Our mission is to develop and implement a comprehensive data strategy for our clients, from mining massive data sets and using predictive analytics to uncover business value to implementing cutting-edge deep learning to solve technical challenges. We rapidly close client capability gaps, increase the speed of organizations, and their ability to deliver their strategy.
We are a data science start-up with a mission to curate truths in biomedicine. By providing scientists with the necessary components to tackle biomedicine's biggest unanswered questions we aim to propel life sciences research into a new era of big data analysis. Our capabilities start with extraction, normalization or standardization, and integration of larger data sets semi-automatically. We have rich experience in dealing with diverse data types, which is key to handling the life sciences domain.
Analytics is the discovery and communication of meaningful patterns in data. It makes use of information technology, statistics and mathematical algorithms to develop knowledge, to quantify performance or to make predictions. It uses the insights gained from this process to recommend
action or to guide decision making. Analytics is best thought of as a research procedure for decision making, not simply as isolated tools or steps in a process.
One of the primary problems facing scientific research is the extraordinary growth in volume and velocity of new and updated data. There is a huge gap in moving data from the bench to analysis. Researchers spend more time finding and organizing data than they do in analysis and discovery!
The central challenge of biomedical data management is discovery. In other words, "does the data exist to answer <this> question?
- Semantic search across fully integrated data sets
- Well harmonized data, semantically classified via relevant ontologies
- Knowledge graphs and a powerful search to answer highly specific questions.