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http://genome.imim.es/datasets/abs2005/index.html

Public database of known binding sites identified in promoters of orthologous vertebrate genes that have been manually curated from bibliography. We have annotated 650 experimental binding sites from 68 transcription factors and 100 orthologous target genes in human, mouse, rat or chicken genome sequences. Computational predictions and promoter alignment information are also provided for each entry. For each gene, TFBSs conserved in orthologous sequences from at least two different species must be available. Promoter sequences as well as the original GenBank or RefSeq entries are additionally supplied in case of future identification conflicts. The final TSS annotation has been refined using the database dbTSS. Up to this release, 500 bps upstream the annotated transcription start site (TSS) according to REFSEQ annotations have been always extracted to form the collection of promoter sequences from human, mouse, rat and chicken. For each regulatory site, the position, the motif and the sequence in which the site is present are available in a simple format. Cross-references to EntrezGene, PubMed and RefSeq are also provided for each annotation. Apart from the experimental promoter annotations, predictions by popular collections of weight matrices are also provided for each promoter sequence. In addition, global and local alignments and graphical dotplots are also available.

Proper citation: ABS: A Database of Annotated Regulatory Binding Sites From Orthologous Promoters (RRID:SCR_002276) Copy   

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http://www.drugbank.ca/

Bioinformatics and cheminformatics database that combines detailed drug (i.e. chemical, pharmacological and pharmaceutical) data with comprehensive drug target (i.e. sequence, structure, and pathway) information.

Proper citation: DrugBank (RRID:SCR_002700) Copy   

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http://romi.bu.edu/elisa/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. ELISA is an online database that combines functional annotation with structure and sequence homology modeling to place proteins into sequence-structure-function neighborhoods. The atomic unit of the database is a set of sequences and structural templates that those sequences encode. A graph that is built from the structural comparison of these templates is called PDUG (protein domain universe graph). It introduces a method of functional inference through a probabilistic calculation done on an arbitrary set of PDUG nodes. Further, all PDUG structures are mapped onto all fully sequenced proteomes allowing an easy interface for evolutionary analysis and research into comparative proteomics. ELISA is the first database with applicability to evolutionary structural genomics explicitly in mind.

Proper citation: Evolutionary Lineage Inferred from Structural Analysis (RRID:SCR_002343) Copy   

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http://www.allgenes.org/

DoTS (Database Of Transcribed Sequences) is a human and mouse transcript index created from all publicly available transcript sequences. The input sequences are clustered and assembled to form the DoTS Consensus Transcripts that comprise the index. These transcripts are assigned stable identifiers of the form DT.123456 (and are often referred to as dots). The transcripts are in turn clustered to form putative DoTS Genes. These are assigned stable identifiers of the form DG.1234356. As of September 1, 2004, the DoTS annotation team has manually annotated 43,164 human and 78,054 mouse DoTS Transcripts (DTs), corresponding to 3,939 human and 7,752 mouse DoTS Genes (DGs). Use the manually annotated gene query to see the DoTS Transcripts that have been manually annotated. The focus of the DoTS project is integrating the various types of data (e.g., EST sequences, genomic sequence, expression data, functional annotation) in a structured manner which facilitates sophisticated queries that are otherwise not easy to perform. DoTS is built on the GUS Platform which includes a relational database that uses controlled vocabularies and ontologies to ensure that biologically meaningful queries can be posed in a uniform fashion. An easy way to start using the site is to search for DoTS Transcripts using an existing cDNA or mRNA sequence. Click on the BLAST tab at the top of the page and enter your sequence in the form provided. All the transcripts with significant sequence similarity to your query sequence will be displayed. Or use one of the provided queries to retrieve transcripts using a number of criteria. These queries are listed on the query page, which can also be reached by clicking on the tab marked query at the top of the page. Finally, the boolean query page allows these queries to be combined in a variety of ways. Sponsors: Funding provided by -NIH grant RO1-HG-01539-03 -DOE grant DE-FG02-00ER62893

Proper citation: Database of Transcribed Sequences (RRID:SCR_002334) Copy   

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http://machibase.gi.k.u-tokyo.ac.jp/

Database for Drosophila melanogaster transcription profiling that allows users to search the Drosophilia genome, see sequence overviews, and look at various transcripts. The data were generated in conjunction with the recently developed high-throughput genome sequencer Illumina / Solexa using a newly developed 5'-end mRNA collection method. Approximately 25 million 25-27 nucleotide (nt) 5'-end mRNA tags from the embryos, larvae, young males, young females, old males, old females, and S2 (culture cell line) of D. melanogaster were collected. By arranging this vast amount of expression tag with other annotated data, they have built a one-stop service for Drosophila melanogaster transcription profiling.

