<1> Public Databases integrated in iUUCD 2.0
(1) Cancer Mutation
(2) Single Nucleotide Polymorphism (SNP)
(3) mRNA Expression
(4) DNA & RNA Element
(5) Protein-protein Interaction
(6) Protein 3D Structure
(7) Disease-associated Variation
(8) Drug and Target
(9) Post-translational Modifications (PTMs)
(10) DNA Methylation
(11) Protein Expression/Proteomics
<2>
Public Databases for ubiquitin and ubiquitin-like conjugations
<3> Computational Algorithms and Tools
(1)
Ubiquitination
(2)
Ubiquitin-like modification
last updated: Jun, 2017
<1> Public Databases integrated in iUUCD 2.0
(1) Cancer Mutation:
1. TCGA: Comprehensive genomic characterization defines human glioblastoma genes and core pathways (Cancer Genome Atlas Research Network, 2008).
2. ICGC:
International Cancer Genome Consortium Data Portal--a one-stop shop for cancer genomics data (Zhang, et al., 2011).
3. COSMIC:
COSMIC: exploring the world's knowledge of somatic mutations in human cancer (Forbes,
et al., 2014).
4. CGAP:
A new cancer genome anatomy project web resource for the community (Schaefer,
et al., 2001).
5. IntOGen:
IntOGen: integration and data mining of multidimensional oncogenomic data (Gundem,
et al., 2010).
(2) Single Nucleotide Polymorphism (SNP):
1. dbSNP:
dbSNP: the NCBI database of genetic variation (Sherry, et al., 2001).
(3) mRNA Expression:
1. GEO:
Gene Expression Omnibus: NCBI gene expression and hybridization array data repository (Edgar,
et al., 2002).
2. ArrayExpress:
ArrayExpress: a public database of gene expression data at EBI (Rocca-Serra,
et al., 2003).
3. GXD:
The mouse Gene Expression Database (GXD): 2014 update (Smith,
et al., 2014).
4. FFGED:
The filamentous fungal gene expression database (FFGED) (Zhang,
et al., 2010).
5. TCGA: Comprehensive genomic characterization defines human glioblastoma genes and core pathways (Cancer Genome Atlas Research Network, 2008).
6. ICGC:
International Cancer Genome Consortium Data Portal--a one-stop shop for cancer genomics data (Zhang, et al., 2011).
7. COSMIC:
COSMIC: exploring the world's knowledge of somatic mutations in human cancer (Forbes,
et al., 2014).
8. Human Proteome Map:
A draft map of the human proteome (Kim,
et al., 2014).
9. Human Protein Atlas:
The Human Protein Atlas as a proteomic resource for biomarker discovery (Pontén,
et al., 2011).
10. SZDB:
SZDB: A Database for Schizophrenia Genetic Research (Wu, et al. 2017).
(4) DNA & RNA Element:
1. UTRdb:
UTRdb and UTRsite (RELEASE 2010): a collection of sequences and regulatory motifs of the untranslated regions of eukaryotic mRNAs (Grillo,
et al., 2010).
2. AREsite:
AREsite: a database for the comprehensive investigation of AU-rich elements (Gruber,
et al., 2011).
3. JASPAR CORE:
JASPAR 2016: a major expansion and update of the open-access database of transcription factor binding profiles (Mathelier,
et al., 2016).
4. circBase:
circBase: a database for circular RNAs (Glažar,
et al., 2014).
5. circRNADb:
circRNADb: A comprehensive database for human circular RNAs with protein-coding annotations (Chen,
et al., 2016).
6. CircNet:
CircNet: a database of circular RNAs derived from transcriptome sequencing data (Liu, et al. 2016).
7. Circ2Traits:
Circ2Traits: a comprehensive database for circular RNA potentially associated with disease and traits (Ghosal,
et al., 2013).
8. miRTarBase:
miRTarBase: a database curates experimentally validated microRNA-target interactions (Hsu,
et al., 2011).
9. microRNA.org:
The microRNA.org resource: targets and expression (Betel,
et al., 2008).
10. TRANSFAC:
TRANSFAC and its module TRANSCompel: transcriptional gene regulation in eukaryotes (Matys,
et al., 2006).
11. miRWalk:
miRWalk2.0: a comprehensive atlas of microRNA-target interactions (Dweep,
et al., 2015).
12. TargetScan:
Predicting effective microRNA target sites in mammalian mRNAs (Agarwal,
et al., 2015).
13. miRecords:
miRecords: an integrated resource for microRNA-target interactions (Xiao,
et al., 2009).
14. RepTar:
RepTar: a database of predicted cellular targets of host and viral miRNAs (Elefant,
et al., 2011).
15. miRNAMap:
miRNAMap 2.0: genomic maps of microRNAs in metazoan genomes (Hsu,
et al., 2008).
