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https://bitbucket.org/dkessner/forqs

Software for forward-in-time population genetics simulation that tracks individual haplotype chunks as they recombine each generation. It also also models quantitative traits and selection on those traits.

Proper citation: forqs (RRID:SCR_000643) Copy   

•   Source: SciCrunch Registry

http://www.brown.edu/Research/Istrail_Lab/hapcompass.php

Software that utilizes a fast cycle basis algorithm for the accurate haplotype assembly of sequence data. It is able to create pairwise SNP phasings.

Proper citation: HapCompass (RRID:SCR_000942) Copy   

•   Source: SciCrunch Registry

http://ccb.jhu.edu/software/sim4cc/

Software tool as cross species spliced alignment program.Heuristic sequence alignment tool for comparing cDNA sequence with genomic sequence containing homolog of gene in another species.

Proper citation: sim4cc (RRID:SCR_001204) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://www.broadinstitute.org/genome_bio/siphy/

Software that implements rigorous statistical tests to detect bases under selection from a multiple alignment data. It takes full advantage of deeply sequenced phylogenies to estimate both unlikely substitution patterns as well as slowdowns or accelerations in mutation rates. It can be applied as an Hidden Markov Model (HMM), in sliding windows, or to specific regions.

Proper citation: SiPhy (RRID:SCR_000564) Copy   

•   Source: SciCrunch Registry

https://kepler-project.org/

Kepler is a software application for analyzing and modeling scientific data. Using Kepler''s graphical interface and components, scientists with little background in computer science can create executable models, called scientific workflows, for flexibly accessing scientific data (streaming sensor data, medical and satellite images, simulation output, observational data, etc.) and executing complex analyses on this data. Kepler is developed by a cross-project collaboration led by the Kepler/CORE team. The software builds upon the mature Ptolemy II framework, developed at the University of California, Berkeley. Ptolemy II is a software framework designed for modeling, design, and simulation of concurrent, real-time, embedded systems. The Kepler Project is dedicated to furthering and supporting the capabilities, use, and awareness of the free and open source, scientific workflow application, Kepler. Kepler is designed to help scien��tists, analysts, and computer programmers create, execute, and share models and analyses across a broad range of scientific and engineering disciplines. Kepler can operate on data stored in a variety of formats, locally and over the internet, and is an effective environment for integrating disparate software components, such as merging R scripts with compiled C code, or facilitating remote, distributed execution of models. Using Kepler''s graphical user interface, users simply select and then connect pertinent analytical components and data sources to create a scientific workflowan executable representation of the steps required to generate results. The Kepler software helps users share and reuse data, workflows, and compo��nents developed by the scientific community to address common needs. Kepler is a java-based application that is maintained for the Windows, OSX, and Linux operating systems. The Kepler Project supports the official code-base for Kepler development, as well as provides materials and mechanisms for learning how to use Kepler, sharing experiences with other workflow developers, reporting bugs, suggesting enhancements, etc. The Kepler Project Leadership Team works to assure the long-term technical and financial viability of Kepler by making strategic decisions on behalf of the Kepler user community, as well as providing an official and durable point-of-contact to articulate and represent the interests of the Kepler Project and the Kepler software application. Details about how to get more involved with the Kepler Project can be found in the developer section of this website.

Proper citation: Kepler (RRID:SCR_005252) Copy   

•   Source: SciCrunch Registry

http://www.bioextract.org/GuestLogin

An open, web-based system designed to aid researchers in the analysis of genomic data by providing a platform for the creation of bioinformatic workflows. Scientific workflows are created within the system by recording tasks performed by the user. These tasks may include querying multiple, distributed data sources, saving query results as searchable data extracts, and executing local and web-accessible analytic tools. The series of recorded tasks can then be saved as a reproducible, sharable workflow available for subsequent execution with the original or modified inputs and parameter settings. Integrated data resources include interfaces to the National Center for Biotechnology Information (NCBI) nucleotide and protein databases, the European Molecular Biology Laboratory (EMBL-Bank) non-redundant nucleotide database, the Universal Protein Resource (UniProt), and the UniProt Reference Clusters (UniRef) database. The system offers access to numerous preinstalled, curated analytic tools and also provides researchers with the option of selecting computational tools from a large list of web services including the European Molecular Biology Open Software Suite (EMBOSS), BioMoby, and the Kyoto Encyclopedia of Genes and Genomes (KEGG). The system further allows users to integrate local command line tools residing on their own computers through a client-side Java applet.

Proper citation: BioExtract (RRID:SCR_005397) Copy   

•   Source: SciCrunch Registry

http://www.biokepler.org

A Comprehensive Bioinformatics Scientific Workflow Module for Distributed Analysis of Large-Scale Biological Data that is distributed on top of the core Kepler scientific workflow system.

