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http://compbio.soe.ucsc.edu/yeast_introns.html

Database of information about the spliceosomal introns of the yeast Saccharomyces cerevisiae. Listed are known spliceosomal introns in the yeast genome and the splice sites actually used are documented. Through the use of microarrays designed to monitor splicing, they are beginning to identify and analyze splice site context in terms of the nature and activities of the trans-acting factors that mediate splice site recognition. In version 3.0, expression data that relates to the efficiency of splicing relative to other processes in strains of yeast lacking nonessential splicing factors is included. These data are displayed on each intron page for browsing and can be downloaded for other types of analysis.

Proper citation: Yeast Intron Database (RRID:SCR_007144) Copy   

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http://probeexplorer.cicancer.org/principal.php

Probe Explorer is an open access web-based bioinformatics application designed to show the association between microarray oligonucleotide probes and transcripts in the genomic context, but flexible enough to serve as a simplified genome and transcriptome browser. Coordinates and sequences of the genomic entities (loci, exons, transcripts), including vector graphics outputs, are provided for fifteen metazoa organisms and two yeasts. Alignment tools are used to built the associations between Affymetrix microarrays probe sequences and the transcriptomes (for human, mouse, rat and yeasts). Search by keywords is available and user searches and alignments on the genomes can also be done using any DNA or protein sequence query. Platform: Online tool

Proper citation: ProbeExplorer (RRID:SCR_007116) Copy   

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http://www.broadinstitute.org/annotation/tetraodon/

This database have been funded by the National Human Genome Research Institute (NHGRI) to produce shotgun sequence of the Tetraodon nigriviridis genome. The strategy involves Whole Genome Shotgun (WGS) sequencing, in which sequence from the entire genome is generated. Whole genome shotgun libraries were prepared from Tetraodon genomic DNA obtained from the laboratory of Jean Weissenbach at Genoscope. Additional sequence data of approximately 2.5X coverage of Tetraodon has also been generated by Genoscope in plasmid and BAC end reads. Broad and Genoscope intend to pool their data and generate whole genome assemblies. Tetraodon nigroviridis is a freshwater pufferfish of the order Tetraodontiformes and lives in the rivers and estuaries of Indonesia, Malaysia and India. This species is 20-30 million years distant from Fugu rubripes, a marine pufferfish from the same family. The gene repertoire of T. nigroviridis is very similar to that of other vertebrates. However, its relatively small genome of 385 Mb is eight times more compact than that of human, mostly because intergenic and intronic sequences are reduced in size compared to other vertebrate genomes. These genome characteristics along with the large evolutionary distance between bony fish and mammals make Tetraodon a compact vertebrate reference genome - a powerful tool for comparative genetics and for quick and reliable identification of human genes.

Proper citation: Tetraodon nigroviridis Database (RRID:SCR_007123) Copy   

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http://net.icgeb.org/benchmark/

It was created in order to create standard datasets on which the performance of machine learning methods can be compared. The collection contains datasets of sequences and structures, each subdivided into positive/negative training/test sets. Such a subdivision is called a classification task. Typical tasks include the classification of structural domains in the SCOP and CATH databases based on their sequences, as fell as various functional and taxonomic classification tasks. Running a performance evaluation test on an entire database can include many different classification tasks. These ensembles of classification tasks are encoded in a simple matrix format - called the cast matrix or membership table - that specifies the role of each sequence (or structure) in the different calculations. Each column of this matrix is a subdivision of the objects (rows) into positive/negative training/test sets. Typically, a database record contains such an ensemble of classification tasks, encoded in a single cast matrix. In addition, there is a collection of distance matrices that contain an all vs. all comparison of the datasets using methods as BLAST, Smith-Waterman, 3D-comparisons etc. Evaluation of a method on a given database consists of calculating a performance measure such as a receiver operating curve (ROC) AUC value. Results of evaluation are deposited along with the data, each dataset is evaluated at least by one classification method, such as 1NN (nearest neighbour) or SVM (support vector machines), ANN (artificial neural networks), RF (random forests) etc.. There are small datasets meant for program developers, as well as downloadable programs for various classification algorithms.

