Approximation algorithms for free-label maximization

Berg, Mark de; Gerrits, Dirk H. P.

doi:10.1016/j.comgeo.2011.10.004

Cited by 24 publications

(18 citation statements)

References 12 publications

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“…In ChIPseeqer, fast comparison on genomic intervals is performed using interval trees [39,40], ordered tree structures that store and index intervals with fast querying and processing times, and ensure efficient searching of all indexed intervals that overlap with any given interval or point. An interval tree is an augmented binary search tree: each node contains an interval and also stores the maximum endpoint of the subtree rooted at the particular node.…”

Section: Methodsmentioning

confidence: 99%

An integrated ChIP-seq analysis platform with customizable workflows

Γιαννοπούλου

Elemento

2011

BMC Bioinformatics

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BackgroundChromatin immunoprecipitation followed by next generation sequencing (ChIP-seq), enables unbiased and genome-wide mapping of protein-DNA interactions and epigenetic marks. The first step in ChIP-seq data analysis involves the identification of peaks (i.e., genomic locations with high density of mapped sequence reads). The next step consists of interpreting the biological meaning of the peaks through their association with known genes, pathways, regulatory elements, and integration with other experiments. Although several programs have been published for the analysis of ChIP-seq data, they often focus on the peak detection step and are usually not well suited for thorough, integrative analysis of the detected peaks.ResultsTo address the peak interpretation challenge, we have developed ChIPseeqer, an integrative, comprehensive, fast and user-friendly computational framework for in-depth analysis of ChIP-seq datasets. The novelty of our approach is the capability to combine several computational tools in order to create easily customized workflows that can be adapted to the user's needs and objectives. In this paper, we describe the main components of the ChIPseeqer framework, and also demonstrate the utility and diversity of the analyses offered, by analyzing a published ChIP-seq dataset.ConclusionsChIPseeqer facilitates ChIP-seq data analysis by offering a flexible and powerful set of computational tools that can be used in combination with one another. The framework is freely available as a user-friendly GUI application, but all programs are also executable from the command line, thus providing flexibility and automatability for advanced users.

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Section: Methodsmentioning

confidence: 99%

An integrated ChIP-seq analysis platform with customizable workflows

Γιαννοπούλου

Elemento

2011

BMC Bioinformatics

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“…Each inequality of the form

C (v, C_{Θ}, C_{ℓ}) \leq C (v', C_{Θ}, C_{ℓ})

induces a half-space and R ( v ) is the intersection of those half-spaces. The intersection of N half-spaces can be found in time

O (N \log N)

(Berg et al , 2008) and thus each region can be found in time

O (m^{2} \log m)

. Thus, all

| A |

regions can be found in time

O (m^{4} \log m)

.…”

Section: Algorithmsmentioning

confidence: 99%

Pareto-optimal phylogenetic tree reconciliation

Libeskind-Hadas

Bansal

et al. 2014

Bioinformatics

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Motivation: Phylogenetic tree reconciliation is a widely used method for reconstructing the evolutionary histories of gene families and species, hosts and parasites and other dependent pairs of entities. Reconciliation is typically performed using maximum parsimony, in which each evolutionary event type is assigned a cost and the objective is to find a reconciliation of minimum total cost. It is generally understood that reconciliations are sensitive to event costs, but little is understood about the relationship between event costs and solutions. Moreover, choosing appropriate event costs is a notoriously difficult problem.Results: We address this problem by giving an efficient algorithm for computing Pareto-optimal sets of reconciliations, thus providing the first systematic method for understanding the relationship between event costs and reconciliations. This, in turn, results in new techniques for computing event support values and, for cophylogenetic analyses, performing robust statistical tests. We provide new software tools and demonstrate their use on a number of datasets from evolutionary genomic and cophylogenetic studies.Availability and implementation: Our Python tools are freely available at www.cs.hmc.edu/∼hadas/xscape.Contact: mukul@engr.uconn.eduSupplementary information: Supplementary data are available at Bioinformatics online.

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“…By definition, Ω c is the Minkowski sum of the sets Ω a and Ω b , which is referred to as Ω c = Ω a ⊕ Ω b [17]. Further exploration of Ω c in the case of QPSK modulation is given in Appendix I.…”

Section: Complex Quadrature Spatial Modulationmentioning

confidence: 99%

Complex Quadrature Spatial Modulation

Mohaisen¹,

Lee²

2017

ETRI Journal

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In this paper, we propose a spatial modulation (SM) scheme referred to as complex quadrature SM (CQSM). In contrast to quadrature SM (QSM), CQSM transmits two complex signal constellation symbols on the real and quadrature spatial dimensions at each channel use, increasing the spectral efficiency. To achieve that, signal symbols transmitted at any given time instant are drawn from two different modulation sets. The first modulation set is any of the conventional QAM/PSK alphabets, while the second is a rotated version of it. The optimal rotation angle is obtained through simulations for several modulation schemes and analytically proven for the case of QPSK, where both results coincide. Simulation results showed that CQSM outperformed QSM and generalized SM by approximately 5 dB and 4.5 dB, respectively, for the same transmission rate. Its performance was similar to that of QSM; however, it achieved higher transmission rates. It was additionally shown numerically and analytically that CQSM outperformed QSM for a relatively large number of transmit antennas.

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Approximation algorithms for free-label maximization

Cited by 24 publications

References 12 publications

An integrated ChIP-seq analysis platform with customizable workflows

An integrated ChIP-seq analysis platform with customizable workflows

Pareto-optimal phylogenetic tree reconciliation

Complex Quadrature Spatial Modulation

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