BioPlat

BioPlat facilitates discovery and in silico evaluation of prognostic and predictive cancer biomarkers from oligo-microarray and next-generation sequencing gene expression datasets.

Key Features:

• Data mining: Performs data mining across gene expression signature repositories to identify candidate biomarkers.
• Data extraction and preprocessing: Extracts and preprocesses gene expression data for downstream analysis.
• Filtering techniques: Applies filtering methods to refine datasets prior to signature derivation.
• Gene expression signature calculation: Calculates gene expression signatures to capture relevant gene patterns.
• In silico validation: Conducts in silico validation of identified biomarkers using follow-up datasets.
• Feature selection algorithms: Implements feature selection algorithms to pinpoint significant genes or markers.
• Annotation: Provides annotation functionalities to add biological context to genes and signatures.
• Integration and reuse of signatures: Integrates and reuses existing gene expression signatures within follow-up datasets.

Scientific Applications:

• Biomarker discovery: Identification of prognostic and predictive biomarkers from gene expression data.
• Biomarker validation: In silico validation and cross-dataset assessment of candidate biomarkers.
• High-throughput gene expression analysis: Analysis and comparison of large-scale oligo-microarray and next-generation sequencing datasets.
• Signature reuse and translational research: Reuse of existing gene expression signatures to assess robustness and translational applicability.

Methodology:

Computational methods explicitly include data mining, data extraction and preprocessing, filtering, gene expression signature calculation, feature selection algorithms, in silico validation, annotation, and integration/reuse of gene expression signatures.