We are pleased to announce that we have recently published a collection of Jupyter Notebooks. These documents provide the opportunity for users to replicate and run the same predictions as found on our website, but utilizing the platform of Google Colab.
The list of notebooks is located at the following link: Bio2Byte public notebooks.
Our web interface gives integrated access to individual predictors, and includes a novel feature to explore prediction-based 'biophysical variation' of proteins from a multiple sequence alignment (the complete list of the our software tools is available here).
Depending on the format of your input data, in the second step of this web interface, you will be able to select predictors from these list:
This tools are also available directly through an REST API, find the guidelines and examples on the API documentation section. In addition, we provide a Python Package with all our tools (Single Sequence, MSA, and general tools such as parsing and plotting) to enable you to integrate these predictors in your pipelines. For more information, please visit our site on the Python Package Index: b2BTools package.
Please read the usage guidelines provided on the tutorial section. If you have any feedback or found an issue, please contact us using the feedback from. Read our Terms of use if you are concerned with your privacy and how we handle personal information.