The INB operations are supported by installations and customization of common databases, as well as the databases developed by INB groups, including Firestar/FireDB labeling biding sites in protein structures, Ecid collection of experimental and predicted protein interactions in bacteria, or MODEL, a very large database of molecular Dynamics trajectories with the associated analysis tools.
| FireDB | More info |
FireDB is a database of annotated functionally important residues in protein structures.
Tags:
- Databases and Data Integration
- Biological Databases
- Protein Function and Structure Analysis
- Prediction of Functionally Important Residues
- Prediction of Ligand Binding
Urls:
FireDB is a database of PDB [http://www.rcsb.org/pdb] structures and their associated ligands. FireDB also contains the largest set of reliably annotated functionally important residues.
The whole PDB was clustered at 97% sequence identity and every chain mapped onto a consensus sequence from the cluster, so that important positions can be mapped and binding sites collapsed into the consensus sequence. Comparison of binding sites within a cluster of sequences gives an idea of the flexibility of those regions and the capability they have to bind different ligand analogs.
The whole PDB was clustered at 97% sequence identity and every chain mapped onto a consensus sequence from the cluster, so that important positions can be mapped and binding sites collapsed into the consensus sequence. Comparison of binding sites within a cluster of sequences gives an idea of the flexibility of those regions and the capability they have to bind different ligand analogs.
| E. coli Interaction Database (EcID) | More info |
The EcID database provides a common framework for exploring the sizable amount of protein interaction-related data available for Escherichia coli.
Tags:
- Databases and Data Integration
- Biological Databases
- Data Integration
- Protein-protein interaction
Urls:
The EcID database (E. coli Interaction Database) provides a common framework for exploring the sizable amount of protein interaction-related data available for Escherichia coli. EcID integrates information related with functional interactions extracted from the following sources: EcoCyc [http://ecocyc.org/] (metabolic pathways, protein complexes and regulatory information), KEGG [http://www.genome.jp/kegg/] (metabolic pathways) and MINT [http://mint.bio.uniroma2.it/mint/] (protein interactions). It also contains information on protein complexes from high throughput pull down experiments carried out in E. coli, and potential interactions directly extracted from the literature using the web-services associated to the iHOP [http://www.ihop-net.org/UniPub/iHOP/] text-mining system. Additionally, EcID incorporates results from two protein interaction prediction methods based on genomic information (Phylogenetic Profiles and Gene Neighborhoods) and three methods based on analysis of the potential co-evolution of the corresponding protein families (Mirror Tree, In Silico 2 Hybrid and Context Mirror). EcID associates to each predicted pair a confidence score that reflects the reliability of the functional interaction between those two proteins.
| INFRARED | More info |
INFRARED is a large and complete database with data from many different sources.
INFRARED stands up for INtegrated Functional and Regulatory Annotation RElational Database. It's a large and complete relational database with information form different sources as Ensembl [http://www.ensembl.org/], Reactome [http://www.reactome.org/] or HapMap [http://hapmap.ncbi.nlm.nih.gov/], and, also, with many information calculated by us like: Jaspar TFBS [http://jaspar.genereg.net/] or functional consequences of SNPs. We have been using INFRARED for years as an internal resource for several of our tools (e.g. Babelomics [http://www.babelomics.org/], GEPAS [http://www.gepas.org/] and PupaSuite [http://pupasuite.bioinfo.cipf.es/] among others) in order to connect different gene and protein identifiers among them and to a large collection of functional and regulatory properties for a considerable number of model and non-model organisms.
| ArchDB | More info |
ArchDB is a compilation of structural classifications of loops extracted from known protein structures.
Tags:
- Databases and Data Integration
- Data Integration
- Protein Function and Structure Analysis
- Protein Structure Prediction
- Protein Structural Analysis
Urls:
ArchDB is a compilation of structural classifications of loops extracted from known protein structures [http://www.rcsb.org/pdb/]. Loops in ArchDB have been classified using an improved version of the original ArchType program published in 1997 by Oliva et al. (Oliva B, Bates PA, Querol E, Aviles FX, Sternberg MJ. An automated classification of the structure of protein loops.J Mol Biol. 1997 Mar 7;266(4):814-30.) [http://www.ncbi.nlm.nih.gov/pubmed/9102471?dopt=Abstract]. Conformational clusters and consensus sequences have been derived by computational analysis for loops from SCOP 40 database. Loops have been classified into five types (alpha-alpha, beta-beta links, beta-beta hairpins, alpha-beta and beta-alpha) according to the secondary structures they embrace.
| IntOGen | More info |
IntOGen (Integrative OncoGenomics) is a resource that integrates multidimensional data for the identification of genes involved in cancer development.
Tags:
- Databases and Data Integration
- Biological Databases
- Database Retrieval and Visualization
- Data Integration
- Clinical and Biomedical Applications
- Biomedical Applications
- Ontologies
- Ontology Viewer
Urls:
Integrative OncoGenomics (IntOGen), a discovery tool for cancer researchers, is a resource that integrates multidimensional OncoGenomics Data for the identification of genes and groups of genes (biological modules) involved in cancer development.
