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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
Curated collection of known Drosophila transcriptional cis-regulatory modules (CRMs) and transcription factor binding sites (TFBSs). Includes experimentally verified fly regulatory elements along with their DNA sequence, associated genes, and expression patterns they direct. Submission of experimentally verified cis-regulatory elements that are not included in REDfly database are welcome.
Proper citation: REDfly Regulatory Element Database for Drosophilia (RRID:SCR_006790) Copy
http://compbio.dfci.harvard.edu/tgi/
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.The goal of The Gene Index Project is to use the available Expressed Sequence Transcript (EST) and gene sequences, along with the reference genomes wherever available, to provide an inventory of likely genes and their variants and to annotate these with information regarding the functional roles played by these genes and their products. The promise of genome projects has been a complete catalog of genes in a wide range of organisms. While genome projects have been successful in providing reference genome sequences, the problem of finding genes and their variants in genomic sequence remains an ongoing challenge. TGI has created an inventory that contains genes and their variants together with description. In addition, this resource is attempting to use these catalogs to find links between genes and pathways in different species and to provide lists of features within completed genomes that can aid in the understanding of how gene expression is regulated. DATABASES *Eukaryotic Gene Orthologues (formerly known as TOGA - TIGR Orthologous Gene Alignment): Eukaryotic Gene Orthologues (EGO) at DFGI are generated by pair-wise comparison between the Tentative Consensus (TC) sequences that comprise the Dana Farber Gene Indices from individual organisms. The reciprocal pairs of the best match were clustered into individual groups and multiple sequence alignments were displayed for each group. *GeneChip Oncology Database (GCOD):Cancer gene expression database is a collection of publicly available microarray expression data on Affymetrix GeneChip Arrays related to human cancers. Currently only datasets with available raw data (Affymetrix .CEL files) are processed. All processed datasets were subjected to extensive manual curation, uniform processing and consistent quality control. You can browse the experiments in our collection, perform statistical analysis, and download processed data; or to search gene expression profiles using Entrez gene symbol, Unigene ID, or Affymetrix probeset ID. *Gene Indices: As of July 1, 2008, there are 111 publicly available gene indices. They are separated into 4 categories for better organization and easier access. Animal: 41, Plant: 45, Protist: 15, Fungal: 10 *Genomic Maps: Human, mouse, rat, chicken, drosophila melanogaster, zebrafish, mosquito, caenorhabditis elegans, Arabidopsis thaliana, rice, yeast, fission yeast Dana-Farber Cancer Institute (DFCI) Gene Indices Software Tools: *TGI Clustering tools (TGICL): a software system for fast clustering of large EST datasets. *GICL: this package contains the scripts and all the necessary pre-compiled binaries for 32bit Linux systems. *clview: an assembly file viewer. *SeqClean:a script for automated trimming and validation of ESTs or other DNA sequences by screening for various contaminants, low quality and low-complexity sequences. *cdbfasta/cdbyank: fast indexing/retrieval of fasta records from flat file databases. *DAS/XML Genomic Viewer The Genomic viewer borrows modules from http://www.biodas.org (lstein (at) cshl.org) & http://webreference.com.
Proper citation: Gene Index Project (RRID:SCR_002148) Copy
Software package for a DNA assembly program designed for de novo assembly of 25-40mer input fragments and deep sequence coverage.
Proper citation: SHARCGS (RRID:SCR_002026) Copy
http://www.cs.sunysb.edu/~skiena/shorty/
Software for targeted de novo assembly of microreads with mate pair information and sequencing errors.
