a8f2d68a436c04770,

title = "Identification of tumor evolution patterns by means of inductive logic programming",

abstract = "In considering key events of genomic disorders in the development and progression of cancer, the correlation between genomic instability and carcinogenesis is currently under investigation. In this work, we propose an inductive logic programming approach to the problem of modeling evolution patterns for breast cancer. Using this approach, it is possible to extract fingerprints of stages of the disease that can be used in order to develop and deliver the most adequate therapies to patients. Furthermore, such a model can help physicians and biologists in the elucidation of molecular dynamics underlying the aberrations-waterfall model behind carcinogenesis. By showing results obtained on a real-world dataset, we try to give some hints about further approach to the knowledge-driven validations of such hypotheses.",

keywords = "Adult, Aged, Algorithms, Breast Neoplasms, Comparative Genomic Hybridization, Computational Biology, DNA, Neoplasm, Databases, Genetic, Female, Humans, Logistic Models, Middle Aged, Models, Genetic, Oligonucleotide Array Sequence Analysis",

author = "Vitoantonio Bevilacqua and Patrizia Chiarappa and Giuseppe Mastronardi and Filippo Menolascina and Angelo Paradiso and Stefania Tommasi",

year = "2008",

month = jun,

doi = "10.1016/S1672-0229(08)60024-8",

language = "English",

volume = "6",

pages = "91--7",

journal = "Genomics, Proteomics and Bioinformatics",

issn = "1672-0229",

publisher = "Elsevier",

number = "2",

}

TY - JOUR

T1 - Identification of tumor evolution patterns by means of inductive logic programming

AU - Bevilacqua, Vitoantonio

AU - Chiarappa, Patrizia

AU - Mastronardi, Giuseppe

AU - Menolascina, Filippo

AU - Paradiso, Angelo

AU - Tommasi, Stefania

PY - 2008/6

Y1 - 2008/6

N2 - In considering key events of genomic disorders in the development and progression of cancer, the correlation between genomic instability and carcinogenesis is currently under investigation. In this work, we propose an inductive logic programming approach to the problem of modeling evolution patterns for breast cancer. Using this approach, it is possible to extract fingerprints of stages of the disease that can be used in order to develop and deliver the most adequate therapies to patients. Furthermore, such a model can help physicians and biologists in the elucidation of molecular dynamics underlying the aberrations-waterfall model behind carcinogenesis. By showing results obtained on a real-world dataset, we try to give some hints about further approach to the knowledge-driven validations of such hypotheses.

AB - In considering key events of genomic disorders in the development and progression of cancer, the correlation between genomic instability and carcinogenesis is currently under investigation. In this work, we propose an inductive logic programming approach to the problem of modeling evolution patterns for breast cancer. Using this approach, it is possible to extract fingerprints of stages of the disease that can be used in order to develop and deliver the most adequate therapies to patients. Furthermore, such a model can help physicians and biologists in the elucidation of molecular dynamics underlying the aberrations-waterfall model behind carcinogenesis. By showing results obtained on a real-world dataset, we try to give some hints about further approach to the knowledge-driven validations of such hypotheses.

KW - Adult

KW - Aged

KW - Algorithms

KW - Breast Neoplasms

KW - Comparative Genomic Hybridization

KW - Computational Biology

KW - DNA, Neoplasm

KW - Databases, Genetic

KW - Female

KW - Humans

KW - Logistic Models

KW - Middle Aged

KW - Models, Genetic

KW - Oligonucleotide Array Sequence Analysis

U2 - 10.1016/S1672-0229(08)60024-8

DO - 10.1016/S1672-0229(08)60024-8

M3 - Article

C2 - 18973865

SN - 1672-0229

VL - 6

SP - 91

EP - 97

JO - Genomics, Proteomics and Bioinformatics

JF - Genomics, Proteomics and Bioinformatics

IS - 2

ER -

Identification of tumor evolution patterns by means of inductive logic programming

Abstract / Description of output

Keywords / Materials (for Non-textual outputs)

Access to Document

Fingerprint

Cite this