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Gencovery Newsletter #6 - Constellab new features
Your digital transformation guide With the Constellab data and AI platform, fully leverage your data and turn it into a strategic asset! ✅ Fast and secure digitalization ✅ An intuitive and high-perfor...
Metadata explained: meaning, examples for everyday use
Metadata are everywhere. They are essential for describing and harmonizing information, particularly in multi-source and multi-operator environments. Without well-structured metadata, information beco...
Optimizing data and document organization with tags in Constellab
The ability to organize documents effectively is essential for efficient data management and collaboration. One of the most powerful ways to do this is by using key-value tags. These tags assign ...
Working under influence: When AI prompts take over creativity
By 2025, it is expected that 90% of the content available on the internet will be produced with the help of artificial intelligence Source: <a href="https://quidgest.com/en/blog-en/...
Payfit time tracking aggregator
Migrate gws_biolector to gws_plate_reader
Automatic note for Iris pipeline
Fix ubiome after migration
gws_gaia
GAIA (Gencovery Artificial Intelligence Analytics) provides core features for machine learning and deep learning modelling. It offers a broad range of AI algorithms, covering among others classification, regression, clustering methods, neural networks.

gws_ode
Brick for Ordinary Differential Equations

gws_stats
STATS (Statistical Tools Suite) provides core features for statistical analysis of biological data. It offers the most widely used statistical methods for biological data analysis to quantitatively assess your hypothesis from your data.

gws_gena
GENA provides core features to create and use actionable digital twins of cell metabolism to understand and predict cell mechanisms of action.
