CURE-Choroplast - C to U RNA Editing predictor for chloroplasts of seed plants
Version 1.0

    In CURE-Chloroplast algorithm, the only required input is a genomic sequence. The only requirement is that the input sequence is an unedited sequence. Currently, CURE-Chloroplast is designed to predict the C-to-U RNA editing sites in CDS region of the chloroplast gene. There are some parameters that can be adjusted in the advanced mode of CURE-Chloroplast. Please read the software manual in the download section for more information on using CURE-Chloroplast. If you want to know more about CURE-Chloroplast, please go to our HELP page.

Basic mode
Paste single raw sequence [Change]

Note: Do not enter fasta remark line in the above box. Paste only single raw sequence.
Advanced mode options
Activate Advanced Mode
Show instructions Micro-analyser parameter
Up bound of the working region
Low bound of the working region
K-NN: K value
Show instructions Cons-T EPES
Cons-T EPES
Show instructions Positive strand only
Positive Strand Only
Show instructions Blast parameter
E-value cutoff
Word size

    The software manual and a sample fasta file for quick test can be downloaded below.

User Manual      The software manual provide deltailed instructions on using CURE-Chloroplast service. This document also provids useful tips on using CURE-Chloroplast efficiently.
Software Manual
 
CURE-Chloroplast sample dataset      If you are interested in evaluating CURE-Choloroplast service, you may use this file to get a quick experience of CURE-Chloroplast.
Sample FASTA

 

Authors Declaration

    CURE-Chloroplast algorithm was designed by Pufeng Du. The EPES Library in the CURE-Chloroplast was generated and plugged-in by Liyan Jia. For the algorithm details, you can contact Pufeng Du. The details of the EPES Library in CURE-Chloroplast can be obtained by sending a request to Liyan Jia. This service can be used to any academic purpose for free. For the purpose other than academic purpose, please contact Yanda Li.

    

Acknowledgement

    This work was partially supported by the National Nature Science Foundation of China (Grant Nos.60572086 and 60775002).

    

Supplementary materials

    Citation is not available currently.

 

Bioinformatics Division, TNLIST and Department of Automation, Tsinghua University

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