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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.
http://bioconductor.org/packages/release/bioc/html/sapFinder.html
An R software package, for detection of the variant peptides based on tandem mass spectrometry (MS/MS)-based proteomics data. It automates (1) variation-associated database construction, (2) database searching, (3) post-processing, (4) HTML-based report generation in shotgun proteomics.
Proper citation: sapFinder (RRID:SCR_002685) Copy
https://github.com/grenaud/leeHom
Software program for the Bayesian reconstruction of ancient DNA fragments. The algorithm removes the adaptors and reconstructs the original DNA sequences using a Bayesian maximum a posteriori probability approach.
Proper citation: leeHom (RRID:SCR_002710) Copy
http://andestools.sourceforge.net/
Software library and a suite of applications, written in Perl and R, for deep sequencing statistical analyses.
Proper citation: ANDES (RRID:SCR_002791) 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://www.bioconductor.org/packages/release/bioc/html/pathview.html
A tool set for pathway-based data integration and visualization. It maps and renders a wide variety of biological data on relevant pathway graphs. All users need is to supply their data and specify the target pathway. Pathview automatically downloads the pathway graph data, parses the data file, maps user data to the pathway, and render pathway graph with the mapped data. In addition, Pathview also seamlessly integrates with pathway and gene set (enrichment) analysis tools for large-scale and fully automated analysis.
Proper citation: Pathview (RRID:SCR_002732) 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
http://sourceforge.net/projects/bio-rainbow/
Software developed to provide an ultra-fast and memory-efficient solution to clustering and assembling short reads produced by RAD-seq.
Proper citation: Rainbow (RRID:SCR_002724) Copy
A Support Vector Machine-based classifier to assesses the protein-coding potential of a transcript based on six biologically meaningful sequence features. CPC can discriminate coding from noncoding transcripts with high accuracy and speed. In addition to predicting the coding potential of the input transcripts, the CPC web server also graphically displays detailed sequence features and additional annotations of the transcript that may facilitate users' further investigation. The coding potential calculator tool reads FASTA data format as input.
Proper citation: Coding Potential Calculator (RRID:SCR_002764) Copy
http://www.bioconductor.org/packages/release/bioc/html/rBiopaxParser.html
A software package that provides a comprehensive set of functions for parsing, viewing and modifying BioPAX pathway data within R. At the moment BioPAX level 2 and level 3 are supported.
Proper citation: rBiopaxParser (RRID:SCR_002744) Copy
Computable knowledge regarding functions of genes and gene products. GO resources include biomedical ontologies that cover molecular domains of all life forms as well as extensive compilations of gene product annotations to these ontologies that provide largely species-neutral, comprehensive statements about what gene products do. Used to standardize representation of gene and gene product attributes across species and databases.
Proper citation: Gene Ontology (RRID:SCR_002811) Copy
https://github.com/itojal/hot_scan
A free software to detect genomic regions unusually rich in translocation breakpoints. More generally, it may be used to detect a region that is unusually rich in a given character of a binary sequence.
Proper citation: hot scan (RRID:SCR_002840) Copy
A database designed for plant comparative and functional genomics based on complete genomes. It comprises complete proteome sequences from the major phylum of plant evolution. The clustering of these proteomes was performed to define a consistent and extensive set of homeomorphic plant families. Based on this, lists of gene families such as plant or species specific families and several tools are provided to facilitate comparative genomics within plant genomes. The analyses follow two main steps: gene family clustering and phylogenomic analysis of the generated families. Once a group of sequences (cluster) is validated, phylogenetic analyses are performed to predict homolog relationships such as orthologs and ultraparalogs.
Proper citation: GreenPhylDB (RRID:SCR_002834) Copy
http://www.ncbi.nlm.nih.gov/biosystems/
Database that provides access to biological systems and their component genes, proteins, and small molecules, as well as literature describing those biosystems and other related data throughout Entrez. A biosystem, or biological system, is a group of molecules that interact directly or indirectly, where the grouping is relevant to the characterization of living matter. BioSystem records list and categorize components, such as the genes, proteins, and small molecules involved in a biological system. The companion FLink tool, in turn, allows you to input a list of proteins, genes, or small molecules and retrieve a ranked list of biosystems. A number of databases provide diagrams showing the components and products of biological pathways along with corresponding annotations and links to literature. This database was developed as a complementary project to (1) serve as a centralized repository of data; (2) connect the biosystem records with associated literature, molecular, and chemical data throughout the Entrez system; and (3) facilitate computation on biosystems data. The NCBI BioSystems Database currently contains records from several source databases: KEGG, BioCyc (including its Tier 1 EcoCyc and MetaCyc databases, and its Tier 2 databases), Reactome, the National Cancer Institute's Pathway Interaction Database, WikiPathways, and Gene Ontology (GO). It includes several types of records such as pathways, structural complexes, and functional sets, and is desiged to accomodate other record types, such as diseases, as data become available. Through these collaborations, the BioSystems database facilitates access to, and provides the ability to compute on, a wide range of biosystems data. If you are interested in depositing data into the BioSystems database, please contact them.
