IHNC-RsFPN Server User Guide

Introduction

Crotonylation on lysine sites in human non-histone proteins plays a crucial role in biological activities. However traditional wet experiments are both time consuming and laborious. The use of computational prediction methods has gained more popularity in recent years. Although crotonylation of lysine sites plays a very important role, the human non-histone proteins have been less studied. In this study, we developed an ensemble deep learning predictor called iHNHC-RsFPN.

Prediction by inputting sequences

The user can submit the protein sequences (example), and the webserver can identify the crotonylation sites automatically, and return the prediction result to the Web interface.

Prediction by inputting sequences

Users can submit a protein sequence file (FASTA format) by the function.The webserver will send the predicted results to the mailbox submitted by the user.

    The explanation of Input:

  • Protein file: the FASTA format file containing the protein sequence to be predicted (example).

  • Program name: defined by users and the webserver will use it to mark the task.

  • Email: An email address to receive the prediction results after the prediction task is completed.

Open source

In addition to our online services, we extend our support to the academic community by providing access to the source code and models for download, thereby facilitating their research and application endeavors.