Metabolomics FAQ

• • How Should Non-Normally Distributed Data Be Addressed in Univariate Statistical Analysis?

  In univariate statistical analysis, data normality is typically a key assumption underlying parametric testing. When data deviate from a normal distribution, several strategies can be employed to address this issue:   Applying Data Transformations Transformations such as logarithmic, square root, or Box-Cox can help approximate normality. Following transformation, the data's distribution should be reassessed for normality before proceeding with parametric analyses.   Employing Non-Parametric Tests If ......

• • How Can PLS Analysis Be Conducted in SIMCA-P?

  SIMCA-P is a professional statistical software that provides a user-friendly interface and robust analytical tools. Conducting Partial Least Squares (PLS) analysis using SIMCA-P involves the following steps:   1. Data Preparation (1) Data Format: Ensure that the dataset is imported in a format compatible with SIMCA-P, typically CSV or Excel. (2) Data Organization: Structure the dataset such that samples are arranged in rows and variables in columns. For instance, in metabolomics studies, each row corr......

• • How Can the Water Solubility of Bletilla Polysaccharides Be Improved After Vacuum Drying?

  The poor water solubility of Bletilla polysaccharides after vacuum drying may result from their molecular structure or physical alterations occurring during the drying process. Several strategies can be employed to enhance their solubility:   Physical Modification 1. Fine Grinding Reducing the particle size of polysaccharide powders increases their surface area, promoting faster dissolution.   2. Ultrasonic treatment Applying ultrasound can disrupt polysaccharide aggregates and enhance interactions wi......

• • What Are the Methods for Detecting Serum Metabolomics Indicators?

  Serum metabolomics is a field of study that investigates metabolic profiles by analyzing small-molecule metabolites in serum. This approach provides critical insights into biochemical processes and disease states. The primary detection indicators and analytical methods in serum metabolomics are outlined below.   Detection Indicators 1. Small-Molecule Metabolites Key metabolic components, including amino acids, fatty acids, carbohydrates, nucleotides, and vitamins.   2. Energy Metabolites Molecules inv......

• • How to Analyze and Present Non-Targeted Metabolomics Data Without a Control Group?

  If a study aims to investigate the composition of non-targeted metabolites without including a control group, the following analytical steps can be used to process and interpret the data:   Data Analysis Workflow 1. Data Preprocessing (1) Peak Detection and Integration: Utilize specialized software tools to detect and integrate peaks in mass spectrometry data, ensuring accurate metabolite signal extraction. (2) Signal Correction: Apply baseline correction, noise filtering, and normalization techniques......

• • What Are the Key Metabolomics Techniques and Their Distinctive Features?

  Metabolomics is the study of the comprehensive profile of metabolites in biological systems and their dynamic variations. Various analytical techniques are employed to detect and quantify metabolites in biological samples. Below are the major metabolomics techniques and their unique characteristics:   Characteristics of Nuclear Magnetic Resonance (NMR) Spectroscopy 1. Non-destructive method, suitable for analyzing live cells and tissues without compromising sample integrity. 2. Highly effective for st......

• • Is PLS-DA or OPLS-DA Generally Used to Evaluate Model Predictive Performance?

  When choosing between PLS-DA (Partial Least Squares Discriminant Analysis) and OPLS-DA (Orthogonal Partial Least Squares Discriminant Analysis) for evaluating a model’s predictive performance, one must consider the data characteristics and the specific research objectives. Both methods are employed for multivariate statistical analysis and are widely used in metabolomics and chemometrics; however, they exhibit key differences:   PLS-DA PLS-DA is a supervised learning method designed to build models th......

• • How Are Allosteric and Chemical Modification Regulations Demonstrated in Carbohydrate Metabolism?

  Allosteric regulation and chemical modification are two fundamental mechanisms governing enzyme activity in carbohydrate metabolism. These regulatory processes are essential for maintaining carbohydrate homeostasis in living organisms.   Allosteric regulation involves enzyme modulation at a site distinct from the active site. In this process, a regulatory molecule binds to an allosteric site, inducing conformational changes that alter enzyme activity. In glycolysis, phosphofructokinase-1 (PFK-1) serve......

• • What Are the Key Steps in DEAE Column Chromatography and Polysaccharide Purification?

  Key Steps in DEAE Column Chromatography 1. Column Preparation (1) Pack the DEAE resin into the chromatography column and equilibrate it using an appropriate buffer to establish a stable ionic environment. (2) Prepare the sample by dissolving or suspending it in a compatible buffer to maintain stability during separation.   2. Sample Application Carefully load the prepared sample onto the equilibrated DEAE column, allowing ionic interactions between the target molecules and the resin.   3. Removal of N......

• • How to Analyze Non-Targeted Metabolomics Results?

  Analyzing non-targeted metabolomics results is a complex process that involves a series of bioinformatics steps:   Data Preprocessing 1. Data Cleaning Remove noise and irrelevant information.   2. Peak Detection and Alignment Detect metabolite peaks and align them across samples.   3. Normalization and Standardization Eliminate variability caused by experimental conditions or instrument differences.   Feature Selection and Dimensionality Reduction: 1. Principal Component Analysis (PCA) Reduce data dim......