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http://mitores.ba.itb.cnr.it

MitoRes, is a comprehensive and reliable resource for massive extraction of sequences and sub-sequences of nuclear genes and encoded products targeting mitochondria in metazoa. It has been developed for supporting high-throughput in-silico analyses aimed to studies of functional genomics related to mitochondrial biogenesis, metabolism and to their pathological dysfunctions. It integrates information from the most accredited world-wide databases to bring together gene, transcript and encoded protein sequences associated to annotations on species name and taxonomic classification, gene name, functional product, organelle localization, protein tissue specificity, Enzyme Classification (EC), Gene Ontology (GO) classification and links to other related public databases. The section Cluster, has been dedicated to the collection of data on protein clustering of the entire catalogue of MitoRes protein sequences based on all versus all global pair-wise alignments for assessing putative intra- and inter-species functional relationships. The current version of MitoRes is based on the UniProt release 4 and contains 64 different metazoan species. The incredible explosion of knowledge production in Biology in the past two decades has created a critical need for bioinformatic instruments able to manage data and facilitate their retrieval and analysis. Hundreds of biological databases have been produced and the integration of biological data from these different resources is very important when we want to focus our efforts towards the study of a particular layer of biological knowledge. MitoRes is a completely rebuilt edition of MitoNuc database, which has been extensively modified to deal successfully with the challenges of the post genomic era. Its goal is to represent a comprehensive and reliable resource supporting high-quality in-silico analyses aimed to the functional characterization of gene, transcript and amino acid sequences, encoded by the nuclear genome and involved in mitochondrial biogenesis, metabolism and pathological dysfunctions in metazoa. The central features of MitoRes are: # an integrated catalogue of protein, transcript and gene sequences and sub-sequences # a Web-based application composed of a wide spectrum of search/retrieval facilities # a sequence export manager allowing massive extraction of bio-sequences (genes, introns, exons, gene flanking regions, transcripts, UTRs, CDS, proteins and signal peptides) in FASTA, EMBL and GenBank formats. It is an interconnected knowledge management system based on a MySQL relational database, which ensures data consistency and integrity, and on a Web Graphical User Interface (GUI), built in Seagull PHP Framework, offering a wide range of search and sequence extraction facilities. The database is compiled extracting and integrating information from public resources and data generated by the MitoRes team. The MitoRes database consists of comprehensive sequence entries whose core data are protein, transcript and gene sequences and taxonomic information describing the biological source of the protein. Additional information include: bio-sequences structure and location, biological function of protein product and dynamic links to both, external public databases used as data resources and public databases reporting complementary information. The core entity of the MitoRes database is represented by the protein so that each MitoRes entry is generated for each protein reported in the UniProt database as a nuclear encoded protein involved in mitochondrial biogenesis and function. Sponsors: MitoRes has been supported by Ministero Universit e Ricerca Scientifica, Italy (PRIN, Programma Biotecnologie legge 95/95-MURST 5, Proiect MURST Cluster C03/2000, CEGBA). Currently it is supported by operating grants from the Ministero dellIstruzione, dellUniversit e della Ricerca (MIUR), Italy (PNR 2001-2003 (FIRB art.8) D.M. 199, Strategic Program: Post-genome, grant 31-063933 and Project n.2, Cluster C03 L. 488/929).

Proper citation: MitoRes (RRID:SCR_008208) Copy   

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http://www.ebi.ac.uk/parasites/parasite-genome.html

This website contains information about the genomic sequence of parasites. It also contains multiple search engines to search six frame translations of parasite nucleotide databases for motifs, parasite protein databases for motifs, and parasite protein databases for keywords and text terms. * Guide to Internet Access to Parasite Genome Information * Guide to web-based analysis tools * Parasite Genome BLAST Server: Search a range of parasite specific nucleotide sequence databases with your own sequence. * Parasite Proteome Keyword Search Facility: Search parasite protein databases for keywords and text terms * Parasite Proteome Motif Search Facility: Search parasite protein databases for motifs * Parasite Six Frame Translation Motif Search Facility: Search six frame translations of parasite nucleotide databases for motifs * Genome computing resources: A list of ftp and gopher sites where genome computing applications and other resources can be found.

