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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://equilibrator.weizmann.ac.il/
Web interface designed for thermodynamic analysis of biochemical systems. eQuilibrator enables free-text search for biochemical compounds and reactions and provides thermodynamic estimates for both in a variety of conditions. It can provide estimates for compounds in the KEGG database, and individual compounds and enzymes can be searched for by their common names (water, glucosamine, hexokinase). Reactions can be entered in a free-text format that eQuilibrator parses automatically. eQuilibrator also allows manipulation of the conditions of a reaction - pH, ionic strength, and reactant and product concentrations.
Proper citation: eQuilibrator (RRID:SCR_006011) Copy
http://aias.biol.uoa.gr/OMPdb/
A database of Beta-barrel outer membrane proteins from Gram-negative bacteria. The web interface of OMPdb offers the user the ability not only to view the available data, but also to submit advanced queries for text search within the database''s protein entries or run BLAST searches against the database. The most up-to-date version of the database (as well as all past versions) can be downloaded in various formats (flat text, XML format or raw FASTA sequences). For constructing OMPdb, multiple freely accessible resources were combined and a detailed literature search was performed. The classification of OMPdb''s protein entries into families is based mainly on structural and functional criteria. Information included in the database consists of sequence data, as well as annotation for structural characteristics (such as the transmembrane segments), literature references and links to other public databases, features that are unique worldwide. Along with the database, a collection of profile Hidden Markov Models that were shown to be characteristic for Beta-barrel outer membrane proteins was also compiled. This set, when used in combination with our previously developed algorithms (PRED-TMBB, MCMBB and ConBBPRED) will serve as a powerful tool in matters of discrimination and classification of novel Beta-barrel proteins and whole-genome analyses., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: OMPdb (RRID:SCR_006221) Copy
http://www.bioconductor.org/packages/devel/bioc/html/deepSNV.html
Software package that provides quantitative variant callers for detecting subclonal mutations in ultra-deep (>=100x coverage) sequencing experiments. The algorithm is used for a comparative setup with a control experiment of the same loci and uses a beta-binomial model and a likelihood ratio test to discriminate sequencing errors and subclonal SNVs (single nucleotide variants).
Proper citation: deepSNV (RRID:SCR_006214) Copy
http://evolution.genetics.washington.edu/phylip.html
A free package of software programs for inferring phylogenies (evolutionary trees). The source code is distributed (in C), and executables are also distributed. In particular, already-compiled executables are available for Windows (95/98/NT/2000/me/xp/Vista), Mac OS X, and Linux systems. Older executables are also available for Mac OS 8 or 9 systems.
Proper citation: PHYLIP (RRID:SCR_006244) Copy
http://stormo.wustl.edu/ScerTF
Catalog of over 1,200 position weight matrices (PWMs) for 196 different yeast transcription factors (TFs). They've curated 11 literature sources, benchmarked the published position-specific scoring matrices against in-vivo TF occupancy data and TF deletion experiments, and combined the most accurate models to produce a single collection of the best performing weight matrices for Saccharomyces cerevisiae. ScerTF is useful for a wide range of problems, such as linking regulatory sites with transcription factors, identifying a transcription factor based on a user-input matrix, finding the genes bound/regulated by a particular TF, and finding regulatory interactions between transcription factors. Enter a TF name to find the recommended matrix for a particular TF, or enter a nucleotide sequence to identify all TFs that could bind a particular region.
Proper citation: ScerTF (RRID:SCR_006121) Copy
http://www-bionet.sscc.ru/sitex/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2019. Analyzing protein structure projection on exon-intron structure of corresponding gene through years led to several fundamental conclusions about structural and functional organization of the protein. According to these results we decided to map the protein functional sites. So we created the database SitEx that keep the information about this mapping and included the BLAST search and 3D similar structure search using PDB3DScan for the polypeptide encoded by one exon, participating in organizing the functional site. This will help: # to study the positions of the functional sites in exon structure; # to make the complex analysis of the protein function; # to exposure the exons that took part in exon shuffling and came from bacterial genomes; # to study the peculiarities of coding the polypeptide structures. Currently, SitEx contains information about 9994 functional sites presented in 2021 proteins described in proteomes of 17 organisms.
