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DIA-BERT

DIA-BERT is user-friendly Graphical User Interface (GUI) that leverages a transformer based pre-trained artificial intelligence (AI) model for the analysis of data-independent acquisition (DIA) proteomics. Over 276 million of high-quality training samples from real MS files were used for identification model and 34 million of training samples from synthetic MS files were used for quantification model. The tool is well-suited for multi-species datasets, particularly human proteomes. The output of DIA-BERT is provided as summarized tables in CSV format.

This software is currently under development, and we welcome you to try it out. If you have any feedback or suggestions, please let us know.
Email address: liuzhiwei@westlake.edu.cn; guotiannan@westlake.edu.cn.
You can also create an issue on the GitHub page:https://github.com/guomics-lab/DIA-BERT

Core Features

AI driven

Adopting advanced transformer models to provide accurate proteomic analysis results

High quality data

Based on massive real and simulated mass spectrometry data training, ensure the reliability of analysis results

Friendly interface

Intuitive graphical user interface makes complex analysis processes simple and easy to use

Technical specifications

Training sample size

Over 276 million real samples

Quantitative sample

Over 34 million synthetic samples

Format output

CSV format summary table

Application scenarios

Multi species dataset analysis

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