Integrating knowledge and omics to decipher mechanisms via large‐scale models of signaling networks
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 …
disease. To understand this process, we can use network models based on prior …
A cross-study analysis of drug response prediction in cancer cell lines
To enable personalized cancer treatment, machine learning models have been developed
to predict drug response as a function of tumor and drug features. However, most algorithm …
to predict drug response as a function of tumor and drug features. However, most algorithm …
Connecting omics signatures and revealing biological mechanisms with iLINCS
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 …
and interfaces for integrative analyses and visualization that do not require programming …
A survey of optimal strategy for signature-based drug repositioning and an application to liver cancer
Pharmacologic perturbation projects, such as Connectivity Map (CMap) and Library of
Integrated Network-based Cellular Signatures (LINCS), have produced many perturbed …
Integrated Network-based Cellular Signatures (LINCS), have produced many perturbed …
SigCom LINCS: data and metadata search engine for a million gene expression signatures
JE Evangelista, DJB Clarke, Z Xie… - Nucleic acids …, 2022 - academic.oup.com
Millions of transcriptome samples were generated by the Library of Integrated Network-
based Cellular Signatures (LINCS) program. When these data are processed into …
based Cellular Signatures (LINCS) program. When these data are processed into …
Validating small molecule chemical probes for biological discovery
V Vu, MM Szewczyk, DY Nie… - Annual review of …, 2022 - annualreviews.org
Small molecule chemical probes are valuable tools for interrogating protein biological
functions and relevance as a therapeutic target. Rigorous validation of chemical probe …
functions and relevance as a therapeutic target. Rigorous validation of chemical probe …
Drug target inference by mining transcriptional data using a novel graph convolutional network framework
F Zhong, X Wu, R Yang, X Li, D Wang, Z Fu, X Liu… - Protein & …, 2022 - academic.oup.com
ABSTRACT A fundamental challenge that arises in biomedicine is the need to characterize
compounds in a relevant cellular context in order to reveal potential on-target or off-target …
compounds in a relevant cellular context in order to reveal potential on-target or off-target …
Glutamine-fructose-6-phosphate transaminase 2 (GFPT2) Is upregulated in breast epithelial–mesenchymal transition and responds to oxidative stress
Q Wang, ST Karvelsson, A Kotronoulas… - Molecular & Cellular …, 2022 - ASBMB
Breast cancer cells that have undergone partial epithelial–mesenchymal transition (EMT)
are believed to be more invasive than cells that have completed EMT. To study metabolic …
are believed to be more invasive than cells that have completed EMT. To study metabolic …
Drug repositioning for cancer in the era of AI, big omics, and real-world data
R Wieder, N Adam - Critical Reviews in Oncology/Hematology, 2022 - Elsevier
Drug repositioning in cancer has been pursued for years because of slowing drug
development, increasing costs, and the availability of drugs licensed for other indications …
development, increasing costs, and the availability of drugs licensed for other indications …
Data considerations for predictive modeling applied to the discovery of bioactive natural products
Highlights•Natural products are an important source of therapeutic compounds.•Natural
product research can benefit greatly from advances in AI.•Knowledge integration is a limiting …
product research can benefit greatly from advances in AI.•Knowledge integration is a limiting …