Tools   Select Another Resource Report Type

http://www.brenda-enzymes.org/

Database for functional enzyme and ligand-related information maintained as part of the German ELIXIR Node. Provides advanced query systems, evaluation tools, and various visualization options for the detailed assessment of enzyme properties. Enzyme data in BRENDA are classified according to the Enzyme Commission (EC) nomenclature of IUBMB.

Proper citation: BRENDA (RRID:SCR_002997) Copy   

•   Source: SciCrunch Registry

http://khavarilab.stanford.edu/resources.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 6, 2023. An intersection-based pathogen detection workflow that utilizes a user-provided custom reference genome set for identification of nonhuman sequences in deep sequencing datasets. This is a package recommended for advanced users only.

Proper citation: RINS (RRID:SCR_003652) Copy   

•   Source: SciCrunch Registry

https://github.com/benedictpaten/pecan

A Java consistency based multiple sequence alignment software program.

Proper citation: Pecan (RRID:SCR_001909) Copy   

•   Source: SciCrunch Registry

http://www.well.ox.ac.uk/~kgaulton/chaos.shtml

A Perl-based system for annotation of variants identified in high-throughput sequencing experiments. Functionality includes annotation of variants with information relating to population genetics, known transcripts, positional records, and sequence motif-based prediction. In addition, annotated variants can be summarized and extracted to facilitate downstream analysis. There is also basic support for gene-based biological annotation, and eventually will include tools for variant and genotype analysis and visualization.

Proper citation: CHAoS (RRID:SCR_005174) Copy   

•   Source: SciCrunch Registry

http://cbrc.kaust.edu.sa/readscan/

A highly scalable parallel software program to identify non-host sequences (of potential pathogen origin) and estimate their genome relative abundance in high-throughput sequence datasets.

Proper citation: READSCAN (RRID:SCR_005204) Copy   

•   Source: SciCrunch Registry

http://metagenomics.atc.tcs.com/binning/ProViDE/

A similarity based binning algorithm that uses a customized set of alignment parameter thresholds / ranges, specifically suited for the accurate taxonomic labelling of viral metagenomic sequences., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ProViDE (RRID:SCR_004709) Copy   

•   Source: SciCrunch Registry

http://metagenomics.atc.tcs.com/binning/DiScRIBinATE/

Software for accurate taxonomic classification of metagenomic sequences using a similarity based binning method. User needs to perform a similarity search of the input metagenomic sequences (reads) against the nr protein database using BLASTx search. The generated blastx output is then taken as the input by the DiScRIBinATE program.

Proper citation: DiScRIBinATE (RRID:SCR_004862) Copy   

•   Source: SciCrunch Registry

http://metaphyler.cbcb.umd.edu/

A taxonomic classifier for metagenomic shotgun reads, which uses phylogenetic marker genes as a taxonomic reference. The classifier, based on BLAST, uses different thresholds (automatically learned from the reference database) for each combination of taxonomic rank, reference gene, and sequence length. The reference database includes marker genes from all complete genomes, several draft genomes and the NCBI nr protein database.

Proper citation: MetaPhyler (RRID:SCR_004848) Copy   

•   Source: SciCrunch Registry

http://www.ensembl.org/

Collection of genome databases for vertebrates and other eukaryotic species with DNA and protein sequence search capabilities. Used to automatically annotate genome, integrate this annotation with other available biological data and make data publicly available via web. Ensembl tools include BLAST, BLAT, BioMart and the Variant Effect Predictor (VEP) for all supported species.

Proper citation: Ensembl (RRID:SCR_002344) Copy   

•   Source: SciCrunch Registry

http://droog.gs.washington.edu/polyphred/

Software program that compares fluorescence-based sequences across traces obtained from different individuals to identify heterozygous sites for single nucleotide substitutions. Its functions are integrated with the use of three other programs: Phred (Brent Ewing and Phil Green), Phrap (Phil Green), and Consed (David Gordon and Phil Green). PolyPhred identifies potential heterozygotes using the base calls and peak information provided by Phred and the sequence alignments provided by Phrap. Potential heterozygotes identified by PolyPhred are marked for rapid inspection using the Consed tool.

Proper citation: PolyPhred (RRID:SCR_002337) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.homd.org/index.php

THIS RESOURCE IS NO LONGER IN SERVICE.Documented on April 14,2022. Database of comprehensive information on the approximately 600 prokaryote species that are present in the human oral cavity. The majority of these species are uncultivated and unnamed, recognized primarily by their 16S rRNA sequences. The HOMD presents a provisional naming scheme for the currently unnamed species so that strain, clone, and probe data from any laboratory can be directly linked to a stably named reference entity. The HOMD links sequence data with phenotypic, phylogenetic, clinical, and bibliographic information. Full and partial oral bacterial genome sequences determined as part of this project and the Human Microbiome Project, are being added to the HOMD as they become available. HOMD offers easy to use tools for viewing all publicly available oral bacterial genomes. Data is also downloadable.

Proper citation: HOMD (RRID:SCR_012770) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.dnastar.com/t-sub-solutions-molecular-biology-Sanger-Sequence-Assembly.aspx

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. Software suite for the assembly and analysis of Sanger sequencing data within the SeqMan Pro application. The software's functions include: assembling reads into groups based on sequence names, trimming vector and poor quality data, restoration of sequence ends and designing of sequence primers.

Proper citation: DNASTAR: Lasergene Core Suite (RRID:SCR_000291) Copy   

•   Source: SciCrunch Registry

http://string.embl.de/

Database of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations and are derived from four sources: Genomic Context, High-throughput experiments, (Conserved) Coexpression, and previous knowledge. STRING quantitatively integrates interaction data from these sources for a large number of organisms, and transfers information between these organisms where applicable. The database currently covers 5''214''234 proteins from 1133 organisms. (2013)

Proper citation: STRING (RRID:SCR_005223) Copy   

•   Source: SciCrunch Registry

http://bioinfo.iitk.ac.in/MIPModDB/

This is a database of comparative protein structure models of MIP (Major Intrinsic Protein) family of proteins. The nearly completed sets of MIPs have been identified from the completed genome sequence of organisms available at NCBI. The structural models of MIP proteins were created by defined protocol. The database aims to provide key information of MIPs in particular based on sequence as well as structures. This will further help to decipher the function of uncharacterized MIPs. For each MIP entry, this database contains information about the source, gene structure, sequence features, substitutions in the conserved NPA motifs, structural model, the residues forming the selectivity filter and channel radius profile. For selected set of MIPs, it is possible to derive structure-based sequence alignment and evolutionary relationship. Sequences and structures of selected MIPs can be downloaded from MIPModDB database.

Proper citation: MIPModDB (RRID:SCR_006058) Copy   

•   Source: SciCrunch Registry