Abstract

Patrick Lewis Title: Automatic chemical analysis – Semantic analysis of online chemical literature Abstract: With recent advancements in natural language processing, novel language models have been able to learn and manipulate rather subtle semantic relationships. Is it possible to apply and adapt these models to learn chemical concepts by training on freely available chemical data online? What kind of concepts can we represent and what new kinds of literature analysis can we harness?

Dr Nitin Sharma Title: Investigating mode of action of fraction of Cynara Scolymus extract as anti- mesothelioma agent Abstract: Malignant pleural mesothelioma is an aggressive cancer with no current dedicated therapy. Historically, traditional medicines have been used to treat several diseases as they can target multiple pathways without causing high-level toxicity, thus representing an option for novel indications. However, mode of action (MoA) remains elusive for most natural compounds, which in addition often are applied as complex mixtures. In this study RNA -seq data along with ligand-based predictions was used to deduce the MoA of Cynara scolymus leaf extract (ABO1) against mesothelioma, in order to make one step forward towards its application in therapy.