DisoMine: Intrinsically disordered regions

Our new b2bTools interface gives integrated access to individual predictors.

It includes a novel feature to explore prediction-based 'biophysical variation' of proteins from a multiple sequence alignment.

Single Sequence Predictors

DynaMine

Predicts protein backbone dynamics and flexibility

DisoMine

Identifies intrinsically disordered regions in proteins

EarlyFolding

Predicts early folding residues in protein sequences

AgMata

Identifies aggregation-prone regions in proteins

PSP

Predicts protein structure and secondary structure elements

MSA Predictors

Multiple Sequence Alignment based predictors that analyze evolutionary information to predict protein properties.

Single Sequence Predictors

Including DynaMine, DisoMine, EFoldMine and AgMata

Gaussian Mixture Model Analysis

Score analysis of residues based on GMM scores

Distribution Analysis

Contextualizing residues based on their distribution in the MSA (bottom quartile, middle quartile, top quartile)

Chemical Shift Predictors

ShiftCrypt

Predicts chemical shifts from input files in the NMR Exchange Format (NEF) or NMR-STAR format

Submit Your Sequence

Your prediction submission is related to a token saved in your browser session. You can manage your token from the navigation bar.

Single Sequence

Analyze individual protein sequences

Select your predictors

DisoMine Intrinsically disordered regions

Please select at least one predictor.

Enter Your Sequence

Only accepts FASTA format

Direct Input

File Upload

Enter your protein sequence(s) in valid format or upload a valid file

Enter Your Chemical Shift Data

Accepts NMR and NEF formats.

Chemical Shift Input

Enter your chemical shift data or upload a NEF/NMR-star file

Model Class Selection

Full CS Set Method with the full set of chemical shifts (may return -10 for missing values)

Common CS Method with just the most common chemical shift values

N and H CS Method with only N and H chemical shifts (used for dimers)

Use Original Numbering Keep the original residue numbering from the input file

Our Ecosystem

Bio2Byte Tools are part of a larger ecosystem of bioinformatics tools and resources:

Bitbucket

Access our source code and contribute to the project on Bitbucket.

View on Bitbucket

REST API

Use our tools through our REST API.

REST API

PyPI

Install our tools directly from the Python Package Index using pip.

View on PyPI

Google Colab

Run our tools directly in your browser using Google Colab notebooks.

Open in Colab

Galaxy

Use our tools through Galaxy Europe and Belgium platforms.

Galaxy Europe

Further Information

Find more information about our tools and resources here:

Tutorials

Learn how to use our tools effectively with step-by-step tutorials.

View Tutorials

API Reference

Integrate our tools into your workflow using our REST API.

API Docs

Feedback

Help us improve by sharing your experience and suggestions.

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Publications

Learn about the science behind our tools and their applications.

View Publications