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https://github.com/nextstrain/augur

Software package to track evolution from sequence and serological data. Provides collection of commands which are designed to be composable into larger processing pipelines.

Proper citation: Augur (RRID:SCR_023964) Copy   

•   Source: SciCrunch Registry

http://cbcsrv.watson.ibm.com/phylopythia.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 1, 2023. Data analysis service for accurate phylogenetic classification of variable-length DNA fragments.

Proper citation: PhyloPythia (RRID:SCR_000540) Copy   

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

THIS RESOURCE IS NO LONGER IN SERVICE, as of October 1, 2013; however, the site is still accessible. NCBI resource that contains sequence and mapping data on short genomic landmark sequences or Sequence Tagged Sites. STS sequences are incorporated into the STS Division of GenBank. The dbSTS database offers a route for submission of STS sequences to GenBank. It is designed especially for the submission of large batches of STS sequences.

Proper citation: dbSTS (RRID:SCR_000400) Copy   

•   Source: SciCrunch Registry

http://chgv.org/GenicIntolerance/

A gene-based score intended to help in the interpretation of human sequence data. The score is designed to rank genes in terms of whether they have more or less common functional genetic variation relative to the genome wide expectation given the amount of apparently neutral variation the gene has. A gene with a positive score has more common functional variation, and a gene with a negative score has less and is referred to as intolerant.

Proper citation: Residual Variation Intolerance Score (RVIS) (RRID:SCR_013850) Copy   

•   Source: SciCrunch Registry

http://www.scied.com/pr_cmbas.htm

A software system to assist with cloning simulation, enzyme operations, and graphic map drawing. Clone Manager can also be used as a way to view or edit sequence files, find open reading frames, translate genes, or find genes or text in files. Clone Manager Professional is an upgraded version of Clone Manager Basic., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Clone Manager Software (RRID:SCR_014521) Copy   

•   Source: SciCrunch Registry

http://aem.asm.org/content/71/12/8228.full

THIS RESOURCE IS NO LONGER IN SERVICE, documented Setember 8, 2016. A suite of tools for the comparison of microbial communities using phylogenetic information. It takes as input a single phylogenetic tree that contains sequences derived from at least two different environmental samples and a file describing which sequences came from which sample.

Proper citation: Unifrac (RRID:SCR_014616) Copy   

•   Source: SciCrunch Registry

http://www.cbcb.umd.edu/software/metapath

A statistical package for comparing metagenomic data-sets at the pathway level. It relies on a combination of metagenomic sequence data and prior metabolic pathway knowledge, which is pulled from KEGG.

Proper citation: Metapath (RRID:SCR_014621) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/FT/

A web program that can locate residue periodicities in either amino acid or DNA sequences. It is based on an algorithm of Dr. A.D. McLachlan (1977). NOTE: You must use a Java compatible browser to run the application.

Proper citation: FT (RRID:SCR_006228) Copy   

•   Source: SciCrunch Registry

http://www.kabatdatabase.com/

The Kabat Database determines the combining site of antibodies based on the available amino acid sequences. The precise delineation of complementarity determining regions (CDR) of both light and heavy chains provides the first example of how properly aligned sequences can be used to derive structural and functional information of biological macromolecules. The Kabat database now includes nucleotide sequences, sequences of T cell receptors for antigens (TCR), major histocompatibility complex (MHC) class I and II molecules, and other proteins of immunological interest. The Kabat Database searching and analysis tools package is an ASP.NET web-based portal containing lookup tools, sequence matching tools, alignment tools, length distribution tools, positional correlation tools and much more. The searching and analysis tools are custom made for the aligned data sets contained in both the SQL Server and ASCII text flat file formats. The searching and analysis tools may be run on a single PC workstation or in a distributed environment. The analysis tools are written in ASP.NET and C# and are available in Visual Studio .NET 2003/2005/2008 formats. The Kabat Database was initially started in 1970 to determine the combining site of antibodies based on the available amino acid sequences at that time. Bence Jones proteins, mostly from human, were aligned, using the now-known Kabat numbering system, and a quantitative measure, variability, was calculated for every position. Three peaks, at positions 24-34, 50-56 and 89-97, were identified and proposed to form the complementarity determining regions (CDR) of light chains. Subsequently, antibody heavy chain amino acid sequences were also aligned using a different numbering system, since the locations of their CDRs (31-35B, 50-65 and 95-102) are different from those of the light chains. CDRL1 starts right after the first invariant Cys 23 of light chains, while CDRH1 is eight amino acid residues away from the first invariant Cys 22 of heavy chains. During the past 30 years, the Kabat database has grown to include nucleotide sequences, sequences of T cell receptors for antigens (TCR), major histocompatibility complex (MHC) class I and II molecules and other proteins of immunological interest. It has been used extensively by immunologists to derive useful structural and functional information from the primary sequences of these proteins.

