SYSUCC Sun Yat-sen University Cancer Center

OUR TOOLS


dSCOPE
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dSCOPE is a web server developed for detecting sequences critical for phase separation related proteins.
A software to detect sequences critical for liquid–liquid phase separation
Briefings in Bioinformatics
2023 24(1),1-11
doi: 10.1093/bib/bbac550

DrugCVar
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DrugCVar database, which integrated our manually curated cancer variant-drug targeting evidences from literature and the interpretations from the public resources. In total, 8,539 clinical evidences for cancer variant-drug targeting were integrated and classified into ten evidence tiers.
A platform for evidence-based drug annotation for genetic variants in cancer
Bioinformatics
38, 11, June 2022, 3094-3098
doi: 10.1093/bioinformatics/btac273

DrugCVar
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DrugCVar database, which integrated our manually curated cancer variant-drug targeting evidences from literature and the interpretations from the public resources. In total, 8,539 clinical evidences for cancer variant-drug targeting were integrated and classified into ten evidence tiers.
A platform for evidence-based drug annotation for genetic variants in cancer
Bioinformatics
38, 11, June 2022, 3094-3098
doi: 10.1093/bioinformatics/btac273

pCysMod
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pCysMod is a web server based on deep learning to predict cysteine modification sites.
Prediction of Multiple Cysteine Modifications Based on Deep Learning Framework
Frontiers in Cell and Developmental Biology
2021 Feb 23, fcell.2021.617366
doi: 10.3389/fcell.2021.617366

Deep-PLA
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Deep-PLA is a web server developed for understanding the reversible enzyme-specific lysine acetylation regulation for histone acetyltransferases (HATs) including CREBBP, EP300, HAT1, KAT2A, KAT2B, KAT5 and KAT8, and deacetylases (HDACs) including HDAC1, HDAC2, HDAC3, HDAC6, SIRT1, SIRT2, SIRT3, SIRT6, and SIRT7.
Deep learning based prediction of reversible HAT/HDAC-specific lysine acetylation
Briefings in Bioinformatics
2020 Sep 25, 21(5):1798-1805
doi: 10.1093/bib/bbz107

Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics

DeepGSH
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DeepGSH is a web server based on deep learning to predict S-glutathionylation sites. Given a protein or a set of proteins in FASTA format, it can predict the possible S-glutathionylation sites in proteins.
Deep learning based prediction of species-specific protein S-glutathionylation sites
Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics
2020 Jul, 1868(7):140422
doi: 10.1016/j.bbapap.2020.140422

DeepCalpain
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DeepCalpain is a web server based on deep learning to predict calpain-specific cleavage events. Given a protein or a set of proteins in FASTA format, it can predict the possible cleavage sites of two major types of calpain, including m-calpain and μ-calpain.
Precise prediction of calpain cleavage sites and their aberrance caused by mutations in cancer
Frontiers in Genetics
2019 Aug 8, 10:715
doi: 10.3389/fgene.2019.00715

prkC-PSP
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In this study, we manually curated the experimentally iden-tified substrates and phospho-rylation sites of prkC from the published literature, and developed a novel software of prkC-PSP (prkC-specific Phosphorylation Sites Prediction) for the prediction of prkC-specific phosphorylation sites.
Prediction of prkC-mediated protein serine/threonine phosphorylation sites for bacteria
PloS one
2018 Oct 2, 13(10):e0203840
doi: 10.1371/journal.pone.0203840

Advances in experimental medicine and biology

cPhosBac
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In this study, we present a new predictor of cPhosBac to predict phosphorylation serine/threonine in bacteria proteins.
Prediction of serine/threonine phosphorylation sites in bacteria proteins
Advances in experimental medicine and biology
2015, 827:275-85
doi: 10.1007/978-94-017-9245-5_16