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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://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://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://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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https://github.com/cobilab/altair

Software C toolkit for alignment free and spatial temporal analysis of multi-FASTA data. Used for entangling presence of multiple sequences from epidemic and pandemic events.

Proper citation: AltaiR (RRID:SCR_024752) Copy   

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https://hive.biochemistry.gwu.edu/dna.cgi?cmd=tissue_codon_usage&id=586358&mode=cocoputs

Database includes genomic codon-pair and dinucleotide statistics of all organisms with sequenced genome. Facilitates genetic variation analyses and recombinant gene design. Derived from all available GenBank and RefSeq data.

Proper citation: Codon and Codon-Pair Usage Tables (RRID:SCR_018504) Copy   

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https://sites.google.com/a/blueprint.org/trades/

With Trajectory Directed Ensemble Sampling (TraDES) create large ensembles of high-quality protein structures quickly, ranging from near-native to partially unfolded to intrinsically unfolded. TraDES is a system for directly controlling and sampling protein conformational space. TraDES has been previously used for measuring the vastness of protein conformational space and testing the hypothesis of a brute force solution to the protein folding problem. Over 10 Billion protein structures have been produced by TraDES software in previous distributed computing experiments. The package is comprised of binary executable programs and accessory programs and scripts as well as protein structure data files that map out protein conformational space in a probabilistic way. The main programs are: * trades - generates protein structures following the Trajectory Distribution (see below) * seq2trj - makes Trajectory Distributions from sequences for sampling * str2tr - makes Trajectory Distributions from 3D structures for sampling Trajectory Distributions - Controlling the Sampling of Conformational Space The concept of the trajectory distribution may be new to many protein scientists. A trajectory distribution is simply a map of available conformational space at an amino acid residue. NMR scientists are the primary users of the TraDES package.

Proper citation: TraDES (RRID:SCR_006142) Copy   

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http://www.ncbi.nlm.nih.gov/igblast/

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on January 4,2023. IgBLAST was developed at NCBI to facilitate analysis of immunoglobulin V region sequences in GenBank. In addition to performing a regular BLAST search, IgBLAST has several additional functions: - Reports the germline V, D and J gene matches to the query sequence. - Annotates the immunoglobulin domains (FWR1 through FWR3). - Matches the returned hits (for databases other than germline genes) to the closest germline V genes, making it easier to identify related sequences. - Reveals the V(D)J junction details such as nucleotide homology between the ends of V(D)J segments and N nucleotide insertions. D and J gene reporting is only for nucleotide sequence search and requires a stretch of five or more nucleotide identity between the query and D or J genes. Sponsors: This resource is supported by the National Center for Biotechnology Information, a division of the U.S. National Library of Medicine.

Proper citation: IgBLAST (RRID:SCR_002873) Copy   

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http://cgap.nci.nih.gov/Chromosomes/Mitelman

The web site includes genomic data for humans and mice, including transcript sequence, gene expression patterns, single-nucleotide polymorphisms, clone resources, and cytogenetic information. Descriptions of the methods and reagents used in deriving the CGAP datasets are also provided. An extensive suite of informatics tools facilitates queries and analysis of the CGAP data by the community. One of the newest features of the CGAP web site is an electronic version of the Mitelman Database of Chromosome Aberrations in Cancer. The data in the Mitelman Database is manually culled from the literature and subsequently organized into three distinct sub-databases, as follows: -The sub-database of cases contains the data that relates chromosomal aberrations to specific tumor characteristics in individual patient cases. It can be searched using either the Cases Quick Searcher or the Cases Full Searcher. -The sub-database of molecular biology and clinical associations contains no data from individual patient cases. Instead, the data is pulled from studies with distinct information about: -Molecular biology associations that relate chromosomal aberrations and tumor histologies to genomic sequence data, typically genes rearranged as a consequence of structural chromosome changes. -Clinical associations that relate chromosomal aberrations and/or gene rearrangements and tumor histologies to clinical variables, such as prognosis, tumor grade, and patient characteristics. It can be searched using the Molecular Biology and Clinical (MBC) Associations Searcher -The reference sub-database contains all the references culled from the literature i.e., the sum of the references from the cases and the molecular biology and clinical associations. It can be searched using the Reference Searcher. CGAP has developed six web search tools to help you analyze the information within the Mitelman Database: -The Cases Quick Searcher allows you to query the individual patient cases using the four major fields: aberration, breakpoint, morphology, and topography. -The Cases Full Searcher permits a more detailed search of the same individual patient cases as above, by including more cytogenetic field choices and adding search fields for patient characteristics and references. -The Molecular Biology Associations Searcher does not search any of the individual patient cases. It searches studies pertaining to gene rearrangements as a consequence of cytogenetic aberrations. -The Clinical Associations Searcher does not search any of the individual patient cases. It searches studies pertaining to clinical associations of cytogenetic aberrations and/or gene rearrangements. -The Recurrent Chromosome Aberrations Searcher provides a way to search for structural and numerical abnormalities that are recurrent, i.e., present in two or more cases with the same morphology and topography. -The Reference Searcher queries only the references themselves, i.e., the references from the individual cases and the molecular biology and clinical associations. Sponsors: This database is sponsored by the University of Lund, Sweden and have support from the Swedish Cancer Society and the Swedish Children''s Cancer Foundation

