Detecting and analysing contrasts and contradictions in scientific texts is essential for suggesting further research potentials and discoveries. Finding contrasts and contradictions in text by means of automatic methods is a relatively new area in text mining. Specifically, most biological text mining research has so far focused on mining affirmative statements about the relations amongst entities, although it is of growing interest to find reports on weak or negative relations, or lack there of. Negation detection is a middle step to finding contrasts and contradictions, and has been of special interest in medical text mining, because of the abundance of negative patterns in medical descriptions. The aim of this research is to develop text mining methods to detect and analyse contrasting facts in the biomedical literature and specifically in molecular interactions.