16. SomamiR DB 2.0:
SomamiR 2.0: a database of cancer somatic mutations altering microRNA-ceRNA interactions (Bhattacharya,
et al., 2016).
17. miRcode:
miRcode: a map of putative microRNA target sites in the long non-coding transcriptome (Jeggari,
et al., 2012).
18. RAID v2.0:
RAID v2.0: an updated resource of RNA-associated interactions across organisms (Yi,
et al., 2017).
19. LncRNADisease:
LncRNADisease: a database for long-non-coding RNA-associated diseases (Chen,
et al., 2013).
(5) Protein-protein Interaction:
1. IID:
Integrated interactions database: tissue-specific view of the human and model organism interactomes (Kotlyar,
et al., 2016).
2. iRefIndex:
iRefIndex: a consolidated protein interaction database with provenance (Razick,
et al., 2008).
3. PINA:
PINA v2.0: mining interactome modules (Cowley,
et al., 2012).
4. HINT:
HINT: High-quality protein interactomes and their applications in understanding human disease (Das,
et al., 2012).
5. Mentha:
mentha: a resource for browsing integrated protein-interaction networks (Calderone,
et al., 2013).
6. InWeb_IM:
A scored human protein-protein interaction network to catalyze genomic interpretation (Li,
et al., 2017).
(6) Protein 3D Structure:
1. PDB:
The Protein Data Bank (Berman,
et al., 2000).
2. MMDB:
MMDB: 3D structures and macromolecular interactions (Madej,
et al., 2012).
3. SCOP:
SCOP2 prototype: a new approach to protein structure mining (Andreeva,
et al., 2014).
(7) Disease-associated Variation:
1. ClinVar:
ClinVar: public archive of interpretations of clinically relevant variants (Landrum,
et al., 2016).
2. OMIM:
OMIM.org: Online Mendelian Inheritance in Man (OMIM®), an online catalog of human genes and genetic disorders (Amberger,
et al., 2015).
3. GWASdb:
GWASdb v2: an update database for human genetic variants identified by genome-wide association studies (Li,
et al., 2016).
4. GWAS Central:
GWAS Central: a comprehensive resource for the comparison and interrogation of genome-wide association studies (Beck,
et al., 2014).
(8) Drug and Target:
1. DrugBank:
DrugBank 4.0: shedding new light on drug metabolism (Law,
et al., 2014).
2. TTD:
Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery (Zhu,
et al., 2012).
3. KPID:
Kinase Profiling Inhibitor Database (MRC PPU International Centre for Kinase Profiling, 2012).
4. CARLSBAD:
The CARLSBAD database: a confederated database of chemical bioactivities (Mathias,
et al., 2013).
5. SuperTarget:
SuperTarget goes quantitative: update on drug-target interactions (Hecker,
et al., 2012).
6. GRAC:
The IUPHAR/BPS Guide to PHARMACOLOGY: an expert-driven knowledgebase of drug targets and their ligands (Pawson,
et al., 2014).
7. PDTD:
PDTD: a web-accessible protein database for drug target identification (Gao,
et al., 2008).
(9) Post-translational Modifications (PTMs):
1. CPLM:
CPLM: a database of protein lysine modifications (Liu,
et al., 2014).
2. dbPAF:
dbPAF: an integrative database of protein phosphorylation in animals and fungi (Ullah,
et al., 2016).
3. dbPPT:
dbPPT: a comprehensive database of protein phosphorylation in plants (Cheng,
et al., 2014).
4. phosSNP:
PhosSNP for systematic analysis of genetic polymorphisms that influence protein phosphorylation (Ren,
et al., 2010).
5. PhosphositePlus:
PhosphoSitePlus, 2014: mutations, PTMs and recalibrations (Hornbeck,
et al., 2015).
6. Phospho.ELM:
Phospho.ELM: a database of phosphorylation sites--update 2011 (Dinkel,
et al., 2011).
7. dbPTM:
dbPTM 2016: 10-year anniversary of a resource for post-translational modification of proteins (Huang,
et al., 2016).
8. PHOSIDA:
PHOSIDA 2011: the posttranslational modification database (Gnad,
et al., 2011).
9. BioGRID:
The BioGRID interaction database: 2017 update (Chatr-Aryamontri,
et al., 2017).
10. HPRD:
Human Protein Reference Database--2009 update (Keshava Prasad,
et al., 2009).
11. UniProt:
UniProt Protein Knowledgebase (Pundir,
et al., 2017).
12. O-GlycBase:
O-GLYCBASE version 4.0: a revised database of O-glycosylated proteins (Gupta,
et al., 1999).
13. PhosphoBase:
PhosphoBase, a database of phosphorylation sites: release 2.0 (Kreegipuu, et al. 1999).
14. mUbiSiDa:
mUbiSiDa: a comprehensive database for protein ubiquitination sites in mammals (Chen,
et al., 2014).
