Multiple Instance Learning based AMyloid Prediction (MILAMP)


This is the webserver for our paper " Farzeen Munir, Sadaf Gull, Amina Asif and Fayyaz Minhas, MILAMP: Multiple Instance Prediction of Amyloid Proteins, IEEE/ACM transactions on computational biology and bioinformatics, 2019. " It can predict whether an amino acid sequence is amyloid or not, identify its hotspots, and detect change in amyloidogenicity due to point mutations.

To use it for prediction, enter a single amino acid sequence (for example KCNTATCATQRLANFLVRSSNNLGPVLPPTNVGSNTY) in the first box. You can optionally enter information about point mutations in the second textbox in the following format: [Original Amino Acid][Position][Mutant Amino Acid] (for example, K1H describes a mutation at position 1 from K to H). You can give more than one mutations as H18R,L23F,V26I. Hit "Predict" to generate predictions.

             Amino acid Sequence: 
Mutations in above sequence: 

Developed and maintained by Biomedical Informatics Research Laboratory , Department of Computer and Information Sciences   (DCIS),
Pakistan Institute of Engineering and Applied Sciences  (PIEAS) , Islamabad, Pakistan.