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K-Branches specifications

Information


Unique identifier OMICS_14450
Name K-Branches
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 3.0
Computer skills Advanced
Version 0.21
Stability Stable
Requirements
destiny, k-branches
Maintained Yes

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Maintainer


  • person_outline Nikolaos-Kosmas Chlis <>

Publication for K-Branches

K-Branches in publications

 (4)
PMCID: 5860029
PMID: 28582478
DOI: 10.1093/bioinformatics/btx325

[…] however, they commonly assume specific geometries such as tree-like developmental hierarchies and lack statistically sound methods to decide on the number of branching events., we present k-branches, a solution to the above problem by locally fitting half-lines to single-cell data, introducing a clustering algorithm similar to k-means. these halflines are proxies for branches […]

PMCID: 4211445
PMID: 25253455
DOI: 10.1098/rspb.2014.1324

[…] branches of z that were extant during the follow-up [ts, te]. we denote this set by sz(k), and the elements of this set with x. furthermore, we denote with {k = o(z)} the event that a total of k branches were observed from tree z during the follow-up. in addition, {x, t|z)} denotes the event in which exactly the branches x were observed exactly at times t from z. finally, with {g|x, t, z}, […]

PMCID: 3226351
PMID: 22158732
DOI: 10.1016/j.disc.2011.07.028

[…] to show that almost all optimal trees fulfil lc2 and lc3. as a first step, we will show that almost all rooted subtrees of optimal trees contain a k-claw for k∈{2,3,4}, i.e., a rooted subtree with k branches all of which are single vertices, see (a). in a second step, the existence of k-claws will provide us with bounds for ρ(s) for rooted subtrees s of optimal trees. these bounds […]

PMCID: 1971121
PMID: 17845075
DOI: 10.1371/journal.pgen.0030147

[…] under various alternative scenarios to examine the performance of the modified aic method. specifically, for each k selected lineages (k = 0,…,6), we simulated 100,000 cncs in which each cnc has k branches that evolve with their own rates. these rates were higher or lower than the background rate with 50% probability each. to incorporate the variation in strength of signals in real data, […]


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K-Branches institution(s)
Institute of Computational Biology, Helmholtz Zentrum Munchen, Neuherberg, Germany; School of Life Sciences Weihenstephan, Technical University of Munich, Freising, Germany; Department of Mathematics, Technical University of Munich, Garching, Germany
K-Branches funding source(s)
This project was supported by a DFG Fellowship through the Graduate School of Quantitative Biosciences Munich (QBM) and the Helmholtz Postdoc Programme, Initiative and Networking Fund of the Helmholtz Association. It was also supported by the German Science Foundation as well as by the Bavarian government (BioSysNet).

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