Resources

Proteomics Databases



Metabolomics Databases

• • Gel Electrophoresis and Image Analysis

  Gel electrophoresis is a crucial technique for separating and analyzing biological macromolecules, widely used in proteomics and molecular biology research. This paper aims to introduce the basic principles, experimental procedures, and image analysis methods of gel electrophoresis, focusing on optimizing experimental conditions and improving data accuracy. This provides a comprehensive solution for researchers.

• • Advances in Proteomics

  Proteins are the direct executors of physiological functions, and studying their structure and function helps elucidate the mechanisms of changes under physiological or pathological conditions. Research on protein post-translational modifications, interactions, and conformations relies on direct protein studies. Therefore, a comprehensive understanding of life's complex activities necessitates studying proteins at a holistic, dynamic, and network level.

• • Sample Preparation and Proteomics Solutions

  Proteomics is the study of the overall structure and function of proteomes in living organisms. Sample preparation is a critical step in proteomics research, directly impacting the results of subsequent mass spectrometry (MS) analysis. This paper introduces the basic workflow and related solutions for proteomics sample preparation, aiming to provide effective methods and strategies for researchers.

• • Detection of Differentially Expressed Proteins Using Statistical Methods

  Detecting differentially expressed proteins (DEPs) is a fundamental task in modern proteomics research, particularly in the investigation of disease mechanisms and the discovery of biomarkers. To extract biologically meaningful DEPs from complex proteomic data, scientists employ various statistical methods to ensure the reliability and accuracy of their results.   Basic Workflow of Detecting Differentially Expressed Proteins The detection of DEPs typically involves comparing protein expression levels ......

• • Error Analysis in Proteomics Data Assessment

  With the continued advancement of technologies, acquiring proteomics data has become more efficient and accessible. However, due to the inherent complexity of proteomics data and the limitations of current technologies, errors can arise during data evaluation. These errors may affect the accuracy and reliability of experimental outcomes.   Sources of Error in Proteomics Data Evaluation 1. Sample Preparation Sample preparation is a critical foundational step in proteomics research, as it directly......

• • De Novo Peptide Sequencing by Deep Learning

  Deep learning, characterized by its ability to automatically extract meaningful features from complex data via deep neural network architectures, has been extensively applied in domains such as image recognition, natural language processing, and bioinformatics. In recent years, it has also been increasingly employed in peptide sequence analysis. Applications range from de novo sequencing and peptide function prediction to antigen epitope identification and MHC binding affinity estimation, consistently .....

• • How Do De Novo Sequencing and Homology Search Integrate in Analysis?

  In proteomics research, database-dependent search remains the dominant analytical strategy. However, its effectiveness hinges on the completeness and accuracy of reference databases. This reliance becomes a significant limitation when dealing with non-model organisms, natural products, antibody fragments, or variations at translation initiation sites, leading to potential omissions or incorrect identifications. To address this limitation, de novo sequencing offers a database-independent approach for .......

• • Next-Generation De Novo Sequencing Algorithms

  De Novo sequencing, defined as the de novo inference of peptide amino acid sequences, is a critical technique in proteomics for the identification of unknown proteins, post-translationally modified peptides, and antibody fragments. In contrast to database search-based approaches, De Novo sequencing operates independently of reference databases, rendering it particularly effective for complex scenarios such as non-model organisms, incomplete database coverage, post-translational modifications, and highly....

• • High-Accuracy Antibody Sequencing Using De Novo Techniques

  Introduction: Why is antibody sequencing becoming increasingly important Antibodies, as key effectors of the adaptive immune system, exhibit remarkable diversity and specificity that make them indispensable in basic research, diagnostic development, and biopharmaceutical applications. From the generation of monoclonal antibodies to the evaluation of novel vaccines and the elucidation of tumor immunotherapy mechanisms, acquiring complete antibody sequence information is a critical initial step. Convention...

• • Common Issues in De Novo Sequencing and How to Solve Them

  In proteomics and antibody-related studies, De Novo Sequencing has emerged as a powerful approach due to its independence from reference databases and its ability to reconstruct complete protein sequences. This capability makes it indispensable for applications such as antibody sequence characterization, ancient protein reconstruction, and novel antigen discovery—contexts where De Novo Sequencing is often the only viable solution. However, owing to its reliance on complex mass spectrometry data .......