Proper citation: Kabat Database of Sequences of Proteins of Immunological Interest (RRID:SCR_006465) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/bioinformatics/NON-RED/index.html

A web tool to select biological sequences from a given set, with similarity / homology less than a user-defined level. This web-based application takes as input a set of N sequences and outputs a set of sequences of user-determined redundancy. Initially, the algorithm runs an all-against-all BLAST alignment on the input data set and creates an NxN matrix of pairwise distances defined by the similarity percentages. In the next step, the algorithm removes the sequence with the largest number of neighbors, causing that sequence not to be counted as a neighbor of any other sequence during the next iterations. It then reassesses the number of neighbors of each sequence and repeats the previous step until the sequences left over have no more neighbors. The user can specify the similarity (%) threshold and the minimum coverage length of the alignments. Sequences with a similarity below the threshold or a smaller coverage than the minimum length are not considered to be neighbors.

Proper citation: NON-RED (RRID:SCR_006225) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/bioinformatics/waveTM/

A web tool for the prediction of transmembrane segments in alpha-helical membrane proteins. A sliding window of 20 residues is used in order to calculate an average residue hydrophobicity profile, using a hydrophobicity scale. Discrete Wavelet Transform is applied on the average residue hydrophobicity signal and the different frequency coefficients produced are adaptively thresholded so that a denoised signal is reconstructed. A dynamic programming algorithm processes the denoised signal to provide the optimal model for the number, the length and the location of membrane-spanning segments. The end points of the predicted segments are extended to include flanking hydrophobic residues. Topology prediction can also be obtained in conjunction with OrienTM (Liakopoulos et al, 2001). Analysis of a non-redundant test set, provides a ~95% per segment accuracy and ~90% per residue accuracy. Now, you can: * Run waveTM on a sequence * Browse the results obtained with the algorithm * View additional material concerning the hydrophobicity scale

Proper citation: waveTM (RRID:SCR_006199) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/PRED-TMR/

A web server that predicts transmembrane domains in proteins using solely information contained in the sequence itself. The algorithm refines a standard hydrophobicity analysis with a detection of potential termini (edges, starts and ends) of transmembrane regions. This allows both to discard highly hydrophobic regions not delimited by clear start and end configurations and to confirm putative transmembrane segments not distinguishable by their hydrophobic composition. The accuracy obtained on a test set of 101 non homologous transmembranes proteins with reliable topologies compares well with that of other popular existing methods. Only a slight decrease in prediction accuracy was observed when the algorithm was applied to all transmembrane proteins of the SwissProt database (release 35).

Proper citation: PRED-TMR (RRID:SCR_006203) Copy   

•   Source: SciCrunch Registry

http://rapdb.dna.affrc.go.jp/

Database that provides the genome sequence assembly of the International Rice Genome Sequencing Project (IRGSP), manually curated annotation of the sequence, and other genomics information that could be useful for comprehensive understanding of the rice biology. RAP-DB contains clone positions, structures and functions of genes validated by cDNAs, RNA genes detected by massively parallel signature sequencing (MPSS) technology and sequence similarity, flanking sequences of mutant lines, transposable elements, etc. Other annotation data such as Gnomon can be displayed along with those of RAP for comparison.

Proper citation: RAP-DB (RRID:SCR_006610) Copy   

•   Source: SciCrunch Registry

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

Database (anonymous FTP) resulting from a collaborative effort to identify a core set of human and mouse protein coding regions that are consistently annotated and of high quality. The long term goal is to support convergence towards a standard set of gene annotations. Collaborators are EBI, NCBI, UCSC, WTSI and the initial results are also available from the participants'''' genome browser Web sites. In addition, CCDS identifiers are indicated on the relevant NCBI RefSeq and Entrez Gene records and in Map Viewer displays of RNA (RefSeq) and Gene annotations on the reference assembly.

Proper citation: Consensus CDS (RRID:SCR_006729) Copy   

•   Source: SciCrunch Registry

https://myhits.sib.swiss/

Database devoted to protein domains. It is also a collection of tools for the investigation of the relationships between protein sequences and motifs described on them.

Proper citation: MyHits (RRID:SCR_006757) Copy   

•   Source: SciCrunch Registry

http://igs-server.cnrs-mrs.fr/mgdb/Rickettsia/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 18, 2016. Rickettsia are obligate intracellular bacteria living in arthropods. They occasionally cause diseases in humans. To understand their pathogenicity, physiologies and evolutionary mechanisms, RicBase is sequencing different species of Rickettsia. Up to now we have determined the genome sequences of R. conorii, R. felis, R. bellii, R. africae, and R. massiliae. The RicBase aims to organize the genomic data to assist followup studies of Rickettsia. This website contains information on R. conorii and R. prowazekii. A R. conorii and R. prowazekii comparative genome map is also available. Images of genome maps, dendrogram, and sequence alignment allow users to gain a visualization of the diagrams.