Proper citation: SHORTY (RRID:SCR_002048) Copy
Database of genetic and molecular biological information about the filamentous fungi of the genus Aspergillus including information about genes and proteins of Aspergillus nidulans and Aspergillus fumigatus; descriptions and classifications of their biological roles, molecular functions, and subcellular localizations; gene, protein, and chromosome sequence information; tools for analysis and comparison of sequences; and links to literature information; as well as a multispecies comparative genomics browser tool (Sybil) for exploration of orthology and synteny across multiple sequenced Sgenus species. Also available are Gene Ontology (GO) and community resources. Based on the Candida Genome Database, the Aspergillus Genome Database is a resource for genomic sequence data and gene and protein information for Aspergilli. Among its many species, the genus contains an excellent model organism (A. nidulans, or its teleomorph Emericella nidulans), an important pathogen of the immunocompromised (A. fumigatus), an agriculturally important toxin producer (A. flavus), and two species used in industrial processes (A. niger and A. oryzae). Search options allow you to: *Search AspGD database using keywords. *Find chromosomal features that match specific properties or annotations. *Find AspGD web pages using keywords located on the page. *Find information on one gene from many databases. *Search for keywords related to a phenotype (e.g., conidiation), an allele (such as veA1), or an experimental condition (e.g., light). Analysis and Tools allow you to: *Find similarities between a sequence of interest and Aspergillus DNA or protein sequences. *Display and analyze an Aspergillus sequence (or other sequence) in many ways. *Navigate the chromosomes set. View nucleotide and protein sequence. *Find short DNA/protein sequence matches in Aspergillus. *Design sequencing and PCR primers for Aspergillus or other input sequences. *Display the restriction map for a Aspergillus or other input sequence. *Find similarities between a sequence of interest and fungal nucleotide or protein sequences. AspGD welcomes data submissions.
Proper citation: ASPGD (RRID:SCR_002047) Copy
http://www.pathwaycommons.org/pc
Database of publicly available pathways from multiple organisms and multiple sources represented in a common language. Pathways include biochemical reactions, complex assembly, transport and catalysis events, and physical interactions involving proteins, DNA, RNA, small molecules and complexes. Pathways were downloaded directly from source databases. Each source pathway database has been created differently, some by manual extraction of pathway information from the literature and some by computational prediction. Pathway Commons provides a filtering mechanism to allow the user to view only chosen subsets of information, such as only the manually curated subset. The quality of Pathway Commons pathways is dependent on the quality of the pathways from source databases. Pathway Commons aims to collect and integrate all public pathway data available in standard formats. It currently contains data from nine databases with over 1,668 pathways, 442,182 interactions,414 organisms and will be continually expanded and updated. (April 2013)
Proper citation: Pathway Commons (RRID:SCR_002103) Copy
Original SAMTOOLS package has been split into three separate repositories including Samtools, BCFtools and HTSlib. Samtools for manipulating next generation sequencing data used for reading, writing, editing, indexing,viewing nucleotide alignments in SAM,BAM,CRAM format. BCFtools used for reading, writing BCF2,VCF, gVCF files and calling, filtering, summarising SNP and short indel sequence variants. HTSlib used for reading, writing high throughput sequencing data.
Proper citation: SAMTOOLS (RRID:SCR_002105) Copy
Software package as distribution of ImageJ and ImageJ2 together with Java, Java3D and plugins organized into coherent menu structure. Used to assist research in life sciences.
Proper citation: Fiji (RRID:SCR_002285) Copy
http://ftp://ftp.ncbi.nlm.nih.gov/pub/mhc/rbc/Final Archive
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 23, 2019.BGMUT was database that provided publicly accessible platform for DNA sequences and curated set of blood mutation information. Data Archive are available at ftp://ftp.ncbi.nlm.nih.gov/pub/mhc/rbc/Final Archive.
Proper citation: Blood Group Antigen Gene Mutation Database (RRID:SCR_002297) Copy
Maintains and provides archival, retrieval and analytical resources for biological information. Central DDBJ resource consists of public, open-access nucleotide sequence databases including raw sequence reads, assembly information and functional annotation. Database content is exchanged with EBI and NCBI within the framework of the International Nucleotide Sequence Database Collaboration (INSDC). In 2011, DDBJ launched two new resources: DDBJ Omics Archive and BioProject. DOR is archival database of functional genomics data generated by microarray and highly parallel new generation sequencers. Data are exchanged between the ArrayExpress at EBI and DOR in the common MAGE-TAB format. BioProject provides organizational framework to access metadata about research projects and data from projects that are deposited into different databases.
Proper citation: DNA DataBank of Japan (DDBJ) (RRID:SCR_002359) Copy
http://www.unc.edu/~yunmli/shotgun.html
Software for short read simulating in order to facilitate sequencing-based study designs.
Proper citation: ShotGun (RRID:SCR_002529) Copy
http://ccmbweb.ccv.brown.edu/gibbs/gibbs.html
Software to identify motifs, conserved regions, in DNA or protein sequences.