Proper citation: MachiBase (RRID:SCR_003078) Copy   

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

Databases of protein sequences and 3D structures of proteins. Collection of sequences from several sources, including translations from annotated coding regions in GenBank, RefSeq and TPA, as well as records from SwissProt, PIR, PRF, and PDB.

Proper citation: NCBI Protein Database (RRID:SCR_003257) Copy   

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http://xavante.fmrp.usp.br/mammibase/

Database developed to assist the phylogeneticist user in retrieving individual gene sequence alignments for genes in complete mammalian mitochondrial genomes. Data retrieval in MamMiBase requires three stages. At the first stage, the user must select the mammalian species or group that (s)he wishes to study. In the second stage, the user will select the outgroup from a list that included all species selected in the first stage plus Xenopus laevis and Gallus gallus. Finally, at the third stage, the user will select individual mitochondrial gene alignments or a phylogenetic tree that (s)he wishes to download.

Proper citation: Mammalian Mitochondrial Genomics Database (RRID:SCR_003084) Copy   

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http://www.ncbi.nlm.nih.gov/genbank/tpa/

Database designed to capture experimental or inferential results that support submitter-provided annotation for sequence data that the submitter did not directly determine but derived from GenBank primary data. Records are divided into two categories: * TPA:experimental: Annotation of sequence data is supported by peer-reviewed wet-lab experimental evidence. * TPA:inferential: Annotation of sequence data by inference (where the source molecule or its product(s) have not been the subject of direct experimentation) TPA records are retrieved through the Nucleotide Database and feature information on the sequence, how it was cataloged, and proper way to cite the sequence information.

Proper citation: TPA (RRID:SCR_003593) 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   

•   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   

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http://www.cbs.dtu.dk/services/TMHMM/

Web application for the prediction of transmembrane helices in proteins using Hidden Markov Models. FASTA formatted sequences can be uploaded via file or copy-paste, and output can be formatted as extensive with graphics, extensive without graphics, or one line per protein. Submissions are limited to 10,000 sequences and 4,000,000 amino acids - each sequence is limited to no more than 8,000 amino acids.

Proper citation: TMHMM Server (RRID:SCR_014935) Copy   

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http://www.cbs.dtu.dk/services/ProP/

Web application which predicts arginine and lysine propeptide cleavage sites in eukaryotic protein sequences using an ensemble of neural networks. Furin-specific prediction is the default. It is also possible to perform a general proprotein convertase prediction.

Proper citation: ProP Server (RRID:SCR_014936) Copy   

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http://www.cprofiler.org/

Web tool for discovery and visualization of differences in amino acid composition. Two samples of amino acid sequences serve as input and a bar chart composed of twenty data points is output.

Proper citation: Composition Profiler (RRID:SCR_014630) Copy   

•   Source: SciCrunch Registry

http://www.structuralgenomics.org/

The Structural Genomics Project aims at determination of the 3D structure of all proteins. It also aims to reduce the cost and time required to determine three-dimensional protein structures. It supports selection, registration, and tracking of protein families and representative targets. This aim can be achieved in four steps : -Organize known protein sequences into families. -Select family representatives as targets. -Solve the 3D structure of targets by X-ray crystallography or NMR spectroscopy. -Build models for other proteins by homology to solved 3D structures. PSI has established a high-throughput structure determination pipeline focused on eukaryotic proteins. NMR spectroscopy is an integral part of this pipeline, both as a method for structure determinations and as a means for screening proteins for stable structure. Because computational approaches have estimated that many eukaryotic proteins are highly disordered, about 1 year into the project, CESG began to use an algorithm. The project has been organized into two separate phases. The first phase was dedicated to demonstrating the feasibility of high-throughput structure determination, solving unique protein structures, and preparing for a subsequent production phase. The second phase, PSI-2, has focused on implementing the high-throughput structure determination methods developed in PSI-1, as well as homology modeling and addressing bottlenecks like modeling membrane proteins. The first phase of the Protein Structure Initiative (PSI-1) saw the establishment of nine pilot centers focusing on structural genomics studies of a range of organisms, including Arabidopsis thaliana, Caenorhabditis elegans and Mycobacterium tuberculosis. During this five-year period over 1,100 protein structures were determined, over 700 of which were classified as unique due to their < 30% sequence similarity with other known protein structures. The primary goal of PSI-1 was to develop methods to streamline the structure determination process, resulted in an array of technical advances. Several methods developed during PSI-1 enhanced expression of recombinant proteins in systems like Escherichia coli, Pichia pastoris and insect cell lines. New streamlined approaches to cell cloning, expression and protein purification were also introduced, in which robotics and software platforms were integrated into the protein production pipeline to minimize required manpower, increase speed, and lower costs. The goal of the second phase of the Protein Structure Initiative (PSI-2) is to use methods introduced in PSI-1 to determine a large number of proteins and continue development in streamlining the structural genomics pipeline. Currently, the third phase of the PSI is being developed and will be called PSI: Biology. The consortia will propose work on substantial biological problems that can benefit from the determination of many protein structures Sponsors: PSI is funded by the U.S. National Institute of General Medical Sciences (NIGMS),

