For most pharmaceutical companies, extracting insight from heterogeneous and ambiguous data remains a challenge. The era of data-driven R&D is motivating investment in technologies such as machine learning to provide deeper insights into new drug development strategies.
The quality of data directly impacts the accuracy and reliability of the results of computational approaches. However, the work required to achieve clean, high quality data can be costly, often prohibitively so, requiring data scientists to spend the majority of their time as ‘data janitors’, rather than actually analysing data.
SciBite provides an integrated, cost-effective solution to significantly reduce the time and cost associated with the process of data cleansing, normalisation and annotation. The output ensures that downstream integration and discovery activities are based on high quality, contextualised data.
To learn more, download the full use case.
Perfect for those new to bio-ontologies or who work with ontologists - a whole new vocabulary deciphered!Read
SciBite is delighted to announce that we've been awarded Best of Show at Bio IT 2017!Read
Get in touch with us to find out how we can transform your data
© SciBite Limited / Registered in England & Wales No. 07778456