CTD2 Network Analytical Tools

An algorithm for inferring direct regulatory relationships between transcriptional regulator proteins and target genes.

A computational method designed to analyze phenotypic readouts from multiple-sample RNAi screens in which each gene is targeted by multiple RNAi reagents.

A resource of compound sensitivity data (concentration-response curves) that can be mined to develop insights into small-molecule mechanisms of action and novel therapeutic hypotheses.

A web resource for exploring, visualizing, and analyzing complex multidimensional cancer genomics datasets.

DCB supports a variety of resources that are available to scientists studying cancer to aid them in their research.

A computational method for inferring gene essentiality from genome-wide CRISPR-Cas9 screens in cancer cell lines to correct the copy number effect.

A tool that allows users to visualize networks and related information derived from complex datasets.

A computation method that estimates gene dependencies by integrating data from large-scale RNAi screens with read-out of cell viabilities performed in cancer cell lines.

A comprehensive preclinical reference portal that connects tumor features with genetic and small molecule dependencies.

An algorithm that elucidates mechanisms of action of cellular perturbations by analyzing network dysregulations.

A software package that integrates patient-matched genomic mutation and gene expression data with corresponding gene regulatory networks to identify candidate driver mutations that are upstream of master regulators and drive cellular phenotypes.

Software code that models gene-centric dependencies when integrating genomic alterations data of the same gene from different platforms to prioritize genes supported by multiple inputs.

An open source bioinformatics application that provides access to an integrated suite of tools for the analysis and visualization of data from a wide range of genomic domains.

An algorithm that can be used to identify transcription factors that control the transition between two cellular phenotypes.

An algorithm to identify hyper and hypomethylated genes for a disease.

A computational method which ranks known protein-protein interactions (PPIs).

A bioinformatic approach that integrates multi-omic cancer patient data with pharmacogenomic data from cell lines.

An algorithm for the genome-wide discovery of modulators of transcriptional interactions.

A platform to facilitate discovery of new mechanisms to control tumorigenesis through the integration of genomic, pharmacological, clinical, and structural data with the network of cancer-associated protein-protein interactions experimentally detected in cancer cells.

A web-based platform to access and discover data integrated from public pathway and interactions databases.

Software that predicts driver mutations by integrating genome-wide mRNA/protein expression levels, evolutionary and structural properties of mutations characterized by functional impact scores.

An algorithm that measures gene-level activity to assess the effect of high-throughput RNAi or CRISPR screens through Bayesian hierarchical modeling.

A bioinformatic method for visualizing and analyzing high-throughput single-cell gene expression datasets.

A statistical tool designed to perform allele-specific, tumor-deconvoluted transcriptome-exome integration of the bulk whole exome (WES) and whole transcriptome sequencing (WTS) data obtained from autologous patient tissue samples.

A web and mobile interface for identifying clinical – genomic driver associations.

A comprehensive resource for accessing, visualizing, and analyzing cancer functional proteomics.

An algorithm that allows computational inference of protein activity on an individual sample from the gene expression data.