Proper citation: Protein Structure Initiative (RRID:SCR_002161) Copy   

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http://www.hgsc.bcm.tmc.edu/content/honey-bee-genome-project

The HGSC has sequenced the honey bee, Apis mellifera. The version 4.0 assembly was released in March 2006 and published in October 2006. The genome sequence is being upgraded with additional sequence coverage. The honey bee is important in the agricultural community as a producer of honey and as a facilitator of pollination. It is a model organism for studying the following human health issues: immunity, allergic reaction, antibiotic resistance, development, mental health, longevity and diseases of the X chromosome. In addition, biologists are interested in the honey bee's social organization and behavioral traits. This project was proposed to the HGSC by a group of dedicated insect biologists, headed by Gene Robinson. Following a workshop at the HGSC and a honey bee white paper, the HGSC began the project in 2002. A 6-fold coverage WGS, BAC sequence from pooled arrays, and an initial genome assembly (Amel_v1.0) were released beginning in 2003. This has been a challenging project with difficulty in recovering AT-rich regions. The WGS data had lower coverage in AT-rich regions and BAC data from clones showed evidence of internal deletions. Additional reads from AT enriched DNA addressed these underrepresented regions. The current assembly Amel_4.0 was produced with Atlas and includes 2.7 million reads (1.8 Gb) or 7.5x coverage of the (clonable) genome. About 97% of STSs, 98% of ESTs, and 96% of cDNAs are represented in the 231 Mb assembly. About 2,500 reads were also produced from a strain of Africanized honey bee and SNPs were extracted. These were released in dbSNP and the NCBI Trace Archive. Analysis of the genome by a consortium of 20 labs has been completed. This produced a gene list derived from five different methods melded through the GLEAN software. Publications include a main paper in Nature and up to forty companion papers in Genome Research and Insect Molecular Biology. Sponsors: Sequencing of the honey bee is jointly funded by National Human Genome Research Institute (NHGRI) and the Department of Agriculture (USDA). Multiple drones from the same queen (strain DH4) were obtained from Danny Weaver of B. Weaver Apiaries. All libraries were made from DNA isolated from these drones. The honey bee BAC library (CHORI-224) was prepared by Pieter de Jong and Katzutoyo Osoegawa at the Children's Hospital Oakland Research Institute.

Proper citation: Honey Bee Genome Project (RRID:SCR_002890) Copy   

•   Source: SciCrunch Registry

http://proteininformationresource.org/

Integrated public bioinformatics resource to support genomic, proteomic and systems biology research and scientific studies. Provides databases and protein sequence analysis tools to scientific community, including Protein Sequence Database which grew out from the Atlas of Protein Sequence and Structure. Conducts research in biomedical text mining and ontology, computational systems biology, and bioinformatics cyberinfrastructure. In 2002 PIR, along with its international partners, EBI (European Bioinformatics Institute) and SIB (Swiss Institute of Bioinformatics), were awarded a grant from NIH to create UniProt, a single worldwide database of protein sequence and function, by unifying the PIR-PSD, Swiss-Prot, and TrEMBL databases. Currently, PIR major activities include: i) UniProt (Universal Protein Resource) development, ii) iProClass protein data integration and ID mapping, iii) PRO protein ontology, and iv) iProLINK protein literature mining and ontology development. The FTP site provides free download for iProClass, PIRSF, and PRO.

Proper citation: Protein Information Resource (RRID:SCR_002837) Copy   

•   Source: SciCrunch Registry

https://github.com/liukai5016/FungiLT

Software classifier tool based on deep learning methods for classification and annotation of large-scale fungal ITS sequences. Used for fungal species classification.

Proper citation: FungiLT (RRID:SCR_025886) Copy   

•   Source: SciCrunch Registry

http://technelysium.com.au/?page_id=27

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 31,2023. Software which is able to assemble data from 454 and Illumina next-generation sequencers, with up to 100,000 sequences if 2 Gb RAM is available.

Proper citation: ChromasPro (RRID:SCR_000229) Copy   

•   Source: SciCrunch Registry