XB BioIntegration Suite

Category Cross-Omics>Biomarker Discovery/Tools

Abstract The XB BioIntergration Suite™ (XB BIS) is a software product that has been designed by translational researchers for 'translational research' with integrated capabilities and features created to readily apply across the entire life science pipeline.

XB BIS represents a unique systems approach for a range of purposes including basic biomedical research, clinical diagnostics, and identifying new pharmacogenomic and pharmacogenetic strategies for the future.

XB BIS is a fully integrated bioinformatics solution that allows users to generate, refine, and validate causal hypotheses across disparate data sets.

XB BIS accelerates the translational research workflow by providing researchers with integrated functionality as part of the application.

The open architecture of XB BIS also allows integration with existing applications to further enhance the power and functionality of the system.

XB BIS features/capabilities include:

Capabilities --

Target Discovery & Validation - Identifying potential molecular attributes of disease as targets for drug development through the integrated longitudinal analysis of molecular, clinical, and biomedical data.

Validating suspected drug or biomarker targets through a series of analytical steps, utilizing in-house and public domain data.

Biomarker Discovery - Identifying molecular and/or phenotypic markers of disease to serve as diagnostic (predictive) tests for assessing a wide variety of clinical outcomes. Objective clinical response markers to ensure successful therapeutic delivery (accelerate clinical trials and dose/schedule modification).

Clinical Trial Support - Multi-directional management, analysis, and reporting of clinical and molecular data to support clinical trials.

Long-Term Clinical Monitoring - Exploring long-term molecular and clinical patterns based on long-term exposure and response to therapies as early indicators of potential toxicity or decreasing therapeutic response.

Drug Rescue - Analysis of existing clinical and molecular data captured for a failed drug with a focus on determining molecular and/or clinical attributes for definable patient populations with improved therapeutic response or limited toxicity profiles.

New Indications for Existing Therapeutics - Analysis of molecular and clinical data to identify potential novel uses of released drugs, alone or in combination with other agents.

Tailored Treatment Strategies/Personalized Medicine - Identification of optimal therapeutic treatments which may change over time based on a patient’s changing molecular and clinical attributes (personalized medicine).

Data Access & Management --

Integrated Data Store -

Integrate Biomedical & Molecular Data - Cellular, preclinical and clinical phenotypic data is directly integrated with molecular data generated from experiments performed on samples derived from a subject.

Extensible Data Store - Installations define their own set of attributes and fields to capture and maintain.

Time-Phased Data - Data is captured and analyzed longitudinally to support higher level trend analysis.

Industry Reference Molecular Data - Supports reference data for genes and proteins from various industry sources.

Tools to Manage the Data Store -

Dynamic Queries & Filters - Users search and navigate data based on conditions of any combination of data fields.

Reporting & Visualization - Generates canned and dynamic reports against any combination of attributes, including user-defined fields.

Provides interactive visualization of the data via Venn Diagrams and plots.

Grouping Support - Users define their own groups to be used for analysis. Groups can be defined from biomedical, experimental or molecular data using filters and during analysis session(s).

Import/Export - Data can be imported from and exported to flat files. Cohesive sets of user-defined fields are grouped into modules which form the data type template for importing and exporting.

Advanced Statistical Analysis & Research Engine -

Identifies Discriminators - Uses a variety of statistical analyses to identify discriminating data between groups. Discriminators can include a variety of molecular and/or biomedical data elements, and time- phased calculations.

Discriminator Lists - Users define discriminator lists which can be used as input for data set refinement supporting custom analysis.

Provides Multiple Algorithms - Supports a variety of statistical and data treatment methods and interactive data visualizations.

Searches Industry Publications - Provides an automated front end to public domain searches of discoveries, such as PubMed and US patent documents.

Molecular Pathway Mapping - Readily maps genes/proteins identified during analysis to ‘molecular networks’, allowing the user to identify key convergence/divergence points within pathways that may represent excellent therapeutic targets.

Hypothesis Generation - Defines a set of preliminary hypotheses, following initial analysis, for validation with further data analysis or exploration within the laboratory.

This capability enables the seamless, circular flow or laboratory experimentation to data analysis and back to laboratory experimentation again.

Diagnostic Reports - Diagnostic reporting tool to apply molecular and clinical diagnostic patterns for prospective diagnostic applications.

Detailed Data Filtering -

XB BIS allows filtering based on a wide variety of parameters. Filtering allows for simple review of data (e.g. evaluating the number of subjects within a category of interest). Filtering is also central in creating groups for analysis.

XB BIS follows a logical experimental flow in that subjects provide samples which are used for experiments. XB BIS associates all overlying data higher up in the database.

Types of Variables that can be filtered are by subject, samples, experiments, groups and molecular data.

XB BIS also allows filtering based on lists compiled from external data sources. For instance, a list of genes of interest by an XB BIS analysis can then be filtered against a list of genes that are known drug targets or filtered against a list of genes from a public data source containing data from a similar or related study.

Integrated Analysis Methods -

Mean Difference Tests - Student T Test; Paired Sample Test; Chi Square; and Mann Whitney.

Diagnostic Algorithms - Weighted Voting Diagnostic Correction; False Discovery Rate Correction; and Bonferri Correction (False Discovery Correction).

Data Normalization/Treatment - Mean/Medium Centering; Standardization (Conversion to Z Score); Log Transformation; and Ratio Conversion vs. Reference.

Molecular Data Filtering - Fold Change; Spot Quality; and Intensity.

ANOVA Analysis -

Analysis Visualizations - Hierarchical Clustering (Heat Maps); Multidimensional Scaling (MDS); and Discriminator Grid Review.

System Requirements

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Manufacturer

Manufacturer Web Site XB BioIntegration Suite

Price Contact manufacturer.

G6G Abstract Number 20357

G6G Manufacturer Number 104007