NEST

NEST predicts gene essentiality by integrating protein interaction networks with genomic and epigenomic datasets, including gene expression profiles, CRISPR and shRNA screen results, ChIP-seq histone marks, and tumor profiling to prioritize survival indicator and functional genomic target genes.

Key Features:

• Integration of Protein Interaction Networks: Maps genes onto protein interaction networks to use network topology as a framework for essentiality prediction.
• Integration of CRISPR and shRNA Screen Data: Incorporates CRISPR and shRNA screen results to refine predictions of genes critical for cell viability.
• Use of Network Neighbor Information: Leverages information from network neighbors to improve prioritization of ChIP-seq target genes and survival indicator genes from tumor profiling.
• Combination with Gene Expression and Histone Marks: Integrates gene expression profiles and ChIP-seq histone mark data with network context to enhance functional genomics analyses.

Scientific Applications:

• Gene Essentiality Analysis: Identification and prioritization of genes that are crucial for cell survival and function.
• Prioritization of Genomic Targets: Prioritization of ChIP-seq target genes and survival indicator genes from tumor profiling studies.
• Interpretation of Functional Screens: Improved interpretation and reliability of CRISPR and shRNA screen results through network-informed integration.

Methodology:

Maps genes onto protein interaction networks and integrates CRISPR/shRNA screen data, gene expression profiles, ChIP-seq histone marks, and tumor profiling; analyzes network neighbor relationships, interactions, and expression patterns to predict gene essentiality.