Proper citation: Protein Classification Benchmark Collection (RRID:SCR_007561) Copy   

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http://cmckb.cellmigration.org

It is a database of keys facts about proteins, families, and complexes involved in cell migration. This ongoing project provides a large amount of automated and curated data, collected from numerous online resources that are updated monthly. These data include names, synonyms, sequence information, summaries, CMC research data, reagents, structures, as well as protein family and complex details. CMKB''s ultimate goal is to create a database that will enable the cell migration community to conveniently access significant information about molecules of interest. This will also serve as a stepping stone to pathway analysis and demonstrate how these molecules coordinate with one another during cell adhesion and movement. Sponsors: This resource is supported by the Cell Migration Consortium.

Proper citation: CMKB (RRID:SCR_007229) Copy   

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http://statgen.ncsu.edu/asg/

Alternative splicing essentially increases the diversity of the transcriptome and has important implications for physiology, development and the genesis of diseases. This resource uses a different approach to investigate alternative splicing (instead of the conventional case-by case fashion) and integrates all transcripts derived from a gene into a single splicing graph. ASG is a database of splicing graphs for human genes, using transcript information from various major sources (Ensembl, RefSeq, STACK, TIGR and UniGene). Each transcript corresponds to a path in the graph, and alternative splicing is displayed by bifurcations. This representation preserves the relationships between different splicing variants and allows us to investigate systematically all possible putative transcripts. Web interface allows users to display the splicing graphs, to interactively assemble transcripts and to access their sequences as well as neighboring genomic regions. ASG also provide for each gene, an exhaustive pre-computed catalog of putative transcriptsin total more than 1.2 million sequences. It has found that ~65 of the investigated genes show evidence for alternative splicing, and in 5 of the cases, a single gene might produce over 100 transcripts.

Proper citation: Alternate splicing gallery (RRID:SCR_008129) Copy   

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http://kinasedb.ontology.ims.u-tokyo.ac.jp

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. KinasePathwayDatabase is an integrated database concerning completed sequenced major eukaryotes, which contains the classification of protein kinases and their functional conservation and orthologous tables among species, protein-protein interaction data, domain information, structural information, and automatic pathway graph image interface. The protein-protein interactions are extracted by natural language processing (NLP) from abstracts using basic word pattern and protein name dictionary GENA: developed by our group. In this system, pathways are easily compared among species using protein interactions data more than 47,000 and orthologous tables.

Proper citation: Kinase Pathway Database (RRID:SCR_008199) Copy   

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http://www.roselab.jhu.edu/coil/

The Protein Coil Library is a library of protein structure fragments derived from the Protein Data Bank (PDB). The fragments in this library are those fragments in the PDB that cannot be classified as either alpha-helix or beta-strand. Three-dimensional structures as well as side-chain and backbone torsion angles are stored in the database. The Protein Coil Library allows rapid and comprehensive access to non-alpha-helix and non-beta-strand fragments contained in the Protein Data Bank (PDB). The library contains both sequence and structure information together with calculated torsion angles for both the backbone and side chains. Several search options are implemented, including a query function that uses output from popular PDB-culling servers directly. Additionally, several popular searches are stored and updated for immediate access. The library is a useful tool for exploring conformational propensities, turn motifs, and a recent model of the unfolded state. The library stores the complete torsion angle descriptions for the fragments as well as the three dimensional structures of the fragments themselves. The goal of extracting and pre-calculating this data is to allow for more straightforward investigation of peptide structure without the background of secondary structure elements. In addition to searching by PDB ID, it is possible to download a particular size class, perform a batch search of PDB/chain ID''s, or download precompiled lists of PDB ID''s of interest (PDB Select, etc.). For users interested in browsing the entire database at once or maintaining their own locally-updated copy of the library, FTP access instructions are also provided. The files stored in the coil library FTP site or returned after a batch search are organized heirarchically by PDB ID. This is done to reduce filesystem access times and fascilitate searches using the UNIX find utility. At the lowest directory level in the heirarchy, files are further sorted by fragment length. As a result, the number of files in a particular directory is generally less then 50, yielding relatively fast access on UNIX/Linux filesystems. The heirarchical organization is based on the middle two letters of the PDB ID. For example, hen egg lysozyme, which has a PDB ID of 1HEL, will be located in the directory h/he/. At the final level, fragments of varying sizes are stored in directories that correspond to their fragment length. Again, using lysozyme as an example, any seven-residue fragments, if they exist, will reside in the directory h/he/7/. Similarly, seven-residue fragments from 2HEX and 1HE0 will also be in this location. Sponsors: The Protein Coil Library is funded by Johns Hopkins University.

