Machine learning

SETTING

Setting

Data repositories are exponentially growing and the end is not in sight. Ever more sequencing information, biological data, generated images is becoming available both in public repos as internally with our customers. With this vast amount of information at hand, now is the time to try and learn from this data, to discover patterns driving future Life Science Research.

 

Machine learning is now being introduced in bioinformatics within the Life Science Research. Computer aided algorithm or mathematical model design, based on a training set, can be applied in order to make predictions or decisions. Multiple underlying algorithms exist and can be implemented dependent of the data at hand: (non)linear or logistic regression, classification as SVM, nearest neighbors or random forest, k-means or spectral clustering, dimensionality reduction, deep learning or neural networks.

BioLizard

HELPS OUT!

BioLizard

HELPS OUT!

Machine learning expertise is becoming more important in the bioinformatics field. Our trained professionals have experience with packages providing these solutions as scikit-learn, or pytorch, enabling us to build custom solutions in collaboration with our customers.

 

BioLizard operates as a team! Selected consultants implement machine learning solution at the customer’s site but are always backed by experienced colleagues and industry or academic experts.

 

Our Lizards are trained professionals both experience in informatics, statistics or machine learning and relevant fields of molecular biology. Furthermore, we strive towards high-standard communication and project management skills. Regular follow up meetings are organized together with customer researchers and the BioLizard team (consultants, industry and academic experts) to guarantee smooth and successful execution of the proposed bioinformatics solution.