iTOP statistics

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Citations per year

Number of citations per year for the bioinformatics software tool iTOP
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Tool usage distribution map

This map represents all the scientific publications referring to iTOP per scientific context
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Associated diseases

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iTOP specifications

Information


Unique identifier OMICS_28335
Name iTOP
Alternative name inferring the TOPology
Software type Application/Script
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
License GNU General Public License version 2.0
Computer skills Advanced
Version 1.0.2
Stability Stable
Requirements
Matrix, rmarkdown, knitr, corpcor, Rgraphviz, NMF, pcalg
Maintained Yes

Versioning


No version available

Documentation


Maintainers


  • person_outline Lodewyk F.A. Wessels
  • person_outline Nanne Aben
  • person_outline Age Smilde

Publication for inferring the TOPology

iTOP citations

 (9)
library_books

Stable Gene Regulatory Network Modeling From Steady State Data †

2016
PMCID: 5597136
PMID: 28952574
DOI: 10.3390/bioengineering3020012

[…] r through the production of a protein [,].The process of identifying genetic interactions from measured gene expression data is referred to as reverse engineering or network inference or recovery []. Inferring the topology of GRNs and isolating functional subnetworks are computationally challenging tasks in contemporary functional genomics, and these efforts are valuable for advancing scientific i […]

library_books

Computational Performance and Statistical Accuracy of *BEAST and Comparisons with Other Methods

2016
Syst Biol
PMCID: 4851174
PMID: 26821913
DOI: 10.1093/sysbio/syv118

[…] asure, even when other methods were able to utilize thousands of loci (a).If instead branch lengths are irrelevant for a study, *BEAST still outperformed other methods for a given number of loci when inferring the topology of shallow species trees (e). However, when using thousands of loci, other methods were able to outperform *BEAST because *BEAST was restricted to tens of loci.For certain speci […]

library_books

Predictive analytics of environmental adaptability in multi omic network models

2015
Sci Rep
PMCID: 4611489
PMID: 26482106
DOI: 10.1038/srep15147

[…] . In the objective space, we showed how it is possible to further study this map through component analysis and spectral methods for community detection. A further extension of the framework could be inferring the topology of the network of conditions using a multidimensional scaling approach. Such computational analysis can have a great impact especially for the large fraction of microorganisms t […]

library_books

Uncovering distinct protein network topologies in heterogeneous cell populations

2015
BMC Syst Biol
PMCID: 4480582
PMID: 26040458
DOI: 10.1186/s12918-015-0170-2

[…] l species that can be co-measured per cell. The approaches to explore these data have focused so far either on identifying different subpopulations of cells based on multiparametric proximities or on inferring the topology of statistical relations between the parameters for the population as a whole. However, the aim to reach each of these two goals in separate has fundamental problems. In one dir […]

library_books

Neutral space analysis for a Boolean network model of the fission yeast cell cycle network

2014
PMCID: 4335775
PMID: 25723815
DOI: 10.1186/0717-6287-47-64

[…] tory relations identified in previous publications) [], (2) from transcriptional analysis of a set of knockouts or mutants [], and (3) from transcriptional time-series data of wild-type organisms []. Inferring the topology of a Boolean network from a set of experimental data involves two main steps: first, the experimental data (gene expression profiles or protein concentrations) must be discretiz […]

library_books

Genome Wide Inference of Ancestral Recombination Graphs

2014
PLoS Genet
PMCID: 4022496
PMID: 24831947
DOI: 10.1371/journal.pgen.1004342

[…] In our next experiment, we evaluated the accuracy of ARGweaver in inferring the topology of the local trees, again using the same simulated data. The local trees are a more complex feature of the ARG but are of particular interest for applications such as genotype i […]


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iTOP institution(s)
Division of Molecular Carcinogenesis, Oncode Institute, Netherlands Cancer Institute, Amsterdam, The Netherlands; Faculty of EEMCS, Delft University of Technology, Delft, The Netherlands; Swammerdam Institute for Life Sciences, University of Amsterdam, Amsterdam, The Netherlands; Heymans Institute, University of Groningen, Groningen, The Netherlands; Cancer Genomics Netherlands, Utrecht, The Netherlands
iTOP funding source(s)
Supported by the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013) / ERC synergy grant agreement n ◦ 319661 COMBATCANCER.

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