Proper citation: Mitelman Database of Chromosome Aberrations in Cancer (RRID:SCR_012877) Copy   

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http://www.informatics.jax.org/

Community model organism database for laboratory mouse and authoritative source for phenotype and functional annotations of mouse genes. MGD includes complete catalog of mouse genes and genome features with integrated access to genetic, genomic and phenotypic information, all serving to further the use of the mouse as a model system for studying human biology and disease. MGD is a major component of the Mouse Genome Informatics.Contains standardized descriptions of mouse phenotypes, associations between mouse models and human genetic diseases, extensive integration of DNA and protein sequence data, normalized representation of genome and genome variant information. Data are obtained and integrated via manual curation of the biomedical literature, direct contributions from individual investigators and downloads from major informatics resource centers. MGD collaborates with the bioinformatics community on the development and use of biomedical ontologies such as the Gene Ontology (GO) and the Mammalian Phenotype (MP) Ontology.

Proper citation: Mouse Genome Database (RRID:SCR_012953) Copy   

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http://www.syfpeithi.de/

SYFPEITHI is a database comprising more than 7000 peptide sequences known to bind class I and class II MHC molecules. The entries are compiled from published reports only. It contains a collection of MHC class I and class II ligands and peptide motifs of humans and other species, such as apes, cattle, chicken, and mouse, for example, and is continuously updated. Searches for MHC alleles, MHC motifs, natural ligands, T-cell epitopes, source proteins/organisms and references are possible. Hyperlinks to the EMBL and PubMed databases are included. In addition, ligand predictions are available for a number of MHC allelic products. The database is based on previous publications on T-cell epitopes and MHC ligands. It contains information on: -Peptide sequences -anchor positions -MHC specificity -source proteins, source organisms -publication references Since the number of motifs continuously increases, it was necessary to set up a database which facilitates the search for peptides and allows the prediction of T-cell epitopes. The prediction is based on published motifs (pool sequencing, natural ligands) and takes into consideration the amino acids in the anchor and auxiliary anchor positions, as well as other frequent amino acids. The score is calculated according to the following rules: The amino acids of a certain peptide are given a specific value depending on whether they are anchor, auxiliary anchor or preferred residue. Ideal anchors will be given 10 points, unusual anchors 6-8 points, auxiliary anchors 4-6 and preferred residues 1-4 points. Amino acids that are regarded as having a negative effect on the binding ability are given values between -1 and -3. Sponsors: SYFPEITHI is supported by DFG-Sonderforschungsbereich 685 and theEuropean Union: EU BIOMED CT95-1627, BIOTECH CT95-0263, and EU QLQ-CT-1999-00713.

