A CLUSTERING-BASED TOPIC MODEL USING WORD NETWORKS AND WORD EMBEDDINGS

Abstract Online social networking services like Twitter are frequently used for discussions on numerous topics of interest, which range from mainstream and popular topics (e.g., music and movies) to niche and specialized topics (e.g., politics).Due to the popularity of such services, it is a challenging task to automatically model and determine the

In vitro differentiation of donor blood monocytes to macrophages (Mph) following GM-CSF treatment was accompanied by a significant increase in the levels of gene transcription signaling receptors TLR7 or RIG1.The levels of intracellular viral Swivel Glider RNA (M1 gene) in Mph remained high upon infection by influenza virus A H1N1pdm (Moscow 2009)