Literature DB >> 15657098

Mtreemix: a software package for learning and using mixture models of mutagenetic trees.

Niko Beerenwinkel1, Jörg Rahnenführer, Rolf Kaiser, Daniel Hoffmann, Joachim Selbig, Thomas Lengauer.   

Abstract

SUMMARY: Mixture models of mutagenetic trees constitute a class of probabilistic models for describing evolutionary processes that are characterized by the accumulation of permanent genetic changes. They have been applied to model the accumulation of chromosomal gains and losses in tumor development and the development of drug resistance-associated mutations in the HIV genome.Mtreemix is a software package for estimating mutagenetic trees mixture models from observed cross-sectional data and for using these models for predictions. We provide programs for model fitting, model selection, simulation, likelihood computation and waiting time estimation. AVAILABILITY: Mtreemix, including source code, documentation, sample data files and precompiled Solaris and Linux binaries, is freely available for non-commercial users at http://mtreemix.bioinf.mpi-sb.mpg.de/

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Year:  2005        PMID: 15657098     DOI: 10.1093/bioinformatics/bti274

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  27 in total

1.  Hyperdiploidy defines a distinct cytogenetic entity of meningiomas.

Authors:  Ralf Ketter; Yoo-Jin Kim; Simone Storck; Jörg Rahnenführer; Bernd F M Romeike; Wolf-Ingo Steudel; Klaus D Zang; Wolfram Henn
Journal:  J Neurooncol       Date:  2007-01-17       Impact factor: 4.130

Review 2.  The evolution of tumour phylogenetics: principles and practice.

Authors:  Russell Schwartz; Alejandro A Schäffer
Journal:  Nat Rev Genet       Date:  2017-02-13       Impact factor: 53.242

3.  A phylogenetic and Markov model approach for the reconstruction of mutational pathways of drug resistance.

Authors:  Patricia Buendia; Brice Cadwallader; Victor DeGruttola
Journal:  Bioinformatics       Date:  2009-08-03       Impact factor: 6.937

4.  Simultaneous inference of cancer pathways and tumor progression from cross-sectional mutation data.

Authors:  Benjamin J Raphael; Fabio Vandin
Journal:  J Comput Biol       Date:  2015-03-18       Impact factor: 1.479

5.  Classifying the Progression of Ductal Carcinoma from Single-Cell Sampled Data via Integer Linear Programming: A Case Study.

Authors:  Daniele Catanzaro; Stanley E Shackney; Alejandro A Schaffer; Russell Schwartz
Journal:  IEEE/ACM Trans Comput Biol Bioinform       Date:  2015-09-04       Impact factor: 3.710

6.  Bayesian methods for fitting mixture models that characterize branching tree processes: An application to development of resistant TB strains.

Authors:  Alane Izu; Ted Cohen; Carole Mitnick; Megan Murray; Victor De Gruttola
Journal:  Stat Med       Date:  2011-06-30       Impact factor: 2.373

7.  Selective pressures of HLA genotypes and antiviral therapy on human immunodeficiency virus type 1 sequence mutation at a population level.

Authors:  Golo Ahlenstiel; Kirsten Roomp; Martin Däumer; Jacob Nattermann; Martin Vogel; Jürgen K Rockstroh; Niko Beerenwinkel; Rolf Kaiser; Hans-Dieter Nischalke; Tilman Sauerbruch; Thomas Lengauer; Ulrich Spengler
Journal:  Clin Vaccine Immunol       Date:  2007-08-22

8.  Robust unmixing of tumor states in array comparative genomic hybridization data.

Authors:  David Tolliver; Charalampos Tsourakakis; Ayshwarya Subramanian; Stanley Shackney; Russell Schwartz
Journal:  Bioinformatics       Date:  2010-06-15       Impact factor: 6.937

9.  Analysis of the copy number profiles of several tumor samples from the same patient reveals the successive steps in tumorigenesis.

Authors:  Eric Letouzé; Yves Allory; Marc A Bollet; François Radvanyi; Frédéric Guyon
Journal:  Genome Biol       Date:  2010-07-22       Impact factor: 13.583

10.  Construction of oncogenetic tree models reveals multiple pathways of oral cancer progression.

Authors:  Swapnali Pathare; Alejandro A Schäffer; Niko Beerenwinkel; Manoj Mahimkar
Journal:  Int J Cancer       Date:  2009-06-15       Impact factor: 7.396

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