Results 11 to 20 of about 1,292,086 (235)

Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes

open access: yesGenome Biology, 2002
BackgroundGene-expression analysis is increasingly important in biological research, with real-time reverse transcription PCR (RT-PCR) becoming the method of choice for high-throughput and accurate expression profiling of selected genes.
J. Vandesompele   +6 more
semanticscholar   +1 more source

Accurate Proteome-wide Label-free Quantification by Delayed Normalization and Maximal Peptide Ratio Extraction, Termed MaxLFQ *

open access: yesMolecular & Cellular Proteomics, 2014
Protein quantification without isotopic labels has been a long-standing interest in the proteomics field. However, accurate and robust proteome-wide quantification with label-free approaches remains a challenge. We developed a new intensity determination
J. Cox   +5 more
semanticscholar   +1 more source

Normalization Techniques in Training DNNs: Methodology, Analysis and Application [PDF]

open access: yesIEEE Transactions on Pattern Analysis and Machine Intelligence, 2020
Normalization techniques are essential for accelerating the training and improving the generalization of deep neural networks (DNNs), and have successfully been used in various applications. This paper reviews and comments on the past, present and future
Lei Huang   +5 more
semanticscholar   +1 more source

Normalization of Real-Time Quantitative Reverse Transcription-PCR Data: A Model-Based Variance Estimation Approach to Identify Genes Suited for Normalization, Applied to Bladder and Colon Cancer Data Sets

open access: yesCancer Research, 2004
Accurate normalization is an absolute prerequisite for correct measurement of gene expression. For quantitative real-time reverse transcription-PCR (RT-PCR), the most commonly used normalization strategy involves standardization to a single ...
C. Andersen, J. L. Jensen, T. Ørntoft
semanticscholar   +1 more source

Teaching Normal Birth, Normally [PDF]

open access: yesJournal of Perinatal Education, 2009
Teaching normal-birth Lamaze classes normally involves considering the qualities that make birth normal and structuring classes to embrace those qualities. In this column, teaching strategies are suggested for classes that unfold naturally, free from unnecessary interventions.
openaire   +2 more sources

Are Children “Normal”? [PDF]

open access: yesReview of Economics and Statistics, 2008
We examine Becker's (1960) contention that children are "normal." For the cross section of non-Hispanic white married couples in the U.S., we show that when we restrict comparisons to similarly-educated women living in similarly-expensive locations, completed fertility is positively correlated with the husband's income.
Black, Dan A.   +3 more
openaire   +9 more sources

A Strong Baseline and Batch Normalization Neck for Deep Person Re-Identification [PDF]

open access: yesIEEE transactions on multimedia, 2019
This study proposes a simple but strong baseline for deep person re-identification (ReID). Deep person ReID has achieved great progress and high performance in recent years.
Hao Luo   +6 more
semanticscholar   +1 more source

Normalizers of system normalizers [PDF]

open access: yesTransactions of the American Mathematical Society, 1964
1. The normalizers of the system normalizers are subgroups of some importance in the theory of solvable groups initiated by P. Hall [1-5]. For example, P. Hall observed [4] that a system normalizer was contained in the hypercenter of its norm lizer. R.
openaire   +2 more sources

A scaling normalization method for differential expression analysis of RNA-seq data

open access: yesGenome Biology, 2010
The fine detail provided by sequencing-based transcriptome surveys suggests that RNA-seq is likely to become the platform of choice for interrogating steady state RNA.
Mark D. Robinson, Alicia Oshlack
semanticscholar   +1 more source

SEAN: Image Synthesis With Semantic Region-Adaptive Normalization [PDF]

open access: yesComputer Vision and Pattern Recognition, 2019
We propose semantic region-adaptive normalization (SEAN), a simple but effective building block for Generative Adversarial Networks conditioned on segmentation masks that describe the semantic regions in the desired output image. Using SEAN normalization,
Peihao Zhu   +3 more
semanticscholar   +1 more source

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