讲座资讯

PEAKS 培训课:AI模型在高通量蛋白质组学中的应用

2025-09-15     来源:本站     点击次数:76

BSI 专注于蛋白质组学与生物药领域,依托机器学习与先进算法开发世界领先的质谱数据分析软件,助力加速生物学研究与药物研发进程。

我们有幸受邀于10月10-11日承办PEAKS Training Workshop,为您带来深度、前沿的专业培训,带您走进深度蛋白质组学的世界!欢迎各位老师的参与!

会议注册地址:http://aohupo2025.com/register 

(注册时请选择 PEAKS Online Training)

BSI, dedicated to proteomics and biopharmaceuticals, provides world-leading mass spectrometry data analysis software powered by machine learning and advanced algorithms to accelerate biological research and drug discovery.

We are honored to be invited to host the PEAKS Training Workshop on October 10–11, delivering in-depth, cutting-edge training to take you into the world of Deep Proteomics! We warmly welcome your participation!

Registered address:http://aohupo2025.com/register  
(Remember to Choose PEAKS OnlineTraining)


Introduction
在过去的几年中,大规模的蛋白质组学研究使我们能够开始在蛋白质水平上了解表型。与人类基因组中大约 20,000 个蛋白质编码基因相比,人体内有超过 100,000 种不同的蛋白质,并且由于可变剪接以及转录后和翻译后加工,还存在数十万种 proteoform。多个课题研究表明蛋白质形态比其相应的蛋白质更好地描述蛋白质水平的生物学并且是更具体的分化指标。人工智能(AI)模型的赋能带来了高通量蛋白质组学的革命。

本次为期两天的 PEAKS 培训课程,将介绍 AI 模型在高通量蛋白质组学中的应用;展示如何针对多种互补的质谱方法,结合数据库搜索和从头测序的数据分析,达到在proteoform水平上的深度覆盖。无论是对于刚刚进入AI赋能的蛋白质组领域的新手,还是有经验的大队列样本的蛋白质组学研究,都非常适合参加这个培训。
Over the past few years, large scale proteomics efforts have allowed us to begin to understand phenotype at a protein level. In contrast to about 20,000 protein coding genes in the human genome, there are over 100,000 different proteins and, as a result of alternative splicing, hundreds of thousands of protein isoforms (variants) in the human body. However, proteins function in the context of modifications that include alternative splicing and posttranscriptional and posttranslational processing. Proteoforms better describe protein-level biology and are more specific indicators of differentiation than their corresponding proteins. It comes the revolution in highthroughput proteomics with artificial intelligence (AI) models.
 In PEAKS Online training workshop, we are going to introduce AI models for high throughput proteomics with deep coverage at proteoform level, by integrate alternative MS approaches with complementary database search and de novo sequencing data analysis. This training is highly suitable for both newcomers who have just entered the AI empowered proteomics field and experienced researchers engaged in proteomics studies of large cohort samples.


# 基于深度学习的从头测序与数据库搜索:助力深度、高通量蛋白质组学研究  Deep learning-based de novo sequencing and database search for in-depth and high-throughput proteomics

整合数据库搜索与从头测序技术,并结合多种酶解策略,可实现蛋白质组的深度覆盖。覆盖度可达到1.5万个蛋白组中的100万条独特肽段,平均序列覆盖率约为80%。

Integrating database search and de novo sequencing and combining multiple enzyme digests facilitated deeper proteome coverage up to a million unique peptides from 15,000 protein groups, with a median sequence coverage of approximately 80%.

# 高可信度翻译后修饰(PTM)与序列变异分析  Confident PTM and Sequence Variants Profiling

借助基于人工智能驱动的评分模型,PEAKS在鉴定翻译后修饰(PTM)与序列变异时可实现超高可信度,有效解决了在低丰度修饰或序列变异检测中常见的灵敏度与准确性问题。

Leveraging AI-powered scoring models, PEAKS achieves ultra-high confidence in identifying post-translational modifications (PTMs) and sequence variants, addressing the common issue of sensitivity and accuracy in low-abundance modification or variant detection.

