Visualization of genomic changes by segmented smoothing using an L0 penalty - Wikidata - awgldk - TriplyDB

Visualization of genomic changes by segmented smoothing using an L0 penalty

Visualization of genomic changes by segmented smoothing using an L0 penalty

http://www.wikidata.org/entity/Q34297079

about

An Adaptive Ridge Procedure for L0 Regularization.Application of quantile regression to recent genetic and -omic studies.

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P2860

Visualization of genomic changes by segmented smoothing using an L0 penalty

http://www.wikidata.org/entity/Q34297079

description

2012 nî lūn-bûn

@nan

2012 թուականի Յունիսին հրատարակուած գիտական յօդուած

@hyw

2012 թվականի հունիսին հրատարակված գիտական հոդված

@hy

2012年の論文

@ja

2012年論文

@yue

2012年論文

@zh-hant

2012年論文

@zh-hk

2012年論文

@zh-mo

2012年論文

@zh-tw

2012年论文

@wuu

name

Visualization of genomic changes by segmented smoothing using an L0 penalty

@ast

Visualization of genomic changes by segmented smoothing using an L0 penalty

@en

Visualization of genomic changes by segmented smoothing using an L0 penalty

@nl

type

label

Visualization of genomic changes by segmented smoothing using an L0 penalty

@ast

Visualization of genomic changes by segmented smoothing using an L0 penalty

@en

Visualization of genomic changes by segmented smoothing using an L0 penalty

@nl

prefLabel

Visualization of genomic changes by segmented smoothing using an L0 penalty

@ast

Visualization of genomic changes by segmented smoothing using an L0 penalty

@en

Visualization of genomic changes by segmented smoothing using an L0 penalty

@nl

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Visualization of genomic changes by segmented smoothing using an L0 penalty

@en

P2093

Jacqueline J Meulman

http://www.w3.org/2001/XMLSchema#string

Paul H C Eilers

http://www.w3.org/2001/XMLSchema#string

Ralph C A Rippe

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P2860

PennCNV: an integrated hidden Markov model designed for high-resolution copy number variation detection in whole-genome SNP genotyping data

Comparative analysis of algorithms for identifying amplifications and deletions in array CGH data.

QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data.

Quantile smoothing of array CGH data.

MSMAD: a computationally efficient method for the analysis of noisy array CGH data.

MixHMM: inferring copy number variation and allelic imbalance using SNP arrays and tumor samples mixed with stromal cells

Efficient change point detection for genomic sequences of continuous measurements.

The effect of algorithms on copy number variant detection.

Accuracy of CNV Detection from GWAS Data.

Assessment of copy number variation using the Illumina Infinium 1M SNP-array: a comparison of methodological approaches in the Spanish Bladder Cancer/EPICURO study.

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e38230

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scholarly article

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10.1371/JOURNAL.PONE.0038230

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6

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7

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2012-06-05T00:00:00Z

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225281070

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3367998

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