Proper citation: Gibbs Motif Sampler (RRID:SCR_002550) Copy
http://www.ncbi.nlm.nih.gov/gap
Database developed to archive and distribute clinical data and results from studies that have investigated interaction of genotype and phenotype in humans. Database to archive and distribute results of studies including genome-wide association studies, medical sequencing, molecular diagnostic assays, and association between genotype and non-clinical traits.
Proper citation: NCBI database of Genotypes and Phenotypes (dbGap) (RRID:SCR_002709) Copy
http://colibread.inria.fr/discosnp/
Software designed for discovering Single Nucleotide Polymorphism (SNP) from raw sets of reads obtained with Next Generation Sequencers (NGS).
Proper citation: discoSnp (RRID:SCR_002612) Copy
http://bioinformatics.charite.de/superpred/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on November 24,2025. Publicly available web-server to predict medical indication areas based on properties and similarity of chemical compounds. The web-server translates a user-defined molecule into a structural fingerprint that is compared to about 6300 drugs, which are enriched by 7300 links to molecular targets of the drugs, derived through text mining followed by manual curation. Links to the affected pathways are provided. The similarity to the medical compounds is expressed by the Tanimoto coefficient that gives the structural similarity of two compounds. A similarity score higher than 0.85 results in correct ATC prediction for 81% of all cases. As the biological effect is well predictable, if the structural similarity is sufficient, the web-server allows prognoses about the medical indication area of novel compounds and to find new leads for known targets. The combination of physicochemical property and similarity searching provides the possibility to detect new biologically active compounds and novel targets for drug-like compounds. SuperPred can be applied for drug repositioning purposes, too. A further intention of SuperPred is to find side effects elicited by drugs caused through off-target hits.
Proper citation: SuperPred: Drug classification and target prediction (RRID:SCR_002691) Copy
Consortium founded to establish mechanism-based taxonomies for Alzheimer's and Parkinson's disease and other neurodegenerative disorders (NDD), with the goal of facilitating development of more effective and targeted treatments. To do this, the consortium collects and analyzes data to: * Create new ways to combine underutilized data currently available in the literature, public databases, and from private companies * Determine how to dynamically organize and structure different types of knowledge about NDD * Determine how to apply this knowledge to construct new patient group classification * Identify correlations between disease features at molecular, tissue or organ-specific, and clinical levels * Identify sub-groups of patients based on the molecular cause of their disease, as opposed to the nature and location of their symptoms * Deliver data, tools, and recommendations for the biomedical community in the treatment of NDD A mechanism-based taxonomy is hoped to advance the: # Description and organization of the indication-specific data # Linking of data to disease models, based on causal and correlative relationships The expected outcome of AETIONOMY is a new NDD taxonomy system that distinguishes mixed pathologies, allowing for new features or classes to be added into the taxonomy, all with the goal of aiding drug and biomarker discovery.
Proper citation: AETIONOMY (RRID:SCR_000232) Copy
http://deweylab.biostat.wisc.edu/rsem/
Software package for quantifying gene and isoform abundances from single end or paired end RNA Seq data. Accurate transcript quantification from RNA Seq data with or without reference genome. Used for accurate quantification of gene and isoform expression from RNA-Seq data.
Proper citation: RSEM (RRID:SCR_000262) Copy
http://bioconductor.org/packages/release/bioc/html/DESeq.html
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 30,2023. Software for differential gene expression analysis based on the negative binomial distribution. It estimates variance-mean dependence in count data from high-throughput sequencing assays and tests for differential expression.
Proper citation: DESeq (RRID:SCR_000154) Copy
https://sourceforge.net/projects/popbam/
A tool to perform evolutionary or population-based analyses of next-generation sequencing data. POPBAM takes a BAM file as its input and can compute many widely used evolutionary genetics measures in sliding windows across a genome.
Proper citation: POPBAM (RRID:SCR_000464) Copy
http://code.google.com/p/gasv/
Software tool for identifying structural variants (SVs) from paired-end sequencing data.GASV distribution includes three components that are typically run in succession: the BAM file of unique paired-read mappings is processed; structural variants are identified by clustering discordant fragments; and a probabilistic algorithm improves the specificity of GASV predictions.
Proper citation: GASV (RRID:SCR_000061) Copy
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