Pinned Repositories
AMBROSIA
ICARUS
Flexible protein structural alignment based on Protein Units
MEDUSA
A Deep Learning based protein flexibility prediction tool.
openfold
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
pepit
The PepIT program proposes peptides that may interact with a given protein. PepIT is based on a non-sequential alignment algorithm to identify peptide binding sites that share geometrical and physicochemical properties with regions on the target protein.
PoincareMSA
Detection of the structural, evolutionary and functional relationship between different proteins and protein families requires comparative analysis of their amino acid sequences through multiple sequence alignment. While a direct analysis of the resulting data allows to identify conserved regions, it does not provide a general and broad view on the proteins’ hierarchical organization and their distribution in the sequence, structural or functional spaces. Our project aims to develop a novel strategy for multiple sequence alignment visualization and interpretation using a powerful method demonstrated its efficiency for the hierarchy detection in multi-dimensional data sets called Poincaré maps.
PYTHIA
Deep Learning Approach For Local Protein Conformation Prediction
SWORD2
SWift and Optimized Recognition of protein Domains
test_fork
This is a fork of my test repo
VEP-Benchmark
DSIMB's Repositories
DSIMB/SWORD2
SWift and Optimized Recognition of protein Domains
DSIMB/MEDUSA
A Deep Learning based protein flexibility prediction tool.
DSIMB/PoincareMSA
Detection of the structural, evolutionary and functional relationship between different proteins and protein families requires comparative analysis of their amino acid sequences through multiple sequence alignment. While a direct analysis of the resulting data allows to identify conserved regions, it does not provide a general and broad view on the proteins’ hierarchical organization and their distribution in the sequence, structural or functional spaces. Our project aims to develop a novel strategy for multiple sequence alignment visualization and interpretation using a powerful method demonstrated its efficiency for the hierarchy detection in multi-dimensional data sets called Poincaré maps.
DSIMB/ICARUS
Flexible protein structural alignment based on Protein Units
DSIMB/PYTHIA
Deep Learning Approach For Local Protein Conformation Prediction
DSIMB/pepit
The PepIT program proposes peptides that may interact with a given protein. PepIT is based on a non-sequential alignment algorithm to identify peptide binding sites that share geometrical and physicochemical properties with regions on the target protein.
DSIMB/AMBROSIA
DSIMB/ANN-Glycolysis-Flux-Prediction
Flux prediction using artificial neural network (ANN) for the upper part of glycolysis.
DSIMB/GC-ANN-Enzyme-Concentration-Selection
DSIMB/openfold
Trainable, memory-efficient, and GPU-friendly PyTorch reproduction of AlphaFold 2
DSIMB/test_fork
This is a fork of my test repo
DSIMB/VEP-Benchmark
DSIMB/CompareCBS
Comparison of carbohydrate binding site (CBS) geometry using a graph-based method