Research and development work in the life sciences fields can yield a large amount of data that can be difficult to consolidate and analyze for specific insights, says Ted Slater, a solutions architect at YarcData.
Slater said Tuesday that for such a data environment, using traditional knowledge management tools such as relational databases could be inconvenient as they require a set of queries to extract insights from data,
In his video blog, he talks about graph analytics as an alternative solution, with nodes representing concepts and edges representing the relationship between concepts.
YarcData’s Urika graph analytics appliance works to relate huge data sets from different sources and simplify complex algorithms such as those in next-generation sequencing.
Slater says the the resulting insights from an NGS data set could help gain more information on diseases and develop treatments for particular patients.
He will present Bio-IT World Conference & Expo on YarcData systems’ application in the life sciences.