Data science for a better future – the exploration of complex biological systems
Computational Life Science is an interdisciplinary field that combines knowledge of computer science, statistics, genetics, medicine, chemistry, agriculture and other related fields. Using data-driven AI approaches, biometric data can be systematically and precisely analyzed and identified.
Through data comparison, damage patterns can be identified at an early stage. More serious consequential damage to the respective biosystem can thus be prevented at an early stage. The Supper & Supper BIO team has extensive professional experience in hospitals and various biological institutions and organizations. We deliver customized AI and Machine Learning solutions.
In the analysis of biometrics, we combine classical statistical methods with our innovative machine learning models. Our procedures aim to identify hidden factors that improve the effectiveness of a product or minimize potential risks and dangers. Possible areas of application are:
- Early detection of cancer using X-rays
- Optimization of the pesticide effect in botany
- Trial planning for clinical studies and field trials
- Analysis of the interaction between genes and the environment
Supper & Supper’s BIO Data Science team can provide data-driven AI solutions to companies in virtually all bio-related industries. Our processes, techniques and products offer particularly great potential for:
+ Clinics and hospitals
+ Pharmaceutical industry
+ Plant protection companies
+ Research institute in the biological field
+ Seed companies
+ Companies in the field of medicine and biotechnology
The implementation by Supper & Supper delivered the full scope of Minimum Viable Products on time and within budget. This new Syngenta product meets, in the simplest way, complex business requirements for a large number of departments in the Syngenta R & D organization.
Supper & Supper functions as an extended workbench for the Data Labs of internationally operating research and development organizations. We can fully integrate into existing teams and structures and implement projects autonomously or in collaboration with internal data science departments. We help our clients to increase their productivity, save time and make technological progress.
Learn more about concrete usage potentials
of Computational Lifescience in our Use Cases