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http://harvard.eagle-i.net/i/0000012a-2518-fb6c-5617-794280000000

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 27, 2023. Core provides services: RT PCR service, Gene expression profiling service, Proteomics analysis service, Bioinformatics and Systems Biology analyses, Next Generation Sequencing Service, Affymetrix Human and Mouse Gene 2.0 ST Arrays and 2.1 ST Arrayplates. Core proteomics facility for the Dana-Farber/Harvard Cancer Center. Workflows and algorithms for analysis of next-generation sequencing data including RNA-Seq, ChIP-Seq, Epigenetics-Seq and DNA seq, Comprehensive workflow for analysis of Microbiome sequencing data, Integrated systems biology analysis of transcriptome, miRNA, epigenome, metabolomics and proteomics data. Pipelines: MALDI Tissue imaging and targeted quantitative proteomics.

Proper citation: Beth Israel Deaconess Medical Center Genomics Proteomics Bioinformatics and Systems Biology Center (RRID:SCR_009668) Copy   

•   Source: SciCrunch Registry

https://prokoplab.com/vistedd/

Database of SARS-CoV-2 and other viruses. Integrates structural and dynamic insights with viral evolution for proteins coded by virus. Each virus within database has workflow performed on each protein. Workflow consists of protein modeling, molecular dynamic simulations, evolutionary analysis, and mapping of protein-protein interactions. On page for each protein is link to individual protein data folder system, video of protein rotating with conservation, details of protein function, widget to purchase 3D print of protein at cost of production, amino acid movement from molecular dynamic simulations, and table of data for each amino acid of protein.

Proper citation: Viral Integrated Structural Evolution Dynamic Database (RRID:SCR_018793) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.biol.uoa.gr/ExTopoDB/

A publicly accessible database of experimentally derived topological models of transmembrane proteins. It contains experimental information about the topology of 2143 transmembrane proteins. This information was collected from studies in the literature that reported the use of biochemical methods for the determination of the topology of transmembrane proteins. Each record contains unique information about the given protein, such as its sequence, cross-references to many publicly available databases worldwide, the protein''s name and organism source. The web interface of the database offers the user the ability to submit advanced queries for text search within ExTopoDB''s protein entries and there is also an interface for running BLAST against the database. Furthermore, the results of topology prediction using the HMM-TM algorithm are included for each protein in the database (unconstrained prediction) and we also incorporated the experimental information about the topology of the proteins in the HMM-TM prediction procedure, producing more reliable topology models (constrained prediction).

Proper citation: ExTopoDB (RRID:SCR_013143) Copy   

•   Source: SciCrunch Registry

http://www.cdtdb.brain.riken.jp/CDT/Top.jsp

Transcriptomic information (spatiotemporal gene expression profile data) on the postnatal cerebellar development of mice (C57B/6J & ICR). It is a tool for mining cerebellar genes and gene expression, and provides a portal to relevant bioinformatics links. The mouse cerebellar circuit develops through a series of cellular and morphological events, including neuronal proliferation and migration, axonogenesis, dendritogenesis, and synaptogenesis, all within three weeks after birth, and each event is controlled by a specific gene group whose expression profile must be encoded in the genome. To elucidate the genetic basis of cerebellar circuit development, CDT-DB analyzes spatiotemporal gene expression by using in situ hybridization (ISH) for cellular resolution and by using fluorescence differential display and microarrays (GeneChip) for developmental time series resolution. The CDT-DB not only provides a cross-search function for large amounts of experimental data (ISH brain images, GeneChip graph, RT-PCR gel images), but also includes a portal function by which all registered genes have been provided with hyperlinks to websites of many relevant bioinformatics regarding gene ontology, genome, proteins, pathways, cell functions, and publications. Thus, the CDT-DB is a useful tool for mining potentially important genes based on characteristic expression profiles in particular cell types or during a particular time window in developing mouse brains.

Proper citation: Cerebellar Development Transcriptome Database (RRID:SCR_013096) Copy   

•   Source: SciCrunch Registry

http://dorina.mdc-berlin.de/rbp_browser/dorina.html

In animals, RNA binding proteins (RBPs) and microRNAs (miRNAs) post-transcriptionally regulate the expression of virtually all genes by binding to RNA. Recent advances in experimental and computational methods facilitate transcriptome-wide mapping of these interactions. It is thought that the combinatorial action of RBPs and miRNAs on target mRNAs form a post-transcriptional regulatory code. We provide a database that supports the quest for deciphering this regulatory code. Within doRiNA, we are systematically curating, storing and integrating binding site data for RBPs and miRNAs. Users are free to take a target (mRNA) or regulator (RBP and/or miRNA) centric view on the data. We have implemented a database framework with short query response times for complex searches (e.g. asking for all targets of a particular combination of regulators). All search results can be browsed, inspected and analyzed in conjunction with a huge selection of other genome-wide data, because our database is directly linked to a local copy of the UCSC genome browser. At the time of writing, doRiNA encompasses RBP data for the human, mouse and worm genomes. For computational miRNA target site predictions, we provide an update of PicTar predictions.