#多组学驱动的高准确度、高灵敏度免疫肽组分析  Multi-omics enabled immunopeptidome with higher accuracy and sensitivity
将LC-MS/MS数据与下一代测序(NGS)结果相结合,PEAKS 可实现全面的免疫肽组分析, 突破单一技术手段的局限,确保精准鉴定主要组织相容性复合体(MHC)结合肽,为癌症免疫治疗研究提供支持。

Integrating LC-MS/MS data with next-generation sequencing (NGS) results, PEAKS enables comprehensive immunopeptidome profiling—overcoming the limitation of single-technology approaches and ensuring accurate identification of MHC-bound peptides for cancer immunotherapy research.

#基于DIA的高效蛋白质组学工作流程  Stream-lined Proteomics Proteomics Workflow with DIA
谱图库搜索与序列库搜索是DIA数据分析的两大核心方法。借助优化后的从头测序技术,PEAKS DIA 数据分析可实现蛋白质组的深度覆盖。
Spectral library search and library-free search are the two major approaches for DIA data analysis. Enhanced by de novo sequencing, PEAKS DIA data analysis provides you deep coverage.
#利用 PEAKS 从 DIA 数据中挖掘肽组与蛋白质组“暗物质”  Uncover dark peptidome/proteome from DIA data with PEAKS

除谱图库搜索与直接数据库搜索外,我们提出一种新型计算方法,可直接从复杂 DIA图谱中鉴定肽序列变异体与新肽段,同时严格控制假发现率(FDR)。

In addition to library search and direct database search, we present a novel computational method to identify peptide sequence variants and novel peptides directly and solely from complex DIA spectra while rigorously controlling the false discovery rate.

#结合Intact,Top-Down与Bottom-Up技术的深度Proteoform分析  Deep Proteoform Profiling with Intact, Top-Down and Bottom-Up

通过整合Intact、Top-Down(TD),与Bottom-Up(BU)技术,PEAKS可实现全面的Proteoform表征(包括亚型、翻译后修饰组合),这一突破解决了单一方法工具无法充分解析蛋白质组复杂性的难题。

By integrating intact protein analysis, Top-Down (TD), and Bottom-Up (BU) approaches, PEAKS enables comprehensive proteoform characterization (including isoforms, PTM combinations)—a breakthrough for understanding proteome complexity that single-method tools cannot achieve.

#PEAKS GlycanFinder 实操演示 — 具有结构分辨率的糖谱学分析  PEAKS GlycanFinder Walkthrough - Glycan Profiling with Structural
与只能检测糖基是否存在的通用工具不同,GlycanFinder 可实现糖链结构解析(如连接方式、分支结构),解决了在糖蛋白组学研究中表征复杂糖链结构的关键挑战。
Unlike generic tools that only detect glycan presence, GlycanFinder provides structural-level resolution of glycans (e.g., linkage, branching), solving the key challenge of characterizing complex glycan structures in glycoproteomics research.

#基于云服务器的大规模队列蛋白质组学扩展分析  Cloud-based scalable data analysis of large cohort proteomics.
PEAKS Online 云平台可实现大规模队列项目的自动化分析,支持深度蛋白质组学与蛋白质基因组学分析,并能满足发现型与靶向型质谱技术的分析通量需求。

PEAKS Online enables the automation of large-scale cohort project with in-depth proteomics and proteogenomics analyses and throughput of discovery and targeted mass-spectrometry-based technologies.

#蛋白质从头测序  Protein de novo Sequencing


 
作为生物信息学的领军企业,BSI专注于蛋白质组学和生物药领域,通过机器学习和先进算法提供世界领先的质谱数据分析软件和蛋白质组学服务解决方案,以推进生物学研究和药物发现。我们通过基于AI的计算方案,为您提供对蛋白质组学、基因组学和医学的卓越洞见。旗下著名的PEAKS®️系列软件在全世界拥有数千家学术和工业用户,包括:PEAKS®️ Studio,PEAKS®️ Online,PEAKS®️ GlycanFinder, PEAKS®️ AB,,ProteoformXTM ,DeepImmu®️免疫肽组发现服务和抗体综合表征服务等。Email:  sales-china@bioinfor.com  电话:021-60919891
相关资讯 更多 >