Tools   Select Another Resource Report Type

http://manaslu.fiserlab.org/MMM/

Web server for modeling protein structure by using Multiple Mapping Method. Approach to sequence-to-structure alignment in comparative protein structure modeling.

Proper citation: Multiple Mapping Method Server (RRID:SCR_018015) Copy   

•   Source: SciCrunch Registry

https://github.com/r3fang/SnapTools

Software tool as module for working with snap files in Python. Snap files are designed for storing single nucleus ATAC-seq datasets.

Proper citation: SnapTools (RRID:SCR_018097) Copy   

•   Source: SciCrunch Registry

http://research-pub.gene.com/gmap/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. A software program for mapping and aligning cDNA sequences to a genome. The program maps and aligns a single sequence with minimal startup time and memory requirements, and provides fast batch processing of large sequence sets. The program generates accurate gene structures, even in the presence of substantial polymorphisms and sequence errors, without using probabilistic splice site models. Methodology underlying the program includes a minimal sampling strategy for genomic mapping, oligomer chaining for approximate alignment, sandwich DP for splice site detection, and microexon identification with statistical significance testing.

Proper citation: GMAP (RRID:SCR_008992) Copy   

•   Source: SciCrunch Registry

https://gmod.org/wiki/CMap.1

Web-based tool that allows users to view comparisons of genetic and physical maps. The package also includes tools for curating map data. (entry from Genetic Analysis Software)

Proper citation: CMAP (RRID:SCR_009034) Copy   

•   Source: SciCrunch Registry

http://www.evocontology.org/site/Main/EvocOntologyDotOrg

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 September 6, 2016. Set of orthogonal controlled vocabularies that unifies gene expression data by facilitating a link between the genome sequence and expression phenotype information. The system associates labelled target cDNAs for microarray experiments, or cDNA libraries and their associated transcripts with controlled terms in a set of hierarchical vocabularies. eVOC consists of four orthogonal controlled vocabularies suitable for describing the domains of human gene expression data including Anatomical System, Cell Type, Pathology and Developmental Stage. The four core eVOC ontologies provide an appropriate set of detailed human terms that describe the sample source of human experimental material such as cDNA and SAGE libraries. These expression terms are linked to libraries and transcripts allowing the assessment of tissue expression profiles, differential gene expression levels and the physical distribution of expression across the genome. Analysis is currently possible using EST and SAGE data, with microarray data being incorporated. The eVOC data is increasingly being accepted as a standard for describing gene expression and eVOC ontologies are integrated with the Ensembl EnsMart database, the Alternate Transcript Diversity Project and the UniProt Knowledgebase. Several groups are currently working to provide shared development of this resource such that it is of maximum use in unifying transcript expression information.

Proper citation: eVOC (RRID:SCR_010704) Copy   

•   Source: SciCrunch Registry

https://www.mdc-berlin.de/8551903/en/research/research_teams/systems_biology_of_gene_regulatory_elements/projects/miRDeep

Software tool to identify known and novel miRNA genes in seven animal clades by analyzing sequenced RNAs. Used for discovering known and novel miRNAs from small RNA sequencing data.

Proper citation: miRDeep (RRID:SCR_010829) Copy   

•   Source: SciCrunch Registry

http://mafft.cbrc.jp/alignment/server/

Software package as multiple alignment program for amino acid or nucleotide sequences. Can align up to 500 sequences or maximum file size of 1 MB. First version of MAFFT used algorithm based on progressive alignment, in which sequences were clustered with help of Fast Fourier Transform. Subsequent versions have added other algorithms and modes of operation, including options for faster alignment of large numbers of sequences, higher accuracy alignments, alignment of non-coding RNA sequences, and addition of new sequences to existing alignments.

Proper citation: MAFFT (RRID:SCR_011811) Copy   

•   Source: SciCrunch Registry

https://github.com/MikkelSchubert/adapterremoval

Software program to remove residual adapter sequences from next generation sequencing reads. Used for cleaning of next-generation sequencing reads. AdapterRemoval v2 introduces improvements in throughput, through use of single instruction, multiple data (SIMD; SSE1 and SSE2) instructions and multi-threading support; handles datasets containing reads or read-pairs with different adapters or adapter pairs; provides simultaneous demultiplexing and adapter trimming; has ability to reconstruct adapter sequences from paired-end reads for poorly documented data sets; provides native gzip and bzip2 support.

