Abstract Knowledge of the underpinnings of cancer initiation, progression and metastasis
has increased exponentially in recent years. Advanced “omics” coupled with machine …

Predicting the sensitivity of tumors to specific anti-cancer treatments is a challenge of
paramount importance for precision medicine. Machine learning (ML) algorithms can be …

The Cellosaurus is a knowledge resource on cell lines. It aims to describe all cell lines used
in biomedical research. Its scope encompasses both vertebrates and invertebrates …

There are only a few platforms that integrate multiple omics data types, bioinformatics tools,
and interfaces for integrative analyses and visualization that do not require programming …

Pharmacologic perturbation projects, such as Connectivity Map (CMap) and Library of
Integrated Network-based Cellular Signatures (LINCS), have produced many perturbed …

Drug repurposing is an unconventional drug discovery approach to explore new therapeutic
benefits of existing, shelved and the drugs in clinical trials. This approach is currently …

Signal transduction governs cellular behavior, and its dysregulation often leads to human
disease. To understand this process, we can use network models based on prior …

Millions of transcriptome samples were generated by the Library of Integrated Network-
based Cellular Signatures (LINCS) program. When these data are processed into …

Abstract The Library of Integrated Network-Based Cellular Signatures (LINCS) is an NIH
Common Fund program with the goal of generating a large-scale and comprehensive …

Recently, various computational methods have been proposed to find new therapeutic
applications of the existing drugs. The Multimodal Restricted Boltzmann Machine approach …