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Feature-specific quantile normalization and feature-specific mean–variance normalization deliver robust bi-directional classification and feature selection performance between microarray and RNAseq data
BackgroundCross-platform normalization seeks to minimize technological bias between microarray and RNAseq whole-transcriptome data. Incorporating...
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Evaluation of normalization strategies for GC-based metabolomics
IntroductionFor many samples studied by GC-based metabolomics applications, extensive sample preparation involving extraction followed by a two-step...
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Gene count normalization in single-cell imaging-based spatially resolved transcriptomics
BackgroundRecent advances in imaging-based spatially resolved transcriptomics (im-SRT) technologies now enable high-throughput profiling of targeted...
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Data normalization for addressing the challenges in the analysis of single-cell transcriptomic datasets
BackgroundNormalization is a critical step in the analysis of single-cell RNA-sequencing (scRNA-seq) datasets. Its main goal is to make gene counts...
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Internal and external normalization of nascent RNA sequencing run-on experiments
In experiments with significant perturbations to transcription, nascent RNA sequencing protocols are dependent on external spike-ins for reliable...
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An analysis of entity normalization evaluation biases in specialized domains
BackgroundEntity normalization is an important information extraction task which has recently gained attention, particularly in the...
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Cross-platform normalization enables machine learning model training on microarray and RNA-seq data simultaneously
Large compendia of gene expression data have proven valuable for the discovery of novel biological relationships. Historically, most available RNA...
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Cross-modal feature fusion Mask R-CNN and point cloud normalization segmentation transformation for fish length estimation
Automatic fish length estimation is essential for modern aquaculture. Occlusion and body bended make accurate fish length estimation challenging in...
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Titration-based normalization of antibody amount improves consistency of ChIP-seq experiments
Chromatin immunoprecipitation (ChIP) is an antibody-based approach that is frequently utilized in chromatin biology and epigenetics. The challenge in...
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Comprehensive evaluation and validation of optimal reference genes for normalization of qPCR data in different caprine tissues
BackgroundQuantitative real-time PCR (qPCR) is a highly reliable method for validating gene expression data in molecular studies due to its...
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Significant variation in the performance of DNA methylation predictors across data preprocessing and normalization strategies
BackgroundDNA methylation (DNAm)-based predictors hold great promise to serve as clinical tools for health interventions and disease management....
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Degree-Normalization Improves Random-Walk-Based Embedding Accuracy in PPI Graphs
Among the many proposed solutions in graph embedding, traditional random walk-based embedding methods have shown their promise in several fields....
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Normalization and de-noising of single-cell Hi-C data with BandNorm and scVI-3D
Single-cell high-throughput chromatin conformation capture methodologies (scHi-C) enable profiling of long-range genomic interactions. However, data...
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Normalization of gene expression data revisited: the three viewpoints of the transcriptome in human skeletal muscle undergoing load-induced hypertrophy and why they matter
BackgroundThe biological relevance and accuracy of gene expression data depend on the adequacy of data normalization. This is both due to its role in...
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MicroRNA qPCR normalization in Nile tilapia (Oreochromis niloticus): Effects of acute cold stress on potential reference targets
The Nile tilapia ( Oreochromis niloticus ) is one of the most important cultured fish worldwide, but tilapia culture is largely affected by low...
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Robust normalization and transformation techniques for constructing gene coexpression networks from RNA-seq data
BackgroundConstructing gene coexpression networks is a powerful approach for analyzing high-throughput gene expression data towards module...
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Metabolite quantification: A fluorescence-based method for urine sample normalization prior to 1H-NMR analysis
IntroductionMetabolomics is a multi-discipline approach to systems biology that provides a snapshot of the metabolic status of a cell, tissue, or...
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Evaluation of suitable qRT-PCR normalization genes for various citrus rootstocks
Citrus rootstock can modify plant growth and enhance stress resistance. There are many genotypes and species used as citrus rootstocks. Although...
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MUREN: a robust and multi-reference approach of RNA-seq transcript normalization
BackgroundNormalization of RNA-seq data aims at identifying biological expression differentiation between samples by removing the effects of unwanted...
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CHIPIN: ChIP-seq inter-sample normalization based on signal invariance across transcriptionally constant genes
BackgroundMultiple studies rely on ChIP-seq experiments to assess the effect of gene modulation and drug treatments on protein binding and chromatin...
