De Novo Pathway-Based Classification of Breast Cancer Subtypes

Publikation: Bidrag til bog/antologi/rapport › Bidrag til bog/antologi › Forskning › fagfællebedømt

Standard

De Novo Pathway-Based Classification of Breast Cancer Subtypes. / List, Markus; Alcaraz, Nicolas; Batra, Richa.

Protein-Protein Interaction Networks: Methods and Protocols. red. / Stefan Canzar; Francisca Rojas Ringeling. Humana Press, 2020. s. 201-213 (Methods in Molecular Biology, Bind 2074).

Publikation: Bidrag til bog/antologi/rapport › Bidrag til bog/antologi › Forskning › fagfællebedømt

Harvard

List, M, Alcaraz, N & Batra, R 2020, De Novo Pathway-Based Classification of Breast Cancer Subtypes. i S Canzar & FR Ringeling (red), Protein-Protein Interaction Networks: Methods and Protocols. Humana Press, Methods in Molecular Biology, bind 2074, s. 201-213. https://doi.org/10.1007/978-1-4939-9873-9_15

APA

List, M., Alcaraz, N., & Batra, R. (2020). De Novo Pathway-Based Classification of Breast Cancer Subtypes. I S. Canzar, & F. R. Ringeling (red.), Protein-Protein Interaction Networks: Methods and Protocols (s. 201-213). Humana Press. Methods in Molecular Biology Bind 2074 https://doi.org/10.1007/978-1-4939-9873-9_15

Vancouver

List M, Alcaraz N, Batra R. De Novo Pathway-Based Classification of Breast Cancer Subtypes. I Canzar S, Ringeling FR, red., Protein-Protein Interaction Networks: Methods and Protocols. Humana Press. 2020. s. 201-213. (Methods in Molecular Biology, Bind 2074). https://doi.org/10.1007/978-1-4939-9873-9_15

Author

List, Markus ; Alcaraz, Nicolas ; Batra, Richa. / De Novo Pathway-Based Classification of Breast Cancer Subtypes. Protein-Protein Interaction Networks: Methods and Protocols. red. / Stefan Canzar ; Francisca Rojas Ringeling. Humana Press, 2020. s. 201-213 (Methods in Molecular Biology, Bind 2074).

Bibtex

@inbook{98881bc730af472f8ecc2942d3908f26,
title = "De Novo Pathway-Based Classification of Breast Cancer Subtypes",
abstract = "Breast cancer is a heterogeneous disease for which various clinically relevant subtypes have been reported. These subtypes are characterized by molecular differences which direct treatment selection. The state of the art for breast cancer subtyping utilizes histochemistry or gene expression to measure a few selected markers. However, classification based on molecular pathways (rather than individual markers) is a more robust way to classify breast cancer samples into known subtypes. Here, we present PathClass, a web application that allows its users to predict breast cancer subtypes using various traditional as well as advanced methods. This includes methods based on classical gene expression panels as well as de novo pathway-based predictors. Users can predict labels for datasets in the Gene Expression Omnibus or upload their own expression profiling data. Availability: https://pathclass.compbio.sdu.dk/.",
keywords = "Breast cancer, Classification, De novo pathways, Disease subtyping",
author = "Markus List and Nicolas Alcaraz and Richa Batra",
year = "2020",
doi = "10.1007/978-1-4939-9873-9_15",
language = "English",
isbn = "978-1-4939-9872-2",
series = "Methods in Molecular Biology",
publisher = "Humana Press",
pages = "201--213",
editor = "Stefan Canzar and Ringeling, {Francisca Rojas}",
booktitle = "Protein-Protein Interaction Networks",
address = "United States",

}

RIS

TY - CHAP

T1 - De Novo Pathway-Based Classification of Breast Cancer Subtypes

AU - List, Markus

AU - Alcaraz, Nicolas

AU - Batra, Richa

PY - 2020

Y1 - 2020

N2 - Breast cancer is a heterogeneous disease for which various clinically relevant subtypes have been reported. These subtypes are characterized by molecular differences which direct treatment selection. The state of the art for breast cancer subtyping utilizes histochemistry or gene expression to measure a few selected markers. However, classification based on molecular pathways (rather than individual markers) is a more robust way to classify breast cancer samples into known subtypes. Here, we present PathClass, a web application that allows its users to predict breast cancer subtypes using various traditional as well as advanced methods. This includes methods based on classical gene expression panels as well as de novo pathway-based predictors. Users can predict labels for datasets in the Gene Expression Omnibus or upload their own expression profiling data. Availability: https://pathclass.compbio.sdu.dk/.

AB - Breast cancer is a heterogeneous disease for which various clinically relevant subtypes have been reported. These subtypes are characterized by molecular differences which direct treatment selection. The state of the art for breast cancer subtyping utilizes histochemistry or gene expression to measure a few selected markers. However, classification based on molecular pathways (rather than individual markers) is a more robust way to classify breast cancer samples into known subtypes. Here, we present PathClass, a web application that allows its users to predict breast cancer subtypes using various traditional as well as advanced methods. This includes methods based on classical gene expression panels as well as de novo pathway-based predictors. Users can predict labels for datasets in the Gene Expression Omnibus or upload their own expression profiling data. Availability: https://pathclass.compbio.sdu.dk/.

KW - Breast cancer

KW - Classification

KW - De novo pathways

KW - Disease subtyping

U2 - 10.1007/978-1-4939-9873-9_15

DO - 10.1007/978-1-4939-9873-9_15

M3 - Book chapter

C2 - 31583640

AN - SCOPUS:85072911207

SN - 978-1-4939-9872-2

T3 - Methods in Molecular Biology

SP - 201

EP - 213

BT - Protein-Protein Interaction Networks

A2 - Canzar, Stefan

A2 - Ringeling, Francisca Rojas

PB - Humana Press

ER -

ID: 230742706