Proper citation: Rickettsia Genome Database (RRID:SCR_007102) Copy   

•   Source: SciCrunch Registry

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

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Database of sequence tagged sites (STSs) derived from STS-based maps and other experiments. STSs are defined by PCR primer pairs and are associated with additional information such as genomic position, genes, and sequences. Chromosome maps are labeled by name of the originating organism, the map title, total markers, total UniSTSs and links to view maps as well as research documents available through PubMed, another NCBI database. The search functions within UniSTS allow the user to search by gene marker, chromosome, gene symbol and gene description terms to locate markers on specified genes. A representation of the UniSTS datasets is available by ftp. NOTE: All data from this resource have been moved to the Probe database, http://www.ncbi.nlm.nih.gov/probe. You can retrieve all UniSTS records by searching the probe database using the search term unists(properties). (use brackets insead of parenthesis). Additionally, legacy data remain on the NCBI FTP Site in the UniSTS Repository (ftp://ftp.ncbi.nih.gov/pub/ProbeDB/legacy_unists).

Proper citation: UniSTS (RRID:SCR_006843) Copy   

•   Source: SciCrunch Registry

http://www.mbio.ncsu.edu/RNaseP/home.html

Ribonuclease P is responsible for the 5''-maturation of tRNA precursors. Ribonuclease P is a ribonucleoprotein, and in bacteria (and some Archaea) the RNA subunit alone is catalytically active in vitro, i.e. it is a ribozyme. The Ribonuclease P Database is a compilation of ribonuclease P sequences, sequence alignments, secondary structures, three-dimensional models and accessory information. The database contains information on bacterial, archaeal, and eukaryotic RNase P. The RNase P and protein sequences are available from phylogentically-arranged lists, individual sequences, or aligned in GenBank format. The database also provides secondary structures and 3D models, as well as movies, still images, and other accessory information.

Proper citation: RNase P Database (RRID:SCR_006680) Copy   

•   Source: SciCrunch Registry

http://bond.unleashedinformatics.com/

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone.. Documented on August 19,2019.BOND, which requires registration of a free account, is a resource used to perform cross-database searches of available sequence, interaction, complex and pathway information. BOND integrates a range of component databases including GenBank and BIND, the Biomolecular Interaction Network Database. BOND contains 70+ million biological sequences, 33,000 structures, 38,000 GO terms, and over 200,000 human curated interactions contained in BIND, and is open access. BOND serves the interests of the developing global interactome effort encompassing the genomic, proteomic and metabolomic research communities. BOND is the first open access search resource to integrate sequence and interaction information. BOND integrates BLAST functionality, and contains a well-documented API. BOND also stores annotation links for sequences, including links to Genome Ontology descriptions, MedLine abstracts, taxon identifiers, associated structures, redundant sequences, sequence neighbors, conserved domains, data base cross-references, Online Mendalian Inheritance in Man identifiers, LocusLink identifiers and complete genomes. BIND on BOND The Biomolecular Interaction Network Database (BIND), a component database of BOND, is a collection of records documenting molecular interactions. The contents of BIND include high-throughput data submissions and hand-curated information gathered from the scientific literature. BIND is an interaction database with three classifications for molecular associations: molecules that associate with each other to form interactions, molecular complexes that are formed from one or more interaction(s) and pathways that are defined by a specific sequence of two or more interactions.Interactions A BIND record represents an interaction between two or more objects that is believed to occur in a living organism. A biological object can be a protein, DNA, RNA, ligand, molecular complex, gene, photon or an unclassified biological entity. BIND records are created for interactions which have been shown experimentally and published in at least one peer-reviewed journal. A record also references any papers with experimental evidence that support or dispute the associated interaction. Interactions are the basic units of BIND and can be linked together to form molecular complexes or pathways. The BIND interaction viewer is a tool to visualize and analyze molecular interactions, complexes and pathways. The BIND interaction viewer uses Ontoglyphs to display information about a protein via attributes such as molecular function, biological process and sub-cellular localization. Ontoglyphs allow to graphically and interactively explore interaction networks, by visualizing interactions in the context of 34 functional, 25 binding specificity and 24 sub-cellular localization Ontoglyphs categories. We will continue to provide an open access version of BOND, providing its subscribers with free, unlimited access to a core content set. But we are confident you will soon want to upgrade to BONDplus.

Proper citation: Biomolecular Object Network Databank (RRID:SCR_007433) Copy   

•   Source: SciCrunch Registry

http://biobases.ibch.poznan.pl/5SData/

A database on nucleotide sequences of 5S rRNAs and their genes. The database contains 1985 primary structures of 5S rRNA and 5S rDNA, and was last updated in 2002, according to the website. They include 60 archaebacterial, 470 eubacterial, 63 plastid, nine mitochondrial and 1383 eukaryotic sequences. The nucleotide sequences of the 5S rRNAs or 5S rDNAs are divided according to the taxonomic position of the source organisms. The sequences for particular organisms can be retrieved as single files using a taxonomic browser or in multiple sequence structural alignments. The multiple sequence alignments of 5S ribosomal RNAs can be downloaded in TAB-delimited and FASTA formats.

Proper citation: 5S Ribosomal RNA Database (RRID:SCR_007545) Copy   

•   Source: SciCrunch Registry