Proper citation: Parasite genome databases and genome research resources (RRID:SCR_008150) Copy   

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http://pdbfun.uniroma2.it/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. PDBfun is a web server for structural and functional analysis of proteins at the residue level. pdbFun gives fast access to the whole Protein Data Bank (PDB) organized as a database of annotated residues. The available data (features) range from solvent exposure to ligand binding ability, location in a protein cavity, secondary structure, residue type, sequence functional pattern, protein domain and catalytic activity. PDBfun is an integrated web tool for querying the PDB at the residue level and for local structural comparison. It integrates knowledge on single residues in protein structures coming from other databases or calculated with available or in-house developed instruments for structural analysis. Each set of different annotations represents a feature. Features are listed in PDBfun main page in orange. Features can be used for building residues selections.

Proper citation: Protein Databank Fun (RRID:SCR_008226) Copy   

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http://www.maizegdb.org

Collection of data related to crop plant and model organism Zea mays. Used to synthesize, display, and provide access to maize genomics and genetics data, prioritizing mutant and phenotype data and tools, structural and genetic map sets, and gene models and to provide support services to the community of maize researchers. Data stored at MaizeGDB was inherited from the MaizeDB and ZmDB projects. Sequence data are from GenBank. Data are searchable by phenotype, traits, Pests, Gel Pattern, and Mutant Images.

Proper citation: MaizeGDB (RRID:SCR_006600) Copy   

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http://rgd.mcw.edu

Database for genetic, genomic, phenotype, and disease data generated from rat research. Centralized database that collects, manages, and distributes data generated from rat genetic and genomic research and makes these data available to scientific community. Curation of mapped positions for quantitative trait loci, known mutations and other phenotypic data is provided. Facilitates investigators research efforts by providing tools to search, mine, and analyze this data. Strain reports include description of strain origin, disease, phenotype, genetics, immunology, behavior with links to related genes, QTLs, sub-strains, and strain sources.

Proper citation: Rat Genome Database (RGD) (RRID:SCR_006444) Copy   

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http://flybase.org/

Database of Drosophila genetic and genomic information with information about stock collections and fly genetic tools. Gene Ontology (GO) terms are used to describe three attributes of wild-type gene products: their molecular function, the biological processes in which they play a role, and their subcellular location. Additionally, FlyBase accepts data submissions. FlyBase can be searched for genes, alleles, aberrations and other genetic objects, phenotypes, sequences, stocks, images and movies, controlled terms, and Drosophila researchers using the tools available from the "Tools" drop-down menu in the Navigation bar.

Proper citation: FlyBase (RRID:SCR_006549) Copy   

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https://github.com/uclinfectionimmunity/Decombinator

Software suite for analysis of T cell receptor repertoire data. Used for fast, efficient analysis of T cell receptor (TcR) repertoire samples, designed to be accessible to those with no previous programming experience.

Proper citation: Decombinator (RRID:SCR_006732) Copy   

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http://www.1000genomes.org/

International collaboration producing an extensive public catalog of human genetic variation, including SNPs and structural variants, and their haplotype contexts, in an effort to provide a foundation for investigating the relationship between genotype and phenotype. The genomes of about 2500 unidentified people from about 25 populations around the world were sequenced using next-generation sequencing technologies. Redundant sequencing on various platforms and by different groups of scientists of the same samples can be compared. The results of the study are freely and publicly accessible to researchers worldwide. The consortium identified the following populations whose DNA will be sequenced: Yoruba in Ibadan, Nigeria; Japanese in Tokyo; Chinese in Beijing; Utah residents with ancestry from northern and western Europe; Luhya in Webuye, Kenya; Maasai in Kinyawa, Kenya; Toscani in Italy; Gujarati Indians in Houston; Chinese in metropolitan Denver; people of Mexican ancestry in Los Angeles; and people of African ancestry in the southwestern United States. The goal Project is to find most genetic variants that have frequencies of at least 1% in the populations studied. Sequencing is still too expensive to deeply sequence the many samples being studied for this project. However, any particular region of the genome generally contains a limited number of haplotypes. Data can be combined across many samples to allow efficient detection of most of the variants in a region. The Project currently plans to sequence each sample to about 4X coverage; at this depth sequencing cannot provide the complete genotype of each sample, but should allow the detection of most variants with frequencies as low as 1%. Combining the data from 2500 samples should allow highly accurate estimation (imputation) of the variants and genotypes for each sample that were not seen directly by the light sequencing. All samples from the 1000 genomes are available as lymphoblastoid cell lines (LCLs) and LCL derived DNA from the Coriell Cell Repository as part of the NHGRI Catalog. The sequence and alignment data generated by the 1000genomes project is made available as quickly as possible via their mirrored ftp sites. ftp://ftp.1000genomes.ebi.ac.uk ftp://ftp-trace.ncbi.nlm.nih.gov/1000genomes

