We propose 4acCPred web server, the first prediction framework for high-accuracy identification of 4acC-carrying regions from Arabidopsis genomic DNA sequences. It is designed to help users:
(1) Predicting 4acC modifications.
(2) visualizing captured motif patterns.

All data used in this study (peak information called by MACS2 with annotation) and trained 4acCPred models have also been uploaded to the web server for user convenience. We anticipate that our newly proposed model and the web server can take full advantage of limited experimental data and facilitate the study of DNA 4acC methylation by providing alternative computational prediction approaches.

We have uploaded the peak information with the annotation that is called by MACS2. (datasets with four treatment conditions: standard - Arabidopsis gDNA (wild type), NH₂OH - Arabidopsis gDNA treated with NH₂OH samples, met - Arabidopsis gDNA treated with met1 mutant, and rdd - Arabidopsis gDNA treated with ros1dml2dml3(rdd) mutant).
Users could change shown table by selecting different conditions. Details could be downloaded from the button below the table in CSV format.

Users could input query sequences (FASTA) to the box or upload a FASTA file. Users could also control the condition, motif requirement, and speed.

The result table shows probability, prediction result, and motif figure(if required).

We displayed a framework figure and a brief introduction of the model. Users could download this model.