Proper citation: NCBI BioSystems Database (RRID:SCR_004690) Copy
A web-based browser for Gene Ontology terms and annotations, which is provided by the UniProtKB-GOA group at the EBI. It is able to offer a range of facilities including bulk downloads of GO annotation data which can be extensively filtered by a range of different parameters and GO slim set generation. The software for QuickGO is freely available under the Apache 2 license. QuickGO can supply GO term information and GO annotation data via REST web services.
Proper citation: QuickGO (RRID:SCR_004608) Copy
https://sites.google.com/a/lbl.gov/biopig/
Software providing a framework for genomic data analysis using Apache Pig and Hadoop.
Proper citation: BioPig (RRID:SCR_004636) Copy
An interactive, visual database containing more than 350 small molecule pathways found in humans. More than 2/3 of these pathways (>280) are not found in any other pathway database. SMPDB is designed specifically to support pathway elucidation and pathway discovery in metabolomics, transcriptomics, proteomics and systems biology. It is able to do so, in part, by providing exquisitely detailed, fully searchable, hyperlinked diagrams of human metabolic pathways, metabolic disease pathways, metabolite signaling pathways and drug-action pathways. All SMPDB pathways include information on the relevant organs, subcellular compartments, protein cofactors, protein locations, metabolite locations, chemical structures and protein quaternary structures. Each small molecule is hyperlinked to detailed descriptions contained in the HMDB or DrugBank and each protein or enzyme complex is hyperlinked to UniProt. All SMPDB pathways are accompanied with detailed descriptions and references, providing an overview of the pathway, condition or processes depicted in each diagram. The database is easily browsed and supports full text, sequence and chemical structure searching. Users may query SMPDB with lists of metabolite names, drug names, genes / protein names, SwissProt IDs, GenBank IDs, Affymetrix IDs or Agilent microarray IDs. These queries will produce lists of matching pathways and highlight the matching molecules on each of the pathway diagrams. Gene, metabolite and protein concentration data can also be visualized through SMPDB''s mapping interface. All of SMPDB''s images, image maps, descriptions and tables are downloadable.
Proper citation: Small Molecule Pathway Database (RRID:SCR_004844) Copy
http://www.ncbi.nlm.nih.gov/probe
Public registry of nucleic acid reagents designed for use in a wide variety of biomedical research applications including genotyping, gene expression studies, SNP discovery, genome mapping, and gene silencing. Probe records contain information on reagent distributors, probe effectiveness, and computed sequence similarities. The database is constantly updated, with over 11,000,000 probes available. Users may deposit their data into NCBI Probe Database.
Proper citation: NCBI Probe (RRID:SCR_004816) Copy
http://bioinformatics.rutgers.edu/Software/SLiQ/
Software for simple linear inequalities based Mate-Pair reads filtering and scaffolding. A set of simple linear inequalities (SLIQ) derived from the geometry of contigs on the line that can be used to predict the relative positions and orientations of contigs from individual mate pair reads and thus produce a contig digraph. The SLIQ inequalities can also filter out unreliable mate pairs and can be used as a pre-processing step for any scaffolding algorithm. This tool filters mate pairs and then produces a Directed Contig Graph (contig diGraph). Also provided is a Naive scaffolder that can then produce scaffolds out of the contig diGraph.
Proper citation: SLIQ (RRID:SCR_005003) Copy
Web service for permanent archiving and sharing of all types of personally identifiable genetic and phenotypic data resulting from biomedical research projects. The repository allows you to explore datasets from numerous genotype experiments, supplied by a range of data providers. The EGA''s role is to provide secure access to the data that otherwise could not be distributed to the research community. The EGA contains exclusive data collected from individuals whose consent agreements authorize data release only for specific research use or to bona fide researchers. Strict protocols govern how information is managed, stored and distributed by the EGA project. As an example, only members of the EGA team are allowed to process data in a secure computing facility. Once processed, all data are encrypted for dissemination and the encryption keys are delivered offline. The EGA also supports data access only for the consortium members prior to publication.
Proper citation: European Genome phenome Archive (RRID:SCR_004944) Copy
http://www.physics.rutgers.edu/~anirvans/SOPRA/
Software tool to exploit the mate pair/paired-end information for assembly of short reads from high throughput sequencing platforms, e.g. Illumina and SOLiD.
Proper citation: SOPRA (RRID:SCR_005035) Copy
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