相关实验视频

Updated: Jun 21, 2026

A Strategy for Sensitive, Large Scale Quantitative Metabolomics
14:18

A Strategy for Sensitive, Large Scale Quantitative Metabolomics

Published on: May 27, 2014

21.6K

DPM:一个深度学习和最佳运输框架,用于成本效益的空间代谢学.

Bo Yao1, Longfeng Yang1, Chi Zhang1

  • 1State Key Laboratory of Cellular Stress Biology, State Key Laboratory of Vaccines for Infectious Diseases, Xiang'An Biomedicine Laboratory, School of Life Sciences, Faculty of Medicine and Life Sciences, National Institute for Data Science in Health and Medicine, XMU-HBN skin biomedical research center, Xiamen University, Xiamen, Fujian 361102, China.

Analytical chemistry
|January 15, 2026
PubMed
概括

DeepPathMetabol (DPM) 使用深度学习来从相邻的数据中预测质谱成像 (MSI) 部分的代谢物分布. 这种具有成本效益的方法提高了空间代谢学研究的MSI分辨率和准确性.

更多相关视频

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis07:11

Author Spotlight: Emerging Technologies and Advanced Tools for Decoding Metabolomics Data Analysis

Published on: November 10, 2023

3.2K
Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches09:47

Author Spotlight: Advancing Alzheimer's Research – Exploring Early Detection and Multi-Omics Approaches

Published on: December 15, 2023

1.7K

相关概念视频

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models01:06

Model Approaches for Pharmacokinetic Data: Distributed Parameter Models

Pharmacokinetic models are mathematical constructs that represent and predict the time course of drug concentrations in the body, providing meaningful pharmacokinetic parameters. These models are categorized into compartment, physiological, and distributed parameter models.
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...