Proper citation: SitEx (RRID:SCR_006122) Copy
https://compbio.dfci.harvard.edu/predictivenetworks//
A flexible, open-source, web-based application and data services framework that enables the integration, navigation, visualization and analysis of gene interaction networks. The primary goal of PN is to allow biomedical researchers to evaluate experimentally derived gene lists in the context of large-scale gene interaction networks. The PN analytical pipeline involves two key steps. The first is the collection of a comprehensive set of known gene interactions derived from a variety of publicly available sources. The second is to use these ''known'' interactions together with gene expression data to infer robust gene networks. The regression-based network inference algorithm creates a graph of gene interactions in which cycles may be present (but no self-loops). Based on information-theoretic techniques, a causal gene interaction network is inferred from both prior knowledge (interactions extracted from biomedical literature and structured biological databases) and gene expression data. A prediction model is fitted for each gene, given its parents, enabling assessment of the predictive ability of the network model.
Proper citation: Predictive Networks (RRID:SCR_006110) Copy
http://202.38.126.151:8080/SDisease/
Curated database of experimentally supported data of RNA Splicing mutation and disease. The RNA Splicing mutations include cis-acting mutations that disrupt splicing and trans-acting mutations that affecting RNA-dependent functions that cause disease. Information such as EntrezGeneID, gene genomic sequence, mutation (nucleotide substitutions, deletions and insertions), mutation location within the gene, organism, detailed description of the splicing mutation and references are also given. Users are able to submit new entries to the database. This database integrating RNA splicing and disease associations would be helpful for understanding not only the RNA splicing but also its contribution to disease. In SpliceDisease database, they manually curated 2337 splicing mutation disease entries involving 303 genes and 370 diseases, which have been supported experimentally in 898 publications. The SpliceDisease database provides information including the change of the nucleotide in the sequence, the location of the mutation on the gene, the reference PubMed ID and detailed description for the relationship among gene mutations, splicing defects and diseases. They standardized the names of the diseases and genes and provided links for these genes to NCBI and UCSC genome browser for further annotation and genomic sequences. For the location of the mutation, they give direct links of the entry to the respective position/region in the genome browser.
Proper citation: SpliceDisease (RRID:SCR_006130) Copy
Collection of chemical structures. Provides access to structures, properties and associated information from hundreds of data sources to find compounds of interest and provides services to improve this data by curation and annotation and to integrate it with users applications.
Proper citation: ChemSpider (RRID:SCR_006360) Copy
http://cran.r-project.org/web/packages/QCGWAS/
Software tools for (automated and manual) quality control of the results of Genome Wide Association Studies.
Proper citation: QCGWAS (RRID:SCR_006408) Copy
http://dna.engr.uconn.edu/?page_id=105
Software package that can be used to infer isoform and gene expression levels from high-throughput transcriptome sequencing (RNA-Seq) data.
Proper citation: IsoEM (RRID:SCR_009993) Copy
http://code.google.com/p/bitseq/
A software application for inferring expression levels of individual transcripts from sequencing (RNA-Seq) data and estimating differential expression (DE) between conditions.
Proper citation: BitSeq (RRID:SCR_009904) Copy
A cross-platform software program for Bayesian MCMC analysis of molecular sequences. It is entirely orientated towards rooted, time-measured phylogenies inferred using strict or relaxed molecular clock models. It can be used as a method of reconstructing phylogenies but is also a framework for testing evolutionary hypotheses without conditioning on a single tree topology. BEAST uses MCMC to average over tree space, so that each tree is weighted proportional to its posterior probability. We include a simple to use user-interface program for setting up standard analyses and a suit of programs for analysing the results.
