This server is designed for the prediction of Cyclin-dependent Proteins (CDPs). It will generate an email message containing numeric scores for each protein in your submission that quantifies putative propensity for an unknown function protein to be cyclin-dependent protein. Putative annotations (a given protein is predicted either as a CDP or non-CDP) displayed on the result page. All comments, suggestions or requests regarding our work are welcome. For more information please contact biocomputinglab@sina.com.

Please follow the TWO steps below to make a prediction

STEP ONE   Paste no more than TEN protein sequences with standard FASTA format:

  To make a blance among various predictors that deployed on this server, we limit the computation resource for TYLER. For large-scale predictions, you are welcome to send your protein sequences to us via jianzhang@xynu.edu.cn or biocomputinglab@sina.com

  Click Here to Use Example Protein Sequence

STEP TWO Provide you email address:

HELP

TYLER can accept at most TEN protein sequences for a sigle prediction. You should input the protein sequence in standard FASTA format, which begins with a symbol ">". The format of the input protein sequence is as follows:

    Line 1: > PDB ID or UniProtKB ID or any other annotation(s)

    Line 2: protein sequence (1-letter amino acid encoding)

We will send a message reporting the detailed prediction result to the email address you input once the current prediction is finished. For more information in respect to its content, please make a try and see the result.

Materials

TRAINING dataset Download

TEST dataset Download

10 subsets of CDPs that used to compute enriched cyclin-related motifs Download

10 subsets of non-CDPs that used to compute enriched cyclin-related motifs Download

Putative cyclin-dependent proteins in the human proteome Download

Citation

Upon the usage the users are requested to use the following citation:

Jian Zhang, Xingchen Liang, Feng Zhou, Bo Li, 2021, TYLER, a fast method that accurately predicts cyclin-dependent proteins based on computation-based motifs and sequence-derived features, submitted.

Acknowledgments

We acknowledge with thanks the following databases and software used as a part of this server:

UniProtKB- UniProt Knowledgebase

PANTHER- Gene List Analysis

Pfam- Collection of protein families

Reactome- Protein pathway database

MMseqs2- Search and cluster huge protein and nucleotide sequence sets

PSI-PRED- Prediction of secondary structure