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emb2dis is a deep learning approach based on pretrained protein language models and residual networks with dilated convolutions, trained to identify disordered regions in protein sequences.
This demo provides a pre-trained model with ESM2 and ProtT5 embeddings on the DisProt database, ready to be used for disorder prediction on a single protein.
Input sequences of up to 1,000 amino acids can be processed with this demo. To process longer sequences you can install emb2dis from the repository.
Sample input:
- MSDNGPQNQRNAPRITFGGPSDSTGSNQNGERSGARSKQRRPQGLPNNTASWFTALTQHGKEDLKFPRGQGVPINTNSSP
DDQIGYYRRATRRIRGGDGKMKDLSPRWYFYYLGTGPEAGLPYGANKDGIIWVATEGALNTPKDHIGTRNPANNAAIVLQLPQ
GTTLPKGFYAEGSRGGSQASSRSSSRSRNSSRNSTPGSSRGTSPARMAGNGGDAALALLLLDRLNQLESKMSGKGQQQQGQ
TVTKKSAAEASKKPRQKRTATKAYNVTQAFGRRGPEQTQGNFGDQELIRQGTDYKHWPQIAQFAPSASAFFGMSRIGMEVTP
SGTWLTYTGAIKLDDKDPNFKDQVILLNKHIDAYKTFPPTEPKKDKKKKADETQALPQRQKKQQTVTLLPAADLDDFSKQLQQ
SMSSADSTQA
Contact: Sofia A. Duarte