Proper citation: AdapterRemoval (RRID:SCR_011834) Copy   

•   Source: SciCrunch Registry

http://www.cmhd.ca/

Multidisciplinary collaboration undertaking genome-wide mutagenesis to functionally annotate the mouse genome and develop new mouse models relevant to human disease. To achieve these goals two major research platforms are carried out: Gene trapping and ENU Mutagenesis. A new challenge is faced in the post-genomic era - the assignment of biological function to the human genome sequence and projecting that assignment into understanding of human health and disease. The Centre for Modeling Human Disease (CMHD) was established to take part in the worldwide initiative to address these challenges. At the CMHD, two fundamentally different, yet complimentary methods are employed to generate mutant mouse models of human disease: chemical mutagenesis by ethylnitrosourea (ENU), and gene trap insertional mutagenesis. The Centre contributes its resources to similar international efforts and is the first of its kind in Canada. The Center is also actively developing other mutagenic strategies including pharmacologic and genetic modifier screens to dissect disease pathways, and novel mutagenic techniques using embryonic stem cells. ENU Database * Statistics for Mouse Physiological Parameters * Search Mutants by Phenotype * Search Mutants by Heritability Gene Trap Database * Search by in vitro Expression Pattern * Search by Gene Trap Sequences CMHD Members Only (must register and login) * Search Mouse Line * Histopathology * Sperm, Tissue, Slide Archiving * CMHD Database Download CMHD Services * Phenotyping * Genetic Mapping * Pathology * Pathology Service Charges

Proper citation: CMHD - Centre for Modeling Human Disease (RRID:SCR_006101) Copy   

•   Source: SciCrunch Registry

http://www.nematodes.org/NeglectedGenomes/MOLLUSCA/index.html

A database housing EST information from nine mollusc species, including Lymnaea stagnalis, the pond snail. Co-curated with Angus davison of Nottingham University.

Proper citation: MolluscDB PartiGene database (RRID:SCR_006069) Copy   

•   Source: SciCrunch Registry

http://www.biocomputing.it/digit/index.php

The Database of Immunoglobulins and Integrated Tools (DIG IT) is an integrated resource storing sequences of annotated immunoglobulin variable domains of NCBI database and enriched with tools for searching and analyzing them. It contains 145759 heavy chain sequences and 71404 light chain sequences (47168 kappa type and 24236 lambda type) with assigned canonical structures for the hypervariable loops and the data on the type of antigen as well as the pairing information of immunoglobulin heavy and light chains (9672 total pairs). The user can input the immunoglobulin variable domain sequence (amino acid or nucleotide) of interest (heavy chain variable domain sequence; light chain variable domain sequence or both) to retrieve the closest sequences (sorted according to e-value) with complete annotation. The user can also directly query the database by antigen type, canonical structure, germline family in accordance to the requirements.

Proper citation: DIG IT - Database of Immunoglobulins and Integrated Tools (RRID:SCR_005924) Copy   

•   Source: SciCrunch Registry

http://db-mml.sjtu.edu.cn/ICEberg/

ICEberg is an integrated database that provides comprehensive information about integrative and conjugative elements (ICEs) found in bacteria. ICEs are conjugative self-transmissible elements that can integrate into and excise from a host chromosome. An ICE contains three typical modules, integration and excision, conjugation, and regulation modules, that collectively promote vertical inheritance and periodic lateral gene flow. Many ICEs carry likely virulence determinants, antibiotic-resistant factors and/or genes coding for other beneficial traits. ICEberg offers a unique, highly organized, readily explorable archive of both predicted and experimentally supported ICE-relevant data. It currently contains details of 428 ICEs found in representatives of 124 bacterial species, and a collection of >400 directly related references. A broad range of similarity search, sequence alignment, genome context browser, phylogenetic and other functional analysis tools are readily accessible via ICEberg. ICEberg will facilitate efficient, multidisciplinary and innovative exploration of bacterial ICEs and be of particular interest to researchers in the broad fields of prokaryotic evolution, pathogenesis, biotechnology and metabolism. The ICEberg database will be maintained, updated and improved regularly to ensure its ongoing maximum utility to the research community.

Proper citation: ICEberg (RRID:SCR_006026) Copy   

•   Source: SciCrunch Registry

http://hcv.lanl.gov/content/sequence/HCV/ToolsOutline.html

The HCV sequence database collects and annotates sequence data and provides them to the public via a website that contains a user-friendly search interface and a large number of sequence analysis tools, based on the model of the highly regarded Los Alamos HIV database. The hepatitis C virus (HCV) is a significant threat to public health worldwide. The virus is highly variable and evolves rapidly, making it an elusive target for the immune system and for vaccine and drug design. At present, some 30 000 HCV sequences have been published. This central website provides annotated sequences and analysis tools that will be helpful to HCV scientists worldwide. Things you can do: * Find sequences in the database * Download sequences from the database * Retrieve data about the sequences * Analyze sequences * Work with the sequences using our tools * Download ready-made alignments The HCV sequence database was officially launched in September 2003. Since then, its usage has steadily increased and is now at an average of approximately 280 visits per day from distinct IP addresses.