Proper citation: 1000 Genomes: A Deep Catalog of Human Genetic Variation (RRID:SCR_006828) Copy   

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http://humancyc.org/

The HumanCyc database describes human metabolic pathways and the human genome. By presenting metabolic pathways as an organizing framework for the human genome, HumanCyc provides the user with an extended dimension for functional analysis of Homo sapiens at the genomic level. A computational pathway analysis of the human genome assigned human enzymes to predicted metabolic pathways. Pathway assignments place genes in their larger biological context, and are a necessary step toward quantitative modeling of metabolism. HumanCyc contains the complete genome sequence of Homo sapiens, as presented in Build 31. Data on the human genome from Ensembl, LocusLink and GenBank were carefully merged to create a minimally redundant human gene set to serve as an input to SRI''s PathoLogic software, which generated the database and predicted Homo sapiens metabolic pathways from functional information contained in the genome''s annotation. SRI did not re-annotate the genome, but worked with the gene function assignments in Ensembl, LocusLink, and GenBank. The resulting pathway/genome database (PGDB) includes information on 28,783 genes, their products and the metabolic reactions and pathways they catalyze. Also included are many links to other databases and publications. The Pathway Tools software/database bundle includes HumanCyc and the Pathway Tools software suite and is available under license. This form of HumanCyc is faster and more powerful than the Web version.

Proper citation: HumanCyc: Encyclopedia of Homo sapiens Genes and Metabolism (RRID:SCR_007050) Copy   

•   Source: SciCrunch Registry

http://goblet.molgen.mpg.de/cgi-bin/goblet2008/goblet.cgi

Tool that performs annotation based on GO and pathway terms for anonymous cDNA or protein sequences. It uses the species independent GO structure and vocabulary together with a series of protein databases collected from various sites, to perform a detailed GO annotation by sequence similarity searches. The sensitivity and the reference protein sets can be selected by the user. GOblet runs automatically and is available as a public service on our web server. GOblet expects query sequences to be in FASTA-Format (with header-lines). Protein and nucleotide sequences are accepted. Total size of all sequences submitted per request should not be larger than 50kb currently. For security reasons: Larger post's will be rejected. Due to limited capacities the queries may be processed in batches depending on the server load. The output of the BLAST job is filtered automatically and the relevant hits are displayed. In addition, the respective GO-terms are shown together with the complete GO-hierarchy of parent terms., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: GOblet (RRID:SCR_006998) Copy   

•   Source: SciCrunch Registry

https://simtk.org/home/nast

A knowledge-based coarse-grained tool for modeling RNA structures. It produces a diverse set of plausible 3D structures that satisfy user-provided constraints based on: 1. primary sequence 2. known or predicted secondary structure 3. known or predicted tertiary contacts (optional) Additionally, NAST can use residue-resolution experimental data (e.g. hydroxyl radical footprinting) to filter the generated decoy structures. NAST uses an RNA-specific knowledge-based potential in a coarse-grained molecular dynamics engine to generate large numbers of plausible 3D structures that satisfy the constraints given on the secondary and tertiary structure. It then filter these structures based on agreement to the experimental data (if available). This results in a model of the molecule which satisfies all the known residue-resolution data. Imported from BiositeMaps registry

