Mtreemix: a software package for learning and using mixture models of mutagenetic trees.
about
Cancer evolution: mathematical models and computational inferenceDifferences in reversion of resistance mutations to wild-type under structured treatment interruption and related increase in replication capacityBayesian estimation of mixture models with prespecified elements to compare drug resistance in treatment-naïve and experienced tuberculosis casesLearning 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.Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study.Combining cross-sectional and prospective data methods to improve transition parameter estimation for characterizing the accumulation of HIV-1 drug resistance mutations.Robust unmixing of tumor states in array comparative genomic hybridization dataAlgorithms to model single gene, single chromosome, and whole genome copy number changes jointly in tumor phylogenetics.Analysis of the copy number profiles of several tumor samples from the same patient reveals the successive steps in tumorigenesisInferring tree causal models of cancer progression with probability raising.FISHtrees 3.0: Tumor Phylogenetics Using a Ploidy ProbeDefining order and timing of mutations during cancer progression: the TO-DAG probabilistic graphical modelSelective pressures of HLA genotypes and antiviral therapy on human immunodeficiency virus type 1 sequence mutation at a population level.Construction of oncogenetic tree models reveals multiple pathways of oral cancer progression.Methods and challenges in timing chromosomal abnormalities within cancer samples.A phylogenetic and Markov model approach for the reconstruction of mutational pathways of drug resistance.Role of Gag mutations in PI resistance in the Swiss HIV cohort study: bystanders or contributors?The evolution of tumour phylogenetics: principles and practice.Bayesian methods for fitting mixture models that characterize branching tree processes: An application to development of resistant TB strains.Estimating the dynamics and dependencies of accumulating mutations with applications to HIV drug resistance.Quantifying cancer progression with conjunctive Bayesian networks.Rtreemix: an R package for estimating evolutionary pathways and genetic progression scores.Correspondence of tumor localization with tumor recurrence and cytogenetic progression in meningiomas.
P2860
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P2860
Mtreemix: a software package for learning and using mixture models of mutagenetic trees.
description
2005 nî lūn-bûn
@nan
2005年の論文
@ja
2005年学术文章
@wuu
2005年学术文章
@zh
2005年学术文章
@zh-cn
2005年学术文章
@zh-hans
2005年学术文章
@zh-my
2005年学术文章
@zh-sg
2005年學術文章
@yue
2005年學術文章
@zh-hant
name
Mtreemix: a software package for learning and using mixture models of mutagenetic trees.
@en
Mtreemix: a software package for learning and using mixture models of mutagenetic trees.
@nl
type
label
Mtreemix: a software package for learning and using mixture models of mutagenetic trees.
@en
Mtreemix: a software package for learning and using mixture models of mutagenetic trees.
@nl
prefLabel
Mtreemix: a software package for learning and using mixture models of mutagenetic trees.
@en
Mtreemix: a software package for learning and using mixture models of mutagenetic trees.
@nl
P2093
P50
P356
P1433
P1476
Mtreemix: a software package for learning and using mixture models of mutagenetic trees.
@en
P2093
Joachim Selbig
Niko Beerenwinkel
Rolf Kaiser
P304
P356
10.1093/BIOINFORMATICS/BTI274
P407
P577
2005-01-18T00:00:00Z