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Bricks

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.

Public
BM
Benjamin Maisonneuve
Mar 9, 2022

gws_ode

Brick for Ordinary Differential Equations

Public
DO
Djomangan Adama OUATTARA
Mar 22, 2022

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.

Public
BM
Benjamin Maisonneuve
Mar 9, 2022

gws_scomix

This brick allows users to analyse scRNAseq datasets

Public
RD
Romain De Oliveira
Mar 6, 2023

gws_gena

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

Public
BM
Benjamin Maisonneuve
Mar 9, 2022

gws_ubiome

uBiome provides core features for 16S rRNA short-read sequencing analysis

Public
BM
Benjamin Maisonneuve
Mar 9, 2022

gws_sim

Gencovery brick for dynamical system simulations

Public
DO
Djomangan Adama OUATTARA
Mar 11, 2023

gws_core

Core brick for Constellab. This brick is included in any lab and manage the core functionalities of the lab (experiments, resource, reports...). It contains generic tasks and resources for your pipeline.

Public
BM
Benjamin Maisonneuve
Mar 9, 2022

gws_biota

BIOTA is a unified and structured collection of omics data collected from official open European (EMBL-EBI) and NCBI taxonomy knowledge bases. More than 2 M organisms are referenced in BIOTA with their metabolic characteristics.

Public
BM
Benjamin Maisonneuve
Mar 9, 2022

gws_metag

Short-reads and long-reads metagenomic assembly and annotation pipeline

Public
RD
Romain De Oliveira
Jul 29, 2022