IDP-ELM: Accurate and Fast Prediction of Intrinsically Disordered Protein by Multiple Protein Language Models and Ensemble Learning

IDP-ELM is a web server for predicting intrinsically disordered proteins (IDPs) from amino acid sequences, based on multiple protein language models and ensemble learning. It is designed to predict IDPs with high accuracy and speed. [ GitHub | Paper | License ]

IDP-ELM

Prediction Results

The prediction process may take a few seconds and may not been very soon since it is running with limited resources without GPU. The results contains 5 lines:

  1. The first line is the sequence ID.
  2. The second line is the input sequence.
  3. The third line is the propensity of intrinsically disorder.
  4. The fourth line is the propensity of disordered flexible linker.
  5. The fifth line is the propensity of disordered protein binding.

References

Users are kindly requested to utilize the following citation when referencing this method:

Please contact shijie.xu@ees.hokudai.ac.jp for any questions.

Changelogs