Proper citation: NAST (RRID:SCR_006995) Copy   

•   Source: SciCrunch Registry

http://sites.huji.ac.il/malaria/

Data set of metabolic pathways for the malaria parasite based on the present knowledge of parasite biochemistry and on pathways known to occur in other unicellular eukaryotes. This site extracted the pertinent information from the universal sites and presented them in an educative and informative format. The site also includes, cell-cell interactions (cytoadherence and rosetting), invasion of the erythrocyte by the parasite and transport functions. It also contains an artistic impression of the ultrastructural morphology of the interaerythrocytic cycle stages and some details about the morphology of mitochondria and the apicoplast. Most pathways are relevant to the erythrocytic phase of the parasite cycle. All maps were checked for the presence of enzyme-coding genes as they are officially annotated in the Plasmodium genome (http://plasmodb.org/). The site is constructed in a hierarchical pattern that permits logical deepening: * Grouped pathways of major chemical components or biological process ** Specific pathways or specific process *** Chemical structures of substrates and products or process **** Names of enzymes and their genes or components of process Each map is linked to other maps thus enabling to verify the origin of a substrate or the fate of a product. Clicking on the EC number that appears next to each enzyme, connects the site to BRENDA, SWISSPROT ExPASy ENZYME, PlasmoDB and to IUBMB reaction scheme. Clicking of the name of a metabolite, connects the site to KEGG thus providing its chemical structure and formula. Next to each enzyme there is a pie that depicts the stage-dependent transcription of the enzyme''s coding gene. The pie is constructed as a clock of the 48 hours of the parasite cycle, where red signifies over-transcription and green, under-transcription. Clicking on the pie links to the DeRisi/UCSF transcriptome database.

Proper citation: Malaria Parasite Metabolic Pathways (RRID:SCR_007072) Copy   

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http://yetfasco.ccbr.utoronto.ca/

Collection of all available transcription factor (TF) specificities for the yeast Saccharomyces cerevisiae in Position Frequency Matrix (PFM) or Position Weight Matrix (PWM) formats. The specificities are evaluated for quality using several metrics. With this website, you can scan sequences with the motifs to find where potential binding sites lie, inspect precomputed genome-wide binding sites, find which TFs have similar motifs to one you have found, and download the collection of motifs. Submissions are welcome.

Proper citation: YeTFaSCo (RRID:SCR_006893) Copy   

•   Source: SciCrunch Registry

http://www.vbase2.org/

Integrative database of germ-line V genes from the immunoglobulin loci of human and mouse. It presents V gene sequences extracted from the EMBL nucleotide sequence database and Ensembl together with links to the respective source sequences. Based on the properties of the source sequences, V genes are classified into 3 different classes: * Class 1: genomic and rearranged evidence * Class 2: genomic evidence only * Class 3: rearranged evidence only This allows careful sequence quality validation by the user. References to other immunological databases ( KABAT, IMGT/LIGM and VBASE ) are given to provide all public annotation data for each V gene. The VBASE2 database can be accessed either by the Direct Query interface or by the DNAPLOT Query interface. The Sequences given by the user are aligned with DNAPLOT against the VBASE2 database. Direct Query allows to enter sequence IDs and names (Field 1), choose species, locus, V gene family and class (Field 2) or search for 100% sequences (Field 3). At the DNAPLOT Query, the sequences given by the user are aligned with DNAPLOT against the VBASE2 database. The DNAPLOT program offers V gene nucleotide sequence alignment referring to the IMGT V gene unique numbering. The Quick Search can be used either for Direct Query to search for sequence IDs and V gene names or for DNAPLOT Query for up to 5 sequences. The new Fab Analysis allows you to align Fab, scFab, scAb or scFv sequences with DNAPLOT against the VBASE2 database, where both heavy and light chain are analyzed.

Proper citation: VBASE2 (RRID:SCR_007082) Copy   

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http://www.scienceexchange.com/facilities/high-throughput-sequencing-and-microarray-facility-princeton

Core facility provides researchers with access to high-throughput sequencing technologies. The staff provide consultation on experimental design, library preparation, and data analysis. The Sequencing Core Facility works closely with Bioinformatics staff in the Center for Quantitative Biology to provide researchers with computing power and consulting services to analyze sequencing data.