Proper citation: BEAST (RRID:SCR_010228) Copy
Web application to generate sequence logos, graphical representations of patterns within multiple sequence alignment. Designed to make generation of sequence logos easy. Sequence logo generator.
Proper citation: WEBLOGO (RRID:SCR_010236) Copy
http://www.genome.umd.edu/masurca.html
A whole genome assembly software that combines the efficiency of the de Bruijn graph and Overlap-Layout-Consensus (OLC) approaches., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: MaSuRCA (RRID:SCR_010691) Copy
http://pathema.jcvi.org/Pathema/index.html
Pathema is one of the eight Bioinformatics Resource Centers designed to serve as a core resource for the bio-defense and infectious disease research community. Pathema strives to support basic research and accelerate scientific progress for understanding, detecting, diagnosing and treating an established set of six target NIAID Category A-C pathogens: Category A priority pathogens; Bacillus anthracis and Clostridium botulinum, and Category B priority pathogens; Burkholderia mallei, Burkholderia pseudomallei, Clostridium perfringens and Entamoeba histolytica. Each target pathogen is represented in one of four distinct clade-specific Pathema web resources and underlying databases developed to target the specific data and analysis needs of each scientific community. All publicly available complete genome projects of phylogenetically related organisms are also represented, providing a comprehensive collection of organisms for comparative analyses. Pathema facilitates the scientific exploration of genomic and related data through its integration with web-based analysis tools, customized to obtain, display, and compute results relevant to ongoing pathogen research. Pathema serves the bio-defense and infectious disease research community by disseminating data resulting from pathogen genome sequencing projects and providing access to the results of inter-genomic comparisons for these organisms. The Pathema BRC contract ends in December 2009. At that time JCVI will cease maintenance of the Pathema web resource and data. The PATRIC team, located at the Virginia Bioinformatics Institute, created and maintains a consolidated BRC for all of the NIAID category A-C priority pathogenic bacteria. The EuPathDB team at the University of Pennsylvania will support all eukaryotic pathogens. Pathema transferred all data and software to PATRIC and EuPathDB for incorporation into their new Web-based bioinformatics resource.
Proper citation: Pathema (RRID:SCR_010585) Copy
http://icy.bioimageanalysis.org/
An open community platform for bioimage informatics providing the software resources to visualize, annotate and quantify bioimaging data. To bridge the gap between developers and users, it combines: a) an open-source image analysis software, offering a powerful and flexible environment for developers such as applied mathematicians to write algorithms fast and efficiently; b) a common set of tools to view and manipulate data, and a set of plugins to perform specific quantification or analysis on images; c) a community-based website centralizing all plugins and resources to facilitate their management and maximize their visibility towards users. Workspaces are virtual groups of plugins dedicated to a specific application or image processing domain. By downloading a workspace, ICY automatically installs all corresponding plugins. The workspaces are enabled, but the editing section is not ready yet. If you want to publish a plugin on this website, its code has to be GPL. Source code is available and provided in each application download.
Proper citation: icy (RRID:SCR_010587) Copy
Software package for sequence alignment, assembly and analysis. Integrated and extendable desktop software platform for organization and analysis of sequence data. Bioinformatics software platform packed with molecular biology and sequence analysis tools.
Proper citation: Geneious (RRID:SCR_010519) Copy
http://compbio.cs.toronto.edu/CNVer/
A method for CNV detection that supplements the depth-of-coverage with paired-end mapping information, where matepairs mapping discordantly to the reference serve to indicate the presence of variation.
Proper citation: CNVer (RRID:SCR_010820) Copy
http://www.popgen.dk/software/index.php/Relate
Software providing a method that estimates the probability of sharing alleles identity by descent (IBD) across the genome and can also be used for mapping disease loci using distantly related individuals.
Proper citation: Relate (RRID:SCR_010794) Copy
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