mbensouda
Computational biologist with a background in statistical physics. Very enthusiastic about variational inference and its interplay with DL to predict cell fate.
Altos LabsSan Francisco
Pinned Repositories
demo-rep
Demo for Github Intro video
Disasters_prediction
repo associated to the Kaggle competition - KerasNLP starter notebook Disaster Tweets
giulioisac.github.io
Immprint
ImmPrint answers the question "were these two samples extracted from the same individual ?" by looking at the numbers and sequences of shared unique TCR between the two samples.
mbensouda.github.io
Repo linked to my personal webpage
NoisET_
NoisET is an easy-to-use python package that implements and generalizes a previously developed Bayesian method in [Puelma Touzel et al, 2020] ). It can be used to learn experimental noise models for repertoire sequencing from replicates, and to detect responding clones following a stimulus.
NoisET_documentation
html_file_noisET_documentation_API
NoisET_tutorial
Inferring_TCR_repertoire_dynamics
Repository associated with the paper "Inferring and predicting the T-cells repertoire dynamics of healthy individuals"
NoisET
NoisET is an easy-to-use python package that implements and generalizes a previously developed Bayesian method in [Puelma Touzel et al, 2020] ). It can be used to learn experimental noise models for repertoire sequencing from replicates, and to detect responding clones following a stimulus.
mbensouda's Repositories
mbensouda/demo-rep
Demo for Github Intro video
mbensouda/Disasters_prediction
repo associated to the Kaggle competition - KerasNLP starter notebook Disaster Tweets
mbensouda/giulioisac.github.io
mbensouda/Immprint
ImmPrint answers the question "were these two samples extracted from the same individual ?" by looking at the numbers and sequences of shared unique TCR between the two samples.
mbensouda/mbensouda.github.io
Repo linked to my personal webpage
mbensouda/NoisET_
NoisET is an easy-to-use python package that implements and generalizes a previously developed Bayesian method in [Puelma Touzel et al, 2020] ). It can be used to learn experimental noise models for repertoire sequencing from replicates, and to detect responding clones following a stimulus.
mbensouda/NoisET_documentation
html_file_noisET_documentation_API
mbensouda/NoisET_tutorial