Proper citation: doRiNA (RRID:SCR_013222) Copy   

•   Source: SciCrunch Registry

http://proline.bic.nus.edu.sg/dedb/

Database on Drosophila melanogaster exons presented in a splicing graph form. Data is based on release 3.2 of the Drosophila melanogaster genome annotations available at FlyBase. The gene structure information extracted from the annotations were checked, clustered and transformed into splicing graph. The splicing graph form of the gene constructs were then used for classification of the various types of alternative splicing events. In addition, Pfam domains were mapped onto the gene structure. Users can query the database using the query page using BLAST, FlyBase Gene Name, FlyBase Gene Symbol, Pfam Accession Number and Pfam Identifier. This allows users to determine the Drosophila melanogaster homology of their gene using a BLAST search and to visualize the alternative splicing variants if any. Users can also determine genes containing a particular domain using the Pfam Accession Numbers and Identifiers.

Proper citation: Drosophila melanogaster Exon Database (RRID:SCR_013441) Copy   

•   Source: SciCrunch Registry

http://www.dbali.org

DBAli is a database that includes a comprehensive all-against-all comparison of protein structures in the PDB database. It is not currently being updated; however, updates should resume in the near future. All pairwise structural comparisons in DBAli have been obtained using the MAMMOTH program developed in the group of Prof. Angel R. Ortiz. All multiple structure alignments in DBAli have been obtained using the SALIGN command in MODELLER developed in the group of Prof. Andrej Sali.

Proper citation: DBAli. A Database of Structure Alignments. (RRID:SCR_013418) Copy   

•   Source: SciCrunch Registry

http://tcm.lifescience.ntu.edu.tw/index.html

TCMGeneDIT is a database system providing association information about traditional Chinese medicines (TCMs), genes, diseases, TCM effects and TCM ingredients automatically mined from vast amount of biomedical literature. Integrated protein-protein interaction and biological pathways information collected from public databases are also available. In addition, the transitive relationships among genes, TCMs and diseases could be inferred through the shared intermediates. Furthermore, TCMGeneDIT is useful in deducing possible synergistic or antagonistic contributions of the prescription components to the overall therapeutic effects. TCMGeneDIT is a unique database of various association information about TCMs. The database integrating TCMs with life sciences and biomedical studies would facilitate the modern clinical research and the understanding of therapeutic mechanisms of TCMs and gene regulations.

Proper citation: TCMGeneDIT (RRID:SCR_013396) Copy   

•   Source: SciCrunch Registry

http://mordred.bioc.cam.ac.uk/bipa

A database for protein-nucleic acid interaction that provides various features of protein-nucleic acid interfaces.
There are 2333 protein-nucleic acid PDB complexes, 9547 SCOP domains, and 9633 domain-nucleic acid interfaces in BIPA. BIPA also provides a multiple structural alignment of representative structures at the SCOP family level using the program SALIGN, and the structural alignments were further annotated using the program JOY to detect local environments of amino acids.

Proper citation: Biological Interaction database for Protein-nucleic Acid (RRID:SCR_013371) Copy   

•   Source: SciCrunch Registry

http://rarge.psc.riken.jp/rartf/

Database of complete sets of Arabidopsis transcription factors with a variety of information on Arabidopsis thaliana transcription factor families including: full-length cDNA sequences, Ds-tagged mutants, multiple sequences alignments of family members, phylogenic trees, functional motifs, and so on. In addition, expression profiles of all transcription factor genes are available.

Proper citation: RARTF (RRID:SCR_013457) Copy   

•   Source: SciCrunch Registry

http://flytrap.med.yale.edu/

The FlyTrap database presents the current results of large scale protein trapping screens that provide both information on which cells express each tagged gene, and subcellular localization of GFP-tagged proteins. Expression is under the control of endogenous promoter and enhancer elements, allowing for visualization of normal expression patterns. Drosophila proteins tagged with Green Fluorescent Protein (GFP) were created by insertion into genes of an artificial exon encoding GFP flanked by splice acceptor (SA) and splice donor (SD) sequences so that expression of GFP relies on splicing into mature mRNAs and in-frame fusion.

Proper citation: FlyTrap- GFP Protein Trap Database (RRID:SCR_013354) Copy   

•   Source: SciCrunch Registry

https://www.nist.gov/srd/nist-standard-reference-database-1a-v14

A library containing spectra upwards of 200,000 chemical compounds. Spectra include metabolites, peptides, contaminants, and lipids. All spectra and chemical structures are examined by professionals.

Proper citation: Mass Spectral Library (RRID:SCR_014668) Copy   

•   Source: SciCrunch Registry

http://epsd.biocuckoo.org/

Software tool as an annotated database of protein phosphorylation sites in eukaryotes. Contains experimentally identified and conserved p-sites which were collected from phosphoproteomic studies.

