CrossCheck

CrossCheck facilitates comparison of user-provided gene lists against a curated, searchable database of 16,231 published high-throughput screening datasets to aid biological interpretation.

Key Features:

• Published dataset collection: A curated repository of 16,231 datasets including genome-wide RNAi and CRISPR screens, interactome proteomics and phosphoproteomics screens, cancer mutation databases, and low-throughput studies of kinases, E3 ubiquitin ligases, and phosphatases.
• Gene ontology integration: Incorporates Gene Ontology annotations to contextualize gene lists within biological processes and pathways.
• Predicted protein kinase substrates: Contains a database of predicted kinase substrates generated via proteome-wide consensus motif searches.
• Comparative analysis of gene lists: Enables comparison of input gene lists against the curated collection to identify overlaps and relevant hits.
• Aggregation and organization: Aggregates and organizes published HTS datasets into a searchable structure for cross-referencing analyses.

Scientific Applications:

• Hit validation and interpretation: Cross-references HTS-derived gene lists against published datasets to validate and interpret screening hits.
• Hypothesis generation: Identifies overlaps with prior studies and predicted kinase–substrate relationships to support data-driven hypothesis generation.
• Kinase signaling analysis: Leverages predicted protein kinase substrates and phosphoproteomics data to investigate kinase–substrate interactions and signaling pathways.
• Integrative genomics and proteomics: Contextualizes findings across genomics, proteomics, and cancer mutation datasets for studies in cancer biology and cell signaling.

Methodology:

Aggregates and organizes published HTS datasets into a searchable database; performs comparative analyses of input gene lists against the curated collection; generates predicted protein kinase substrates using proteome-wide consensus motif searches.