Proper citation: SYFPEITHI: A Database for MHC Ligands and Peptide Motifs (RRID:SCR_013182) Copy   

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http://xin.cz3.nus.edu.sg/group/trmp/trmp.asp

The Therapeutically Relevant Multiple Pathways Database is designed to provide information about such multiple pathways and related therapeutic targets described in the literatures, the targeted disease conditions, and the corresponding drugs/ligands directed at each of these targets. This database currently contains 11 entries of multiple pathways, 97 entries of individual pathways, 120 targets covering 72 disease conditions along with 120 sets of drugs directed at each of these targets. Each entry can be retrieved through multiple methods including multiple pathway name, individual pathway name and disease name. Additional information provided include protein name, synonyms, Swissprot AC number, species, gene name and location, protein sequence (AASEQ) and gene sequence (NTSEQ) as well as potential therapeutic implications while applicable. Cross-links to other databases are provided which include Genecard, GDB, Locuslink, NCBI, KEGG, OMIM, SwissProt to facilitate the access of more detailed information about various aspects of the particular target or non-target protein. Queries can be submitted by entering or selecting the required information in any one or combination of the fields in the form. User can specify full name or any part of the name in a text field, or choose one item from an selection field. Sponsors: TRMP is supported by the National University of Singapore.

Proper citation: Therapeutically Relevant Multiple Pathways Database (RRID:SCR_013471) Copy   

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http://www.vivo.colostate.edu/molkit/manip/#

A software tool that allows users to input a DNA (or RNA) sequence and obtain its inverse, complement or inverse complement. The program can also be used to display a DNA sequence and its complement in double-stranded format. Functions after users paste a DNA sequence into the upper text box, then click the appropriate button to place a manipulated form of the sequence in the lower text box.

Proper citation: Manipulate and Display a DNA Sequence (RRID:SCR_013470) Copy   

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https://dbaasp.org

Collection of manually curated data regarding structure and antimicrobial activity of natural and synthetic peptides. Provides the information and analytical resources to develop antimicrobial compounds with the high therapeutic index.

Proper citation: Database of Antimicrobial Activity and Structure of Peptides (RRID:SCR_016600) Copy   

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http://www.regulomedb.org/

Database that annotates SNPs with known and predicted regulatory elements in intergenic regions of H. sapiens genome. Known and predicted regulatory DNA elements include regions of DNAase hypersensitivity, binding sites of transcription factors, and promoter regions that have been biochemically characterized to regulation transcription. Source of these data include public datasets from GEO, ENCODE project, and published literature.

Proper citation: RegulomeDB (RRID:SCR_017905) Copy   

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http://meme-suite.org/tools/dreme

Software tool to discover short, ungapped motifs (recurring, fixed-length patterns) that are relatively enriched in sequences compared with shuffled sequences or control sequences (sample output from sequences).

Proper citation: DREME (RRID:SCR_016860) 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://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   

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http://animal.dna.affrc.go.jp/agp/index.html

Database of comparative gene mapping between species to assist the mapping of the genes related to phenotypic traits in livestock. The linkage maps, cytogenetic maps, polymerase chain reaction primers of pig, cattle, mouse and human, and their references have been included in the database, and the correspondence among species have been stipulated in the database. AGP is an animal genome database developed on a Unix workstation and maintained by a relational database management system. It is a joint project of National Institute of Agrobiological Sciences (NIAS) and Institute of the Society for Techno-innovation of Agriculture, Forestry and Fisheries (STAFF-Institute), under cooperation with other related research institutes. AGP also contains the Pig Expression Data Explorer (PEDE), a database of porcine EST collections derived from full-length cDNA libraries and full-length sequences of the cDNA clones picked from the EST collection. The EST sequences have been clustered and assembled, and their similarity to sequences in RefSeq, and UniGene determined. The PEDE database system was constructed to store sequences and similarity data of swine full-length cDNA libraries and to make them available to users. It provides interfaces for keyword and ID searches of BLAST results and enables users to obtain sequence data and names of clones of interest. Putative SNPs in EST assemblies have been classified according to breed specificity and their effect on coding amino acids, and the assemblies are equipped with an SNP search interface. The database contains porcine nucleotide sequences and cDNA clones that are ready for analyses such as expression in mammalian cells, because of their high likelihood of containing full-length CDS. PEDE will be useful for researchers who want to explore genes that may be responsible for traits such as disease susceptibility. The database also offers information regarding major and minor porcine-specific antigens, which might be investigated in regard to the use of pigs as models in various medical research applications.

Proper citation: Animal Genome Database (RRID:SCR_008165) 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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