Biostatistics and Bioinformatics

Let RayBiotech help you get the most out of your array data.

In order to understand how cellular activities are altered in different disease states, array data must be expertly analyzed in order to discover patterns and gain critical insights into these activities.

Introduction

Protein arrays represent a powerful technology which has opened a new arena of functional proteomics. When faced with a large magnitude of array data, one must apply comprehensive statistical and data mining analysis to discover potential biomarker panels and meaningful patterns. Biostatistical analysis can also help to evaluate the quality of protein expression data by detecting and extracting errors and confidence levels.

Our in-house team of biostatistics and bioinformatics experts can guide you through this process and tailor a customized computational solution for your antibody and protein array data. The cost of our consultation services will be provided on a per-project basis; hourly rates are also available.

Service Features

RayBio® Biostatistics and Bioinformatics Services include:

Pre-processing Service for Protein Array Data (if applicable or performed):

The pre-processing service is performed on raw array expression data to ensure high quality of the results. The processed array data form the foundation for all subsequent biostatistics and bioinformatics analysis, i.e., discriminatory protein analysis, data mining cluster analysis, pathway analysis, protein-protein interaction networking analysis.

Data storage and management for Protein Array studies
Data computation
Generation of spreadsheet with expression data for all samples
Data normalization and transformation
Data outliner detection
Data filtering
Written report include data expression data for all samples, filtered and transformed data, description of analysis steps performed and analysis summary.

Discriminatory Protein Marker Analysis Service(if applicable or performed):

Discriminatory protein marker analysis allows the detection of genes that show statistical difference between different groups. The minimum requirement is 10 samples from each group, for example, tumor and normal groups.

Determination of the top discriminatory proteins for the two groups of samples
t-test
ANOVA (Analysis of Variance)
Wilcoxon Rank Sum test
SAM(significance Analysis of Microarray)
Volcano Map

Data Mining Cluster Analysis Service (if applicable or performed)

Data mining cluster analysis allows the identification of groups of markers with similar expression profiles, and/or identification of a group of markers which can distinguish different groups and be used as potential biomarkers.

Cluster of all relevant proteins according to the similarity of their expression profiles
Hierarchical cluster analysis
Artificial Neural Network Analysis
K-Nearest Neighbor Analysis)
Split-Point Score Analysis
Assay Performance Analysis and ROC Analysis

Protein Pathway Analysis Service

The pathway analysis allows the conversion of processed array data into biologically meaningful results. Using Go and KEGG analysis, the service can provide biological protein annotation analysis and signaling pathway analysis.

Identification the biological meaning for protein clusters
Gene Ontology Analysis
KEGG analysis
Annotation of Proteins
Assignment of Proteins to Predetermined Categories
Annotation Enrichment Analysis
Signaling Network Analysis

Protein-Protein Interaction Networking Analysis Service

The Protein-Protein Interaction Database was built to integrate a gamut of biological/ bibliographical/ molecular data and build a framework which might help understanding how cells orchestrate their protein content in order to become what they are: machines with a purpose. This is based on the simple paradigm that functionality like signal cascades are held together in a close space, thereby allowing specific events to occur without the necessity of passive diffusion and random events. Our Protein-Protein Interaction Networking Analysis (PPI) allows the annotation of the PPI networking map via PPI data base and identification of key protein markers via comparison with literature reports.