ConTour: Data-Driven Exploration of Multi-Relational Datasets for Drug Discovery.

ABSTRACT: Large scale data analysis is nowadays a crucial part of drug discovery. Biologists and chemists need to quickly explore and evaluate potentially effective yet safe compounds based on many datasets that are in relationship with each other. However, there is a lack of tools that support them in these processes. To remedy this, we developed ConTour, an interactive visual analytics technique that enables the exploration of these complex, multi-relational datasets. At its core ConTour lists all items of each dataset in a column. Relationships between the columns are revealed through interaction: selecting one or multiple items in one column highlights and re-sorts the items in other columns. Filters based on relationships enable drilling down into the large data space. To identify interesting i

SUBMITTER: Partl C 

PROVIDER: S-EPMC4720990 | biostudies-literature | 2014 Dec

REPOSITORIES: biostudies-literature