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资源简介：
iRT data split in two columns one for sequences and another for experimental retention time.
应用场景：
创建时间：
2021-12-13
相关数据集
A proteomics approach to the protein normalization problem
The approach suggested here can be used more widely to determine the suitability of proteins or sets of proteins as loading and normalization controls for any biological system. As we have shown here,
NIAID Data Ecosystem70
Additional file 10: Simulated Dataset 2. of ProteoModlR for functional proteomic analysis
Normalization_dataset_no_error. The file contains a simulated datasets with identical intensity values for all peptides in all conditions. This dataset is provided as a reference to evaluate the accur
NIAID Data Ecosystem50
RepoRT Meta-analysis
Overview This repository contains a Julia-based analytical pipeline for processing method and reported compound datasets imported from https://github.com/michaelwitting/RepoRT. File Registry Notebooks
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A Comparison of Three Liquid Chromatography (LC) Retention Time Prediction Models: Data Associated with Publication
Data associated with publication on A Comparison of Three Liquid Chromatography (LC) Retention Time Prediction Models. Publication DOI: https://doi.org/10.1016/j.talanta.2018.01.022
DataCite Commons2020-08-30 更新60
Prediction of Liquid Chromatographic Retention Times of Peptides Generated by Protease Digestion of the Escherichia coli Proteome Using Artificial Neural Networks
We developed a computational method to predict the retention times of peptides in HPLC using artificial neural networks (ANN). We performed stepwise multiple linear regressions and selected for ANN in
NIAID Data Ecosystem50