Proper citation: HCV Sequence Database (RRID:SCR_006019) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/bioinformatics/PRED-GPCR/

A prediction tool for GPCR Family Classification from sequence alone based on a probabilistic method that uses family-specific profile Hidden Markov Models. The PRED-GPCR system is based on a probabilistic method that uses family specific profile HMMs in order to determine to which GPCR family a query sequence belongs or resembles. The approach proposed in this method exploits the descriptive power of profile HMMs along with an exhaustive discrimination assessment method to select only highly selective and sensitive profiles, for each family. The collection of these profiles constitutes a signature library, which is scanned, for significant matches with a given query sequence. The output report for a query sequence consists of two sections: * A ranked list of the profile HMM matches, below the selected individual motif E-value cutoff, along with their corresponding family. * A ranked list of the Combined P-values, E-values as well as the number of profiles matched for each family. To cross-evaluate your results you can browse through Swiss-Prot, Trembl, Pfam and Prosite family related entries.

Proper citation: PRED-GPCR (RRID:SCR_006196) Copy   

•   Source: SciCrunch Registry

http://www.pseudomonas.com/

Database of peer-reviewed, continually updated annotation for the Pseudomonas aeruginosa PAO1 reference strain genome expanded to include all Pseudomonas species to facilitate cross-strain and cross-species genome comparisons with high quality comparative genomics. The database contains robust assessment of orthologs, a novel ortholog clustering method, and incorporates five views of the data at the sequence and annotation levels (Gbrowse, Mauve and custom views) to facilitate genome comparisons. Other features include more accurate protein subcellular localization predictions and a user-friendly, Boolean searchable log file of updates for the reference strain PAO1. The current annotation is updated using recent research literature and peer-reviewed submissions by a worldwide community of PseudoCAP (Pseudomonas aeruginosa Community Annotation Project) participating researchers. If you are interested in participating, you are invited to get involved. Many annotations, DNA sequences, Orthologs, Intergenic DNA, and Protein sequences are available for download.

Proper citation: Pseudomonas Genome Database (RRID:SCR_006590) Copy   

•   Source: SciCrunch Registry

https://docs.python.org/2/library/random.html

This module implements pseudo-random number generators for various distributions. For integers, uniform selection from a range. For sequences, uniform selection of a random element, a function to generate a random permutation of a list in-place, and a function for random sampling without replacement. On the real line, there are functions to compute uniform, normal (Gaussian), lognormal, negative exponential, gamma, and beta distributions. For generating distributions of angles, the von Mises distribution is available. Sponsors: This resource is supported by ASTi logo Advanced Simulation Technology Inc. (ASTi); Array BioPharma Inc.; BizRate.com; Canonical Ltd.; CCP Games; cPacket Networks; EarnMyDegree.com; Enthought Inc.; Exoweb Ltd.; Google; HitMeister Inc.; IronPort Systems; KNMP; Lucasfilm; Madison Tyler LLC.; Merfin, LLC.; Microsoft; OpenEye Scientific Software; Opsware, Inc.; O''Reilly & Associates, Inc.; PropertySold.ca; Rogue Wave; SEO Moves; Strakt Holdings, Inc.; Sun Microsystems; Tabblo; ZeOmega, LLC., and Zope Corporation.

Proper citation: Generate Pseudo-Random Numbers (RRID:SCR_006535) Copy   

•   Source: SciCrunch Registry

https://github.com/vasilislenis/G-Anchor

Software for comparing large genomes and exploiting highly conserved sequences as evolutionary-stable "anchors". The pipeline maps a newly sequenced genome (assembled in scaffolds) on a reference genome without the need of a supercomputer.

Proper citation: G-Anchor (RRID:SCR_016046) Copy   

•   Source: SciCrunch Registry

https://gitlab.com/SimonHTausch/HiLive

Software tool for performing read mapping that maps Illumina HiSeq sequencer read alignments when they are produced. Used in Next Generation Sequencing in time critical, clinical applications.

Proper citation: HiLive (RRID:SCR_016134) Copy   

•   Source: SciCrunch Registry

http://fsa.sourceforge.net/

Software for a statistical multiple sequence alignment algorithm which uses a "distance-based" approach to align homologous protein, RNA or DNA sequences. The GUI, MAD (Multiple Alignment Display), can display the intermediate alignments produced by FSA, where each character is colored according to the probability that it is correctly aligned.

Proper citation: FSA (RRID:SCR_016114) Copy   

•   Source: SciCrunch Registry

https://github.com/Ashod/garli

Software application for inferring phylogenetic trees and analysis of molecular sequence data using the maximum-likelihood criterion. It implements nucleotide, amino acid and codon-based models of sequence evolution.

Proper citation: GARLI (RRID:SCR_016117) Copy   

•   Source: SciCrunch Registry