动态规划法在串联质谱肽段从头测序中的应用

GA-Novo: De Novo Peptide Sequencing via Tandem Mass Spectrometry using Genetic Algorithm

Proteomics is the large-scale analysis of the proteins. The common method for identifying proteins and characterising their amino acid sequences is to digest the proteins into peptides, analyse the peptides using mass spectrometry and assign the resulting tandem mass spectra (MS/MS) to peptides using database search tools. However, database search algorithms are highly dependent on a reference protein database and they cannot identify peptides and proteins not included in the database. Therefore, de novo sequencing algorithms are developed to overcome the problem by directly reconstructing the…

预测前潜在插补：从头肽测序的新计算范式

Latent Imputation before Prediction: A New Computational Paradigm for De Novo Peptide Sequencing

提出LIPNovo范式，在预测前于潜在空间插补缺失碎裂信息，以集合预测和最优二分匹配提升从头肽测序性能，实验大幅超越现有方法。

MassChroQ：质谱定量的多功能工具

MassChroQ: A versatile tool for mass spectrometry quantification

最近，已经开发了许多软件工具来在LC-MS分析中进行定量。然而，它们中的大多数是特定于定量策略（例如无标记或同位素标记）或质谱系统（例如高或低分辨率）。在这种情况下，我们开发了MassChroQ，这是一种多功能软件，可通过提取离子色谱图的峰面积积分进行LC-MS数据比对和肽定量。MassChroQ适用于标记或不标记的定量，并且不限于高分辨率系统。感兴趣的肽（例如所有鉴定的肽）可以通过提供目标m/z和保留时间值来自动或手动测定。它可以处理包括蛋白质或肽分级分离（如SDS-PAGE，2D-LC）的大型实验。它是完全可配置的。每个处理步骤都是可追溯的，产生的数据是开放的标准格式，其模块化允许轻松集成到蛋白质组学管道中。输出结果可用于统计分析。MassChroQ对从低分辨率和高分辨率质谱仪获得的复杂无标记数据的评估显示技术再现性的CV较低（1.4%），与蛋白质量的相关系数较高（0.98）。MassChroQ在GNU通用公共许可证v3.0下可在http://pappso.inra.fr/bioinfo/masschroq/免费获得。

A Structured Hardware Software Architecture for Peptide Based Diagnosis of Baylisascaris Procyonis Infection (ICIAfS14)

The problem of inferring proteins from complex peptide cocktails (digestion products of biological samples) in shotgun proteomic workflow sets extreme demands on computational resources in respect of the required very high processing throughputs, rapid processing rates and reliability of results. This is exacerbated by the fact that, in general, a given protein cannot be defined by a fixed sequence of amino acids due to the existence of splice variants and isoforms of that protein. Therefore, the problem of protein inference could be considered as one of identifying sequences of amino acids wi…

Protein identification with deep learning: from abc to xyz

Proteins are the main workhorses of biological functions in a cell, a tissue, or an organism. Identification and quantification of proteins in a given sample, e.g. a cell type under normal/disease conditions, are fundamental tasks for the understanding of human health and disease. In this paper, we present DeepNovo, a deep learning-based tool to address the problem of protein identification from tandem mass spectrometry data. The idea was first proposed in the context of de novo peptide sequencing [1] in which convolutional neural networks and recurrent neural networks were applied to predict …

D-Flow：多模态流匹配用于D-肽设计

D-Flow: Multi-modality Flow Matching for D-peptide Design

D-Flow通过多模态流匹配方法，结合结构表示和蛋白质语言模型，提升D-肽设计的生成能力，实现从通用蛋白设计到靶向结合体设计的转变，实验结果表明其在PepMerge基准测试中表现优异。