Proper citation: Princeton High Throughput Sequencing and Microarray Facility (RRID:SCR_012619) Copy   

•   Source: SciCrunch Registry

http://www.ornl.gov/sci/techresources/Human_Genome/home.shtml

This resource gives information about the U.S. Human Genome Project, which was was a 13-year effort to to discover all the estimated 20,000-25,000 human genes and make them accessible for further biological study. The primary project goals were to: - identify all the approximately 20,000-25,000 genes in human DNA, - determine the sequences of the 3 billion chemical base pairs that make up human DNA, - store this information in databases, - improve tools for data analysis, - transfer related technologies to the private sector, and - address the ethical, legal, and social issues (ELSI) that may arise from the project. To help achieve these goals, researchers also studied the genetic makeup of several nonhuman organisms. These include the common human gut bacterium Escherichia coli, the fruit fly, and the laboratory mouse. These parallel studies helped to develop technology and interpret human gene function. Sponsors: The DOE Human Genome Program and the NIH National Human Genome Research Institute (NHGRI) together sponsored the U.S. Human Genome Project.

Proper citation: Human Genome Project Information (RRID:SCR_013028) Copy   

•   Source: SciCrunch Registry

http://sift.bii.a-star.edu.sg/

Data analysis service to predict whether an amino acid substitution affects protein function based on sequence homology and the physical properties of amino acids. SIFT can be applied to naturally occurring nonsynonymous polymorphisms and laboratory-induced missense mutations. (entry from Genetic Analysis Software) Web service is also available.

Proper citation: SIFT (RRID:SCR_012813) Copy   

•   Source: SciCrunch Registry

http://www.mrc-lmb.cam.ac.uk/genomes/dolop/

DOLOP is an exclusive knowledge base for bacterial lipoproteins by processing information from 510 entries to provide a list of 199 distinct lipoproteins with relevant links to molecular details. Features include functional classification, predictive algorithm for query sequences, primary sequence analysis and lists of predicted lipoproteins from 43 completed bacterial genomes along with interactive information exchange facility. This website along will have additional information on the biosynthetic pathway, supplementary material and other related figures. DOLOP also contains information and links to molecular details for about 278 distinct lipoproteins and predicted lipoproteins from 234 completely sequenced bacterial genomes. Additionally, the website features a tool that applies a predictive algorithm to identify the presence or absence of the lipoprotein signal sequence in a user-given sequence. The experimentally verified lipoproteins have been classified into different functional classes and more importantly functional domain assignments using hidden Markov models from the SUPERFAMILY database that have been provided for the predicted lipoproteins. Other features include: primary sequence analysis, signal sequence analysis, and search facility and information exchange facility to allow researchers to exchange results on newly characterized lipoproteins.

Proper citation: DOLOP: A Database of Bacterial Lipoproteins (RRID:SCR_013487) Copy   

•   Source: SciCrunch Registry

http://genetics.bwh.harvard.edu/pph2/

Software tool which predicts possible impact of amino acid substitution on structure and function of human protein using straightforward physical and comparative considerations. PolyPhen-2 is new development of PolyPhen tool for annotating coding nonsynonymous SNPs.

Proper citation: PolyPhen: Polymorphism Phenotyping (RRID:SCR_013189) Copy   

•   Source: SciCrunch Registry

http://biologylabs.utah.edu/jorgensen/wayned/ape/

Software tool for plasmid and sequence editing, annotating and drawing plasmid sequences. Used to view circular or linear maps of DNA sequences. Users can perform virtual digests whereby they select predefined DNA ladder, or specify their own, and visualize theoretical DNA fragments. Used to highlight restriction sites in editing window, accurately reflect Dam/Dcm blocking of enzyme sites, highlighting and drawing graphic maps using feature annotations from genbank and embl files, highlighting text using pre-defined and custom feature libraries, and directly BLASTing selected sequence at NCBI or Wormbase. Runs across Windows, OS X, and Linux/Unix.

Proper citation: A plasmid Editor (RRID:SCR_014266) Copy   

•   Source: SciCrunch Registry