Proper citation: bioKepler (RRID:SCR_005385) Copy   

•   Source: SciCrunch Registry

http://cvcweb.ices.utexas.edu/cvcwp/?page_id=100

VolumeRover (a.k.a VolRover) is an interactive multi-purpose image processing software that can visualize three dimensional imaging data of any size (as big as terabyte) in a commodity PC or workstation and additionally supports the following image processing operations. Image Contrast Enhancement, Filtering/Noise Reduction, Image Segmentation, Isocontouring, Symmetry Detection (for Virus Maps, Boundary-free Image Skeletonization. VolRover provides a user interface to a number of CVC software packages including Segmentation, Contrast Enhancement, and Motif Elucidation.

Proper citation: VolumeRover (RRID:SCR_005457) Copy   

•   Source: SciCrunch Registry

http://bioimage.ucsb.edu/bisque

Open source database for exchange and exploration of biological images. Used to store, visualize, organize and analyze images in cloud. Centered around database of images and metadata.

Proper citation: Bisque database (RRID:SCR_005559) Copy   

•   Source: SciCrunch Registry

http://carringtonlab.org/resources/cashx

Software pipeline to parse, map, quantify and manage large quantities of sequence data. CASHX is a set of tools that can be used together, or as independent modules on their own. The reference genome alignment tools can be used with any reference sequence in fasta format. The pipeline was designed and tested using Arabidopsis thaliana small RNA reads generated using an Illumina 1G.

Proper citation: CASHX (RRID:SCR_005477) Copy   

•   Source: SciCrunch Registry

http://mcbc.usm.edu/gofetcher/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on June 29, 2012. We developed a web application, GOfetcher, with a very comprehensive search facility for the GO project and a variety of output formats for the results. GOfetcher has three different levels for searching the GO: Quick Search, Advanced Search, and Upload Files for searching. The application includes a unique search option which generates gene information given a nucleotide or protein accession number which can then be used in generating gene ontology information. The output data in GOfetcher can be saved into several different formats; including spreadsheet, comma-separated values, and the Extensible Markup Language (XML) format. Platform: Online tool

Proper citation: GOfetcher (RRID:SCR_005681) Copy   

•   Source: SciCrunch Registry

http://mesquiteproject.org/packages/chromaseq/

A software package in Mesquite that processes chromatograms, makes contigs, base calls, etc., using in part the programs Phred and Phrap.

Proper citation: Chromaseq (RRID:SCR_005587) Copy   

•   Source: SciCrunch Registry

http://great.stanford.edu/public/html/splash.php

Data analysis service that predicts functions of cis-regulatory regions identified by localized measurements of DNA binding events across an entire genome. Whereas previous methods took into account only binding proximal to genes, GREAT is able to properly incorporate distal binding sites and control for false positives using a binomial test over the input genomic regions. GREAT incorporates annotations from 20 ontologies and is available as a web application. The utility of GREAT extends to data generated for transcription-associated factors, open chromatin, localized epigenomic markers and similar functional data sets, and comparative genomics sets. Platform: Online tool

Proper citation: GREAT: Genomic Regions Enrichment of Annotations Tool (RRID:SCR_005807) Copy   

•   Source: SciCrunch Registry

http://umbbd.msi.umn.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on August 27, 2014. Database containing information on microbial biocatalytic reactions and biodegradation pathways for primarily xenobiotic, chemical compounds. Its goal is to provide information on microbial enzyme-catalyzed reactions that are important for biotechnology. The reactions covered are studied for basic understanding of nature, biocatalysis leading to specialty chemical manufacture, and biodegradation of environmental pollutants. Individual reactions and metabolic pathways are presented with information on the starting and intermediate chemical compounds, the organisms that transform the compounds, the enzymes, and the genes. The present database has been successfully used to teach enzymology and use of biochemical Internet information resources to advanced undergraduate and graduate students, and is being expanded primarily with the help of such students. In addition to reactions and pathways, this database also contains Biochemical Periodic Tables and a Pathway Prediction System. * Search the UM-BBD for compound, enzyme, microorganism, pathway, or BT rule name; chemical formula; chemical structure; CAS Registry Number; or EC code. * Go to Pathways and Metapathways in the UM-BBD * Lists of 203 pathways; 1400 reactions; 1296 compounds; 916 enzymes; 510 microorganism entries; 245 biotransformation rules; 50 organic functional groups; 76 reactions of naphthalene 1,2-dioxygenase; 109 reactions of toluene dioxygenase; Graphical UM-BBD Overview; and Other Graphics (Metapathway and Pathway Maps and Reaction Mechanisms).