Proper citation: The Protein Coil Library (RRID:SCR_008233) Copy   

•   Source: SciCrunch Registry

http://pbil.univ-lyon1.fr/acuts/ACUTS.html

THIS RESOURCE IS NO LONGER IN SERVICE, Documented on August 12, 2014. Database that identifies new regulatory elements in untranslated regions of protein-coding genes (5 prime flanks, 5 prime UTRs, introns, 3 prime UTRs and 3 prime flanks). The analyses is focused on genes from metazoan species (essentially vertebrates, insects and nematodes). Information on highly conserved regions (sequences, alignments, annotations, bibliographic references) are compiled. Currently 176 out of 326 detected highly conserved regions (HCRs) have been analyzed and incorporated in the database. You can also access the list of annotated conserved elements and the list of conserved elements that remain to be processed. Their approach is based on comparative sequence analysis, for the identification of phylogenetic footprints.

Proper citation: Ancient conserved untranslated sequences (RRID:SCR_008130) Copy   

•   Source: SciCrunch Registry

http://www-personal.umich.edu/~jianghui/rseq/

A software toolkit for RNA sequence data analysis. It contains programs that cover several aspects of RNA-Seq data analysis such as read quality assessment, reference sequence generation, sequence mapping, and gene and isoform expressions estimations.

Proper citation: rSeq (RRID:SCR_000562) Copy   

•   Source: SciCrunch Registry

http://www.glycosciences.de/tools/GlycoFragments/

Service that calculates and displays the main fragments (Band C-, Z- and Y-, A- and X-ions) of oligosaccharides that should occur in MS-spectra. The extended ASCII nomenclature as recommended by IUPAC is used to input the sequence of complex oligosaccharides. However, some additional input rules have to be fulfilled. In case only the topology and composition of the oligosaccharide is known, a simpler way to input carbohydrate sequences is possible. Since the hydroxyl groups of synthetic carbohydrates are often the are protected they have included a way to indicate if sugar residue are persubstituted. Please have a look at the examples of valid input structures.

Proper citation: GlycoFragment (RRID:SCR_001573) Copy   

•   Source: SciCrunch Registry

https://services.healthtech.dtu.dk/services/DictyOGlyc-1.1/

Server that produces neural network predictions for GlcNAc O-glycosylation sites in Dictyostelium discoideum proteins.

Proper citation: DictyOGlyc (RRID:SCR_001600) Copy   

•   Source: SciCrunch Registry

http://mirna.imbb.forth.gr/SSCprofiler.html

Tool which can be used to identify novel miRNA gene candidates in the human genome.

Proper citation: SSCprofiler (RRID:SCR_001282) Copy   

•   Source: SciCrunch Registry

http://www.thearkdb.org/

The ArkDB database system aims to provide a comprehensive public repository for genome mapping data from farmed and other animal Species. The system also aims to provide a route in to genomic and other sequence from the initial viewpoint of linkage mapping, RH mapping, physical mapping or - possibly more importantly - QTL mapping data. Sponsors: ArkDB is funded by Biotechnology and Biological Sciences Research Council (BBSRC), UK. Cat, Chicken, Cow, Deer, Duck, Horse, Pig, Quail, Salmon, Sea Bass, Sheep, Turkey, QLT map, Linkage map, RH map, Farm animal, Genome map, Sequence, Mapping

Proper citation: ArkDB - Genomes For The Rest of Us (RRID:SCR_001838) Copy   

•   Source: SciCrunch Registry

https://cell-innovation.nig.ac.jp/GNP/index_e.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Integrated database of experiment data generated by participating research institutes and public databases relating to: 1) transcription starting position of human genes in the human genome, 2) conjunction to control region on transcriptional factors and the human genome 3) protein-protein interaction with a central focus on transcription factors organized for use in genome level research. Gene Search is the function to search the integrated database by using keywords and public IDs. The search results can be visualized by: * Genome Explorer : provides annotation of landmarks (genes, transcription start sites, etc.) aligned in accordance with their genome locations. * PPI Network : provides a graphical view of protein-protein interaction (PPI) network from the experimental data generated under the project and the public datasets. * Expression Profile : clusters genes by expression pattern and display the result with heatmap. The function provides genes which have relation of coregulation and anti-coregulation. * Comparison Viewer : This function gives the view to compare the genomic regions between human and mouse homologous genes. The viewer shows the distribution of transcription start sites (TSS) as the way of separable by tissues or time points with other landmarks on genome region. * Gene Stock : This is the function to save the gene list that you are interested until the session is closed.

