Sentence examples for entity activity from inspiring English sources

Black boxes, question marks, and filler-terms (such as "activate", "cause", or "inhibitor") hold the place for some entity, activity or process yet to be discovered.

In our approach, known entity activities represent entity co-occurrences in the textual collection.

The Activity Flow (AF) language allows scientists to represent influence diagrams, in which entity activities inhibit or stimulate other entity activities.

This makes it possible to rank all entity activities in the network.

We have extended the VSM with a transitive closure approach in order to predict new potential biological entity activities.

Moreover, we have used the similarity values derived from the VSM to rank the new discovered entity activities.

In this work, our objective is to present a model that employs the VSM in order to identify biological entity activities from a textual collection.

The algebraic framework of the VSM has demonstrated to be a helpful tool in the task of finding known biological entity activities.

These achievements often describe biological entity activities and have been published around the world aiming to assist, increase and speed up the number of discoveries in life sciences.

We have been able to achieve significant results in a strategy that combines the VSM with an inference process in order to predict new biological entity activities.

We have created a model to construct networks of entity interactions from the biological literature with the objective of finding known and new entity activities in a biological system.