Proper citation: UM-BBD (RRID:SCR_005787) Copy   

•   Source: SciCrunch Registry

Ratings or validation data are available for this resource

http://genome.ucsc.edu/

Portal to interactively visualize genomic data. Provides reference sequences and working draft assemblies for collection of genomes and access to ENCODE and Neanderthal projects. Includes collection of vertebrate and model organism assemblies and annotations, along with suite of tools for viewing, analyzing and downloading data.

Proper citation: UCSC Genome Browser (RRID:SCR_005780) Copy   

•   Source: SciCrunch Registry

http://pmgn.vbi.vt.edu

The Oomycete Molecular Genetics Research Collaboration Network (OMGN) is a network for research collaboration for investigators interested in oomycete molecular genetics and genomics. The goals of the OMGN is to facilitate the integration of these investigators into the community and to further strengthen the cooperative culture of this community. A particular emphasis is placed on training and integrating junior faculty and faculty from institutions under-represented in the U.S. research infrastructure. Because of their economic impact as plant pathogens, molecular, genetic and genomics studies are well advanced in many oomycete species. These organisms have served as lead species for the entire Stramenopiles lineage, a major radiation of crown eukaryotes, distinct from plants, animals and fungi. The oomycete molecular genetics community has a strong culture of collaboration and communication, and sharing of techniques and resources. With the recent blossoming of genetic and genomic tools for oomycetes, many new investigators, from a variety of backgrounds, have become interested in oomycete molecular genetics and genomics. The proposed network is open to all researchers with an interest in oomycete molecular genetics and genomics, either at an experimental or a computational level. Investigators new to the field are always welcome, especially those interested in saprophytes and animal pathogens. Goals of OMGN # Provide training to o��mycete molecular genetics researchers, especially those from smaller institutions, in the use of bioinformatics and genomics resources. # Promote the entry, participation and training of new investigators into the field of o��mycete genomics, particularly junior faculty and faculty from institutions under-represented in the U.S. research infrastructure. # Promote communication and collaboration, and minimize duplication of effort, within the worldwide o��mycete genomics community. # Support an O��mycete Genomics Resources Center to maintain and distribute training and research materials produced by community genomics projects. The network''s activities have been supported by two grants from the NSF Research Collaboration Networks in Biology program.

Proper citation: OMGN (RRID:SCR_005781) Copy   

•   Source: SciCrunch Registry

http://connectomes.utah.edu/

A web-compliant application that allows connectomics visualization by converting datasets to web-optimized tiles, delivering volume transforms to client devices, and providing groups of users with connectome annotation tools and data simultaneously via conventional internet connections. Viking is an extensible tool for connectomics analysis and is generalizable to histomics applications.

Proper citation: Viking Viewer for Connectomics (RRID:SCR_005986) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://cnas.ucr.edu/guppy/

A project that observes the processes of adaptive evolution in nature, and tests evolutionary hypotheses, by studying populations of guppies on the Caribbean island of Trinidad. Darwin thought that evolution by natural selection occurred very slowly, over hundreds if not thousands of years. Evolutionary biologists now know that evolutionary changes in species can happen very quickly, over a relatively few generations. The National Science Foundation (NSF), through its Integrative Biological Research (FIBR) program, is funding a 5-year study by 13 biologists from colleges, universities, and research institutions throughout the United States and Canada, to study the relationship of adaptive evolution and environmental circumstances. The Trinidadian guppy (Poecilia reticulata) is an excellent species for these purposes because: * It matures rapidly (one generation = 3-4 months) * It inhabits different ecological environments that can be easily manipulated On Trinidad, guppies live in streams, or portions of streams, that can differ in the species of predators that the guppies have to contend with. Some streams are high-predation environments, others low-predation. Different predation environments are often right next to one another, separated by a waterfall (which neither guppies nor predators can cross). Guppies from high-predation environments experience much higher mortality rates than do guppies in low-predation environments. High mortality is associated with the following characteristics, all of which have a genetic basis: * Earlier maturity * Greater investment of resources in reproduction * More and smaller offspring. We have found that mortality rates can be manipulated by: * Transplanting guppies from high-predation localities into sites from which they and their predators had previously been excluded by natural waterfalls, thus lowering mortality rates; * Introducing predators into low-predation sites, thus increasing mortality rates. Such experiments have shown that species evolve as predicted by theory. We have also found that evolution by natural selection can be remarkably fast, on the order of four to seven orders of magnitude faster than had been inferred from the fossil record.

Proper citation: Guppy Project (RRID:SCR_006255) Copy   

•   Source: SciCrunch Registry