Proper citation: Genome Network Platform (RRID:SCR_001737) Copy   

•   Source: SciCrunch Registry

http://services.bio.ifi.lmu.de:1046/AutoPSIDB/

Searchable database for predicted protein sequences and structures. It has the ability to search through PDB ID, UniProt ID, and descriptive classifiers.

Proper citation: AutoPSI database of predicted SCOP classifications (RRID:SCR_001923) Copy   

•   Source: SciCrunch Registry

http://pepbank.mgh.harvard.edu/

A database of peptides based on sequence text mining and public peptide data sources. Only peptides that are 20 amino acids or shorter are stored. Only peptides with available sequences are stored. After submitting a query you can further refine the results using the new heat map retrieval tool to quickly find the entries that are most relevant to you. Text classification helps you find candidate peptides that are related to cancer, cardiovascular diseases, diabetes, apoptosis, angiogenesis and molecular imaging or peptides for which binding data exist.

Proper citation: PepBank Peptide Database (RRID:SCR_002086) Copy   

•   Source: SciCrunch Registry

http://www.cbil.upenn.edu/ParaDBs/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on October 28,2025. These databases were constructed by extracting the organism specific ESTs from dbEST, removing polyA sequences from the ends and trimming 5' and 3' regions with greater than 25% N's in a 20 base pair window. These quality sequences were then aligned using the cap2 program and the consensus sequences thus generated put into a database that is available on the web. A number of parasitic organisms were chosen that have between 3000 and 15000 ESTs. The attempt here is to provide useful information and analyses to the scientific community without curating the results in any way. A total of 55192 ESTs, deposited into dbEST/GenBank, were included in the analyses. The resulting sequences have been clustered into nonredundant gene assemblies and deposited into a relational database that supports a variety of sequence and text searches. This database has been used to compare the gene assemblies using BLAST similarity comparisons to the public protein databases to identify putative genes. Of these new entries, approximately 15%-20% represent putative homologs with a conservative cutoff of p < 10(-9), thus identifying many conserved genes that are likely to share common functions with other well-studied organisms. Gene assemblies were also used to identify strain polymorphisms, examine stage-specific expression, and identify gene families. An interesting class of genes that are confined to members of this phylum and not shared by plants, animals, or fungi, was identified. These genes likely mediate the novel biological features of members of the Apicomplexa and hence offer great potential for biological investigation and as possible therapeutic targets.

Proper citation: Parasite Databases of Clustered ESTs (RRID:SCR_002262) Copy   

•   Source: SciCrunch Registry

http://www.transcriptionfactor.org/index.cgi?Home

Database of predicted transcription factors in completely sequenced genomes. The predicted transcription factors all contain assignments to sequence specific DNA-binding domain families. The predictions are based on domain assignments from the SUPERFAMILY and Pfam hidden Markov model libraries. Benchmarks of the transcription factor predictions show they are accurate and have wide coverage on a genomic scale. The DBD consists of predicted transcription factor repertoires for 930 completely sequenced genomes.

Proper citation: DBD: Transcription factor prediction database (RRID:SCR_002300) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/compneur-srv/LGICdb/

Database providing access to information about transmembrane proteins that exist under different conformations, with three primary subfamilies: the cys-loop superfamily, the ATP gated channels superfamily, and the glutamate activated cationic channels superfamily. Due to the lack of evolutionary relationship, these three superfamilies are treated separately. It currently contains 554 entries of ligand-activated ion channel subunits. In this database one may find: the nucleic and proteic sequences of the subunits. Multiple sequence alignments can be generated, and some phylogenetic studies of the superfamilies are provided. Additionally, the atomic coordinates of subunits, or portion of subunits, are provided when available. Redundancy is kept to a minimum, i.e. one entry per gene. Each entry in the database has been manually constructed and checked by a researcher of the field in order to reduce the inaccuracies to a minimum. NOTE: This database is not actively maintained anymore. People should not consider it as an up-to-date trustable resource. For any new work, they should consider using alternative sources, such as UniProt, Ensembl, Protein Databank etc.

Proper citation: Ligand-Gated Ion Channel Database (RRID:SCR_002418) Copy   

•   Source: SciCrunch Registry