Here you select your input file, then press 'Next step' to proceed to the selection of predictor(s). Currently, the system takes FASTA files, a range of multiple sequence alignment (MSA) formats, and the NEF and NMR-STAR formats for NMR chemical shift data.
Click on 'Test examples' below to run predictions using an existing example file.
Click on 'Download test examples' below to download example files for upload.
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.