(10) DNA Methylation:
1. MethyCancer:
MethyCancer: the database of human DNA methylation and cancer (He,
et al., 2008).
2. TCGA:
Comprehensive genomic characterization defines human glioblastoma genes and core pathways (Cancer Genome Atlas Research Network,
2008).
3. ICGC:
International Cancer Genome Consortium Data Portal--a one-stop shop for cancer genomics data (Zhang, et al., 2011).
4. COSMIC:
COSMIC: exploring the world's knowledge of somatic mutations in human cancer (Forbes,
et al., 2014).
1. Human Protein Atlas:
The Human Protein Atlas as a proteomic resource for biomarker discovery (Pontén,
et al., 2011).
2. Human Proteome Map:
A draft map of the human proteome (Kim,
et al., 2014).
3. GPMDB:
The GPMDB REST interface (Fenyö, et al., 2015).
<2>
Public Databases for ubiquitin and ubiquitin-like conjugations:
1. UbiProt:
a new resouce of ubiquitinated proteins comprising information about protein properties and sources maintained by Ubiquitin Research Group at Central Research Laboratory of Nizhny Novgorod State Medical Academy (Russia) (Chernorudskiy,
et al., 2007).
2. SCUD:
a database of ubiquitin conjugation system in Saccharomyces cerevisiae, including E1s, E2s, E3s, substrates and deubiquitination enzymes (Lee,
et al., 2008).
3. plantsUPS:
a genomics database of ubiquitin conjugation system in plants including Arabidopsis, Rice, Poplar, Soybean, Grape, Medicago and Maize (Zhou,
et al., 2009).
4. PlantsUBQ:
a database of ubiquitin proteasome pathway in palnts and a project to describe the network of Arabidopsis ubiquitination proteins Funded by the National Science Foundation 2010 Program (USA).
5. hUbiquitome:
a database of human ubiquitin conjugation proteins and ubiquitin binding-site sequences
(Du,
et al., 2011).
6. E3NET:
a system of E3-substrate networks and a systematic framework to analyze E3-mediated regulatory networks in various cellular functions (Han,
et al., 2012).
7. PupDB:
a database of proteins with Prokaryotic ubiquitin-like protein(Pup) modification. It displays the structures of pupylated proteins and pupylation sites (Tung,
et al., 2012).
8. UUCD 1.0:
a comprehensive database of ubiquitin and ubiquitin-like conjugation contains E1s, E2s, E3s and DUBs from 70 eukaryotic species (Gao,
et al., 2013).
9. DUDE-db:
a database of ubiquitin (UB) and deubiquitinating (DUB) enzymes across multiple eukaryotic genomes (Hutchins,
et al., 2013).
10. Human E3 Ubiquitin Ligases:
a comprehensive database of human E3 ubiquitin ligases (Medvar,
et al., 2016).
11. UbSRD:
the ubiquitin structural relational database (Harrison,
et al., 2016).
<3> Computational Algorithms and Tools
(1) Ubiquitination:
1. Methods for the functional genomic analysis of ubiquitin ligases (Li,
et al., 2005). The
tool is not available.
2. Prediction of ubiquitin proteins using artificial neural networks, hidden Markov model and support vector machines (Jaiswal,
et al., 2007). The
tool is not available.
3. UbiPred:
a predictor to predict potential ubiquitination sites (Tung,
et al., 2008).
4. E3Miner:
a text mining tool to extract comprehensive knowledge of ubiquitin-protein ligases from available articles and databases (Lee,
et al., 2008).
5. UbPred:
a random forest predictor to identify potential ubiquitination sites from ubiquitinated substrates (Radivojac,
et al., 2010).
6. CKSAAP_UbSite:
a tool to predict ubiquitination sites from ubiquitinated protein sequences (Chen,
et al., 2011).
7. Prediction of lysine ubiquitination with mRMR feature selection and analysis (Cai,
et al., 2011). The
tool is not available.
8. GPS-ARM:
a novel software to predict D-boxes and KEN-boxes of APC/C-mediated substrates (Liu,
et al., 2012).
9. WPNNA:
a weighted passive nearest neighbor algorithm to predict ubiquitination sites (Feng,
et al., 2012). The
tool is not available.
10. Prediction of lysine ubiquitylation with ensemble classifier and feature selection (Zhao,
et al., 2012). The
tool is not available.
(2) Ubiquitin-like modification:
1. SUMOsp 1.0:
the old version of SUMOsp program for sumoylation site prediction (Xue,
et al., 2006).
2. SUMOsp 2.0:
a new SUMOsp program to specifically predict sumoylation sites in sumoylatd proteins. (Ren,
et al., 2009).
3. Predicting sumoylation site by feature selection method. (Cai,
et al., 2011). The
tool is not available.
4. GPS-PUP:
a predictor to predict pupylation sites in prokaryotic proteins (Liu,
et al., 2011).
