Biomolecules Folding and Disease



Resources

The researchers of the BioFolD Unit have developed several web server applications that are currently hosted on servers of the University of Bologna (Italy) and maintained by other collaborators. In the future a mirror of these applications will be made available on this server. Currently you can reach these web servers using the following links.

Folding and Stability

I-Mutant1.0

Neural Network based method to predict the sign of free energy change of proteins upon single point mutation.

I-Mutant2.0

Support Vector Machine based method to predict the sign and the value of free energy change of proteins upon single point mutation.

K-Fold

Support Vector Machine based method to predict the mechanism and rate of protein folding kinetic.

K-Pro

Database of kinetics data on proteins and mutants.

ThermoScan A semi-automatic method for retrieving protein thermodynamic data from literature.

DDGun

Untrained method for predicting the variation of free energy change of protein mutants.


Genomic Variations and Disease

ContrastRank

Statistical method for the classification of cancer samples using exome sequencing data.

DrCancer

Support Vector Machine based method to predict cancer-causing mutations (Beta version).

Fido-SNP Machine learning method for predicting the impact of SNVs in the dog genome.

Meta-SNP

Meta-predictor of disease causing varints that uses the output of PANTHER, PhD-SNP, SIFT and SNAP

PhD-SNP

Support Vector Machine based method to discriminate between neutral or disease-related single point protein mutations.

PhD-SNPg

Machine learning method for predicting pathogenic variants in coding and non-coding regions.

WS-SNPs&GO

Support Vector Machine method for the detection of disease-related SNPs based on functional information


Macromolecular Structure

SARA

Method for RNA structure alignment and RNA functional assignment.

SARA-Coffee

Method for RNA multiple structure alignment

WebRASP

Method for the assessment RNA 3D structures