A mathematical methodology for determining the temporal order of pathway alterations arising during gliomagenesis.
about
Computational medicine: translating models to clinical careCancer evolution: mathematical models and computational inferenceHeterogeneity of epidermal growth factor receptor signalling networks in glioblastomaLearning oncogenetic networks by reducing to mixed integer linear programming.Temporal ordering of cancer microarray data through a reinforcement learning based approach.Phylogenetic analysis of multiprobe fluorescence in situ hybridization data from tumor cell populations.Simultaneous inference of cancer pathways and tumor progression from cross-sectional mutation data.CAPRI: efficient inference of cancer progression models from cross-sectional data.Most human non-GCIMP glioblastoma subtypes evolve from a common proneural-like precursor gliomaIdentification of constrained cancer driver genes based on mutation timingIdentifying restrictions in the order of accumulation of mutations during tumor progression: effects of passengers, evolutionary models, and sampling.Cancer stem cells in glioblastomaAnalysis of gene copy number changes in tumor phylogeneticsDefining order and timing of mutations during cancer progression: the TO-DAG probabilistic graphical modelPhylogenetic analysis of multiple FISH markers in oral tongue squamous cell carcinoma suggests that a diverse distribution of copy number changes is associated with poor prognosis.The role of targeted therapies in the management of progressive glioblastoma : a systematic review and evidence-based clinical practice guideline.Variable selection for disease progression models: methods for oncogenetic trees and application to cancer and HIV.Computational approaches for the identification of cancer genes and pathwaysThe evolution of tumour phylogenetics: principles and practice.Network analysis of genomic alteration profiles reveals co-altered functional modules and driver genes for glioblastoma.Dissecting human gliomas by single-cell RNA sequencing.
P2860
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P2860
A mathematical methodology for determining the temporal order of pathway alterations arising during gliomagenesis.
description
2012 nî lūn-bûn
@nan
2012 թուականի Յունուարին հրատարակուած գիտական յօդուած
@hyw
2012 թվականի հունվարին հրատարակված գիտական հոդված
@hy
2012年の論文
@ja
2012年論文
@yue
2012年論文
@zh-hant
2012年論文
@zh-hk
2012年論文
@zh-mo
2012年論文
@zh-tw
2012年论文
@wuu
name
A mathematical methodology for ...... arising during gliomagenesis.
@ast
A mathematical methodology for ...... arising during gliomagenesis.
@en
A mathematical methodology for ...... arising during gliomagenesis.
@nl
type
label
A mathematical methodology for ...... arising during gliomagenesis.
@ast
A mathematical methodology for ...... arising during gliomagenesis.
@en
A mathematical methodology for ...... arising during gliomagenesis.
@nl
prefLabel
A mathematical methodology for ...... arising during gliomagenesis.
@ast
A mathematical methodology for ...... arising during gliomagenesis.
@en
A mathematical methodology for ...... arising during gliomagenesis.
@nl
P2093
P2860
P1476
A mathematical methodology for ...... arising during gliomagenesis.
@en
P2093
Eric C Holland
Franziska Michor
Ingo K Mellinghoff
Rameen Beroukhim
Ross L Levine
Yu-Kang Cheng
P2860
P304
P356
10.1371/JOURNAL.PCBI.1002337
P577
2012-01-05T00:00:00Z