Proper citation: EPSD Eukaryotic Phosphorylation Site Database (RRID:SCR_016514) Copy   

•   Source: SciCrunch Registry

http://www.mrmatlas.org/

Resource of targeted proteomics assays to detect and quantify proteins in complex proteome digests by mass spectrometry. Used to quantify the complete human proteome.

Proper citation: SRMAtlas (RRID:SCR_016996) Copy   

•   Source: SciCrunch Registry

https://www.alzforum.org/alzpedia

Collection of brief summaries of various genes and proteins implicated in pathophysiology of Alzheimer’s disease and other neurodegenerative disorders. It will be expanded over time and updated periodically in order to reflect current state of knowledge.

Proper citation: ALZPEDIA (RRID:SCR_017548) Copy   

•   Source: SciCrunch Registry

http://bioinf.uab.es/aggrescan/

Web-based tool for identifying hot spots of aggregation in polypeptides. Aggrescan uses an aggregation-propensity scale for natural amino acids derived from in vivo experiments and on the assumption that short and specific sequence stretches modulate protein aggregation. The algorithm is shown to identify a series of protein fragments involved in the aggregation of disease-related proteins and to predict the effect of genetic mutations on their deposition propensities. It also provides new insights into the differential aggregation properties displayed by globular proteins, natively unfolded polypeptides, amyloidogenic proteins and proteins found in bacterial inclusion bodies.

Proper citation: Aggrescan: The Hot Spot Finder (RRID:SCR_008403) Copy   

•   Source: SciCrunch Registry

http://www.grt.kyushu-u.ac.jp/spad/

It is divided to four categories based on extracellular signal molecules (Growth factor, Cytokine, and Hormone) and stress, that initiate the intracellular signaling pathway. SPAD is compiled in order to describe information on interaction between protein and protein, protein and DNA as well as information on sequences of DNA and proteins. There are multiple signal transduction pathways: cascade of information from plasma membrane to nucleus in response to an extracellular stimulus in living organisms. Extracellular signal molecule binds specific intracellular receptor, and initiates the signaling pathway. Now, there is a large amount of information about the signaling pathway which controls the gene expression and cellular proliferation. We have developed an integrated database SPAD to understand the overview of signaling transduction.

Proper citation: Signaling Pathway Database (RRID:SCR_008243) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/msd-srv/ssm/

Secondary Structure Matching (SSM) is an interactive service for comparing protein structures in 3D. SSM compares to other protein matching services, see results here. It is used as a structure search engine in PISA service (Protein Interfaces, Surfaces and Assemblies). It queries may be launched from any web site, see instructions here and it is based on the CCP4 Coordinate Library, found here. The service provides for: -pairwise comparison and 3D alignment of protein structures -multiple comparison and 3D alignment of protein structures -examination of a protein structure for similarity with the whole PDB or SCOP archives -best Ca-alignment of compared structures -download and visualization of best-superposed structures using Rasmol (Unix/Linux platforms), Rastop (MS Windows machines) and Jmol (platform-independent server-side java viewer) -linking the results to other services - PDBe Motif, OCA, SCOP, GeneCensus, FSSP, 3Dee, CATH, PDBSum, SWISS-PROT and ProtoMap. Sponsors: The project is funded by the Collaborative Computational Project Number 4 in Protein Crystallography of the Biotechnology and Biological Sciences Research Council

Proper citation: Secondary Structure Matching (RRID:SCR_008365) Copy   

•   Source: SciCrunch Registry

http://pbil.univ-lyon1.fr/databases/homolens.php

Database of homologous genes from Ensembl organisms, structured under ACNUC sequence database management system. It allows to select sets of homologous genes among species, and to visualize multiple alignments and phylogenetic trees. It is possible to search for orthologous genes in a wide range of taxons. HOMOLENS is particularly useful for comparative sequence analysis, phylogeny and molecular evolution studies. More generally, HOMOLENS gives an overall view of what is known about a peculiar gene family. Note that HOMOLENS is split into two databases on this server: HOMOLENS contains the protein sequences while HOMOLENSDNA contains the nucleotide sequences. Protein sequences of HOMOLENS have been generated by translating the CDS of HOMOLENSDNA and using associated cross-references to generate the annotations.

Proper citation: Homologous Sequences in Ensembl Animal Genomes (RRID:SCR_008356) Copy   

•   Source: SciCrunch Registry

http://mips.gsf.de/proj/ppi/

The MIPS mammalian protein-protein interaction database (MPPI) is a new resource of high-quality experimental protein interaction data in mammals. The content is based on published experimental evidence that has been processed by human expert curators. It is a collection of manually curated high-quality PPI data collected from the scientific literature by expert curators. We took great care to include only data from individually performed experiments since they usually provide the most reliable evidence for physical interactions. To suit different users needs we provide a variety of interfaces to search the database: -Expert interface Simple but powerful boolean query language. -PPI search form Easy to use PPI search -Protein search Just find proteins of interest in the database Sponsors: This work is funded by a grant from the German Federal Ministry of Education and Research.

Proper citation: MIPS Mammalian Protein-Protein Interaction Database (RRID:SCR_008207) Copy   

•   Source: SciCrunch Registry