Introduction
Lysine crotonylation (Kcr) is a novel post-translational modification of proteins that has attracted wide attention in recent years, mainly occurring on protein lysine residues. It plays a pivotal role in gene expression regulation, cellular metabolism, and a variety of life activities. Kcr has an important regulatory role in major diseases such as tumors and cancer. Therefore, accurate prediction of the Kcr site is essential for understanding the normal functioning of an organism. We propose a deep learning computational model called iKcr-DRC for accurate prediction of Kcr sites.
Prediction by inputting sequences
The user can submit the protein sequences (example), and the webserver can identify Lysine 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.
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.