Displaying Labeled Quantitative Data

Displaying Bivariate Data

Numerical techniques are too often designed to yield specific answers to rigidly defined questions. Graphical techniques are less confining. They aid in understanding the numerous relationships reflected in the data. They help reveal the existence of peculiar looking observations or subsets of the data. It is difficult to obtain similar information from numerical procedures. In this article, by...

Data for chicken semen proteome and label free quantitative analyses displaying sperm quality biomarkers

Understanding of biology of the avian male gamete is essential to improve the conservation of genetic resources and performances in farming. In this study, the semen proteome of the main domestic avian species (Gallus gallus) and evaluation of the molecular phenotype related to sperm quality were investigated using GeLC-MS/MS approach and label-free quantitative proteomic based on Spectral Coun...

Reviving Deuterium - Labeled Tags for Quantitative Proteomics

O18Quant: A Semiautomatic Strategy for Quantitative Analysis of High-Resolution 16O/18O Labeled Data

Proteolytic (18)O-labeling has been widely used in quantitative proteomics since it can uniformly label all peptides from different kinds of proteins. There have been multiple algorithms and tools developed over the last few years to analyze high-resolution proteolytic (16)O/(18)O labeled mass spectra. We have developed a software package, O18Quant, which addresses two major issues in the previ...

Normalization of microarray data: single-labeled and dual-labeled arrays.

DNA microarray is a powerful tool for high-throughput analysis of biological systems. Various computational tools have been created to facilitate the analysis of the large volume of data produced in DNA microarray experiments. Normalization is a critical step for obtaining data that are reliable and usable for subsequent analysis such as identification of differentially expressed genes and clus...