INTREPPPID-an orthologue-informed quintuplet network for cross-species prediction of protein-protein interaction.

An overwhelming majority of protein-protein interaction (PPI) studies are conducted in a select few model organisms largely due to constraints in time and cost of the associated 'wet lab' experiments. In silico PPI inference methods are ideal tools to overcome these limitations, but often struggle with cross-species predictions. We present INTREPPPID, a method that incorporates orthology data using a new 'quintuplet' neural network, which is constructed with five parallel encoders with shared parameters.

RAPPPID: towards generalizable protein interaction prediction with AWD-LSTM twin networks.

Motivation: Computational methods for the prediction of protein-protein interactions (PPIs), while important tools for researchers, are plagued by challenges in generalizing to unseen proteins. Datasets used for modelling protein-protein predictions are particularly predisposed to information leakage and sampling biases.

Results: In this study, we introduce RAPPPID, a method for the Regularized Automatic Prediction of Protein-Protein Interactions using Deep Learning.

Multicellular detachment generates metastatic spheroids during intra-abdominal dissemination in epithelial ovarian cancer.

Ovarian cancer is the most lethal gynecological cancer, where survival rates have had modest improvement over the last 30 years. Metastasis of cancer cells is a major clinical problem, and patient mortality occurs when ovarian cancer cells spread beyond the confinement of ovaries. Disseminated ovarian cancer cells typically spread within the abdomen, where ascites accumulation aids in their transit.

Progressive polarity loss and luminal collapse disrupt tissue organization in carcinoma.

Epithelial cancers (carcinoma) account for 80%-90% of all cancers. The development of carcinoma is associated with disrupted epithelial organization and solid ductal structures. The mechanisms underlying the morphological development of carcinoma are poorly understood, but it is thought that loss of cell polarity is an early event.