by Michael Black Carcinogenesis, or the process of transformation of cells to a cancerous state, often is associated with aberrations in messenger RNA splicing. Removal of introns in pre-mRNA is an essential step in normal cell processing of mRNA prior to transcription of a peptide from a final mRNA transcript. Alternative splicing of pre-mRNA gives cells the ability to regulate multiple final mRNA products from a single gene, adding diversity to the …
Development of a Molecular Fingerprint for Predicting Drug-induced Cholestasis
Jake Reske, ScitoVation graduate intern in toxicogenomics, will explains a meta-analysis strategy used to develop a preliminary classifier of hepatic cholestasis through public transcriptomic data sets. Cholestasis is a hepatic disease that results from bile acid metabolic dysregulation. We describe our approach to using transcriptomics, statistical modeling, and machine learning to identify molecular signatures of cholestasis. What you’ll learn: Data-driven approaches to identify …
Toward an Actionable Collaborative Data System for Toxicology
Patrick McMullen, Director of Computational Toxicology I have often joked that as a computational biologist in an applied field that has been slow to embrace bioinformatics, it is my goal to work myself out of a job. That is, if I can empower the scientific experts responsible for safety decisions with the right tools, then they can ask their questions …
Using Short-term In Life Transcriptomic Studies to More Effectively Assess Dose Responses and Modes of Action
In the past, dose responses results from in life toxicology studies were used to estimate no observed effect levels (NOELs) and more recently benchmark doses (BMDs). These observational studies of apical endpoints were frequently followed up by mechanistic studies both in intact animals and in in vitro models to determine modes of action (MOAs) and lend support to using either linear or threshold-based low dose extrapolations. Over the past two decades, gene expression analysis …