A commonly used analysis method is principal component analysis (PCA, Principal Components Analysis) of trajectories. This method is sometimes called ED (essential dynamics) and aims to identify large-scale intensive motions of atoms, thereby revealing structural information hidden behind atomic fluctuations helps determine which modes of motion contribute the most to the overall dynamics of the protein. The goal of PCA is to describe the original data with new variables that are linear combinations of the original variables. This is also the main problem with PCA: it only uses linear relationships between atomic motions to explain the problem. CD BioSciences use computer-aided methods to provide biofilm conformational principal component analysis service to help customers complete biofilm related research.

Our Services

CD BioSciences provides one-stop biofilm conformational principal component analysis service of biofilm system. We offer a variety of methods and software to choose from to meet your research needs.

Why Do Principal Component Analysis?

• Principal component analysis can reduce the dimensionality of the data space under study.
• The conclusions about the factor loadings aij elucidate some of the relationships between the X variables.
• Principal component analysis can graphically represent multidimensional data.
• Principal component analysis can build regression models.

Specific Biofilm Conformational Principal Component Analysis Approaches We Offer

• Our first step in computing PCA is to construct the covariance matrix, which characterizes the degree of collinearity of the atomic motions between each pair of atoms. The covariance matrix is by definition a symmetric matrix.
• This matrix is then diagonalized to obtain a matrix of eigenvectors and a diagonal matrix of eigenvalues. Each eigenvector describes the intensive motion of the particle, and the vector value represents the degree to which the corresponding atom participates in the motion.
• Typically, most (>90%) motions in a system are described by less than 10 eigenvectors or principal components. The eigenvalues corresponding to the eigenvectors are equal to the sum of the fluctuations described by each atom in the intensive motion, It is a measure of the total motion associated with the eigenvectors and can be used to compare the variability of proteins under different conditions.

Provided by Clients

Please inform us of your specific biofilm conformational principal component analysis service details, and we can provide customized solutions for different projects.

Service Process

Our Features

Deliverables

1. Related experimental results raw data
2. Analysis results of PCA
3. Experimental report
4. Data analysis
5. Image and result analysis
6. Summary of relevant calculation parameters

Why Choose Us?

CD BioScience provides corresponding PCA analysis services. CD BioScienceis is committed to improving various biofilm related services. We are able to design and complete a set of services as solutions for themed projects. Please feel free to contact us for more detailed information, our scientists will tailor the most reasonable plan for your project.

• Biofilm Computational Construction Service
• Biofilm Molecular Dynamics Simulation Service
• Stability Test of Biofilm System
• RMSF Analysis of Biofilm System
• Gyration Radius Analysis of Biofilm System
• Binding Mode Analysis of Biofilm System
• Secondary Structure Analysis of Biofilm System
• Energy Analysis of Biofilm System
• Hydrophobic Interaction Analysis of Biofilm System
• Free Energy Landscape Analysis of Biofilm System
• Biofilm Ramachandran Plots Analysis
• Cluster Analysis of Biofilm System
• SAS Analysis Service of Biofilm System
• Energy Decomposition Analysis of Biofilm System
• Electrostatic Interaction Analysis of Biofilm System
• Biofilm Virtual Screening Service
• Computational Modeling of Early-Stage Biofilm Formation
• Biofilm CGMD Service
• Biofilm DPD Service
• Biofilm DEM Service
• Biofilm SPH Service
• Biofilm XFEM Service
• Other Biofilm MD Serivce
• Biofilm Homology Modeling Serivce
• Gram-negative Bacterial Outer Membrane Construction Service
• Biofilm Formation Simulation Service
• Construction Services for Discrete Difference Models
• Modeling Services for Geometric Heterogeneity in Biofilms
• Computational Simulation Service for Biofilm Development
• Computational Modeling Service for Synthetic Biofilms
• Biofilm MD Results Analysis Services
• Biofilm Multiscale Computational Modeling Service
• Biofilm Modeling Service