Curator Dashboard

• Organization
• SciCrunch
• 14 years ago - submitted by Andrea Stagg

A reference atlas of standard macaque monkey magnetic resonance images. The template brain volume that offers a common stereotaxic reference frame to localize anatomical and functional information in an organized and reliable way for comparison across individual macaque monkeys and studies. We have used MRI volumes from a group of 25 normal adult macaque monkeys (18 Macaca fascicularis, 7 Macaca mulatta) to create the individual atlas. Thus, the atlas does not rely on the anatomy of a single subject, but instead depends on nonlinear normalization of numerous macaque brains mapped to an average template image that is faithful to the location of anatomical structures. Tools for registering a native MRI to the MNI macaque atlas can be found in the Software section. Viewing the atlas and associated volumes online requires Java browser support. Additionally, you may download the atlas and associated files in your chosen format.

• Resource
• SciCrunch
• 15 years ago - by Anonymous

Software for detecting INDELs (small insertions and deletion with size less than 50bp) as well as large deletions that are within the coding regions from the exome sequencing data. It also can be applied to the whole genome sequencing data.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Software package as computational framework with simulation-based error models for inferring genomic structural variants from massive paired-end sequencing data. Package is composed of three modules, PEMer workflow, SV-Simulation and BreakDB. PEMer workflow is a sensitive software for detecting SVs from paired-end sequence reads. SV-Simulation randomly introduces SVs into a given genome and generates simulated paired-end reads from novel genome.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Accelerated alignment tool for mapping data from next-generation DNA sequencing systems. It runs on TimeLogic''s newest FPGA-based DeCypher J-Series Similarity Search Engine Accelerator to provide fast and reliable results that significantly outperform software-only or GPU-accelerated alternatives.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Software mining pipeline guided by a Bayesian principle to detect single nucleotide polymorphisms, insertion and deletions by comparing high-throughput pyrosequencing reads with a reference genome of related organisms. This pipeline is extended to identify and visualize large-size structural variations, including insertions, deletions, inversions and translocations.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Software that detects structural variation (SV) breakpoints by clustering discordant paired-end alignments whose signatures corroborate the same putative breakpoint. Hydra can detect breakpoints caused by all classes of structural variation. Moreover, it was designed to detect variation in both unique and duplicated genomic regions; therefore, it will examine paired-end reads having multiple discordant alignments. Hydra does not attempt to classify SV breakpoints based on the mapping distances and orientations of each breakpoint cluster, it merely detects and reports breakpoints. This is an intentional decision, as it was observed that in loci affected by complex rearrangements, the type of variant suggested by the breakpoint signature is not always correct. Hydra does report the orientations, distances, number of supporting read-pairs, etc., for each breakpoint. It is suggested that downstream methods be used to classify variants based on the genomic features that they overlap and the co-occurrence of other breakpoints. For example, they developed BEDTools for exactly this purpose and the breakpoints reported by Hydra are in the BEDPE format used by BEDTools. Future releases of Hydra will include scripts that assist in the classification process.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Software tool combining both paired read and read depth signals into probabilistic model which can analyze multiple alignments of reads. Used to find structural variation in both normal and cancer genomes using data from variety of next-generation sequencing platforms. Used to predict structural variants directly from aligned reads in SAM/BAM format.Combines read depth information along with discordant paired read mappings into single probabilistic model two common signals of structural variation. When multiple alignments of read are given, GASVPro utilizes Markov Chain Monte Carlo procedure to sample over the space of possible alignments.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

A software tool for calling short indels in next generation sequencing data.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

An algorithm for detecting genomic structural variations at base-pair resolution using next-generation sequencing data. CREST uses pieces of DNA called soft clips to find structural variations. Soft clips are the DNA segments produced during sequencing that fail to properly align to the reference genome as the sample genome is reassembled. CREST uses the soft clips to precisely identify sites of chromosomal rearrangement or where pieces of DNA are inserted or deleted.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

A software program designed to identify long deletions of a genome as well as the RNA splicings using long Illumina reads. Currently, Clippers is implemented for long reads Illumina, ex: 75bp or 100bp, allowing mismatches and a single deletion/splicing. Clippers is a sister tool of PerM, our short reads aligner. Users are strongly suggested to use PerM to initially mapped reads and identify the deletion/splicing with the initially unmapped reads. We plan to extend it to ABI SOLiD reads in the near future. Clippers outputs gap-alignments in SAM format. You can use SAMtools or other program to interpret the deletion/splicing. The input files are a reference in fasta format and the reads is in fasta or fastq format.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

A collection of tools to discover and genotype structural variations in genomes from paired-end sequencing reads. The main software is written in C++ with some auxiliary scripts in Python.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

A fast tool for locating sequence breakpoints from the alignment of single end reads (SE) produced by next generation sequencing (NGS). It adopts a heuristic method in searching for local mapping signatures created by insertion/deletions (indels) or more complex structural variants(SVs). With current NGS single-end sequencing data, the output regions by Breakpoint mainly contain the approximate breakpoints of indels and a limited number of large SVs. Notably, Breakpointer can uncover breakpoints of insertions which are longer than the read length. Breakpointer also can find breakpoints of many variants located in repetitive regions. The regions can be used not only as a extra support for SV predictions by other tools (such as by split-read method), but also can serve as a database for searching variants which might be missed by other tools. Breakpointer is a command line tool that runs under linux system. Breakpointer takes advanage of two local mapping features of single-end reads as a consequence of indel/SVs: 1) non-uniform read distribution (depth skewness) and 2) misalignments at the boundaries of indel/SVs. These features are summarized as breakpoint signature. Breakpointer proceeds in three stages in capturing this signature. It is implemented in C++ and perl. Input is the file or files containing alignments of single-end reads against a reference genome (in .BAM format). Output is the predicted regions containing potential breakpoints of SVs (in .GFF format). To be able to read in .BAM files, Breakpointer requires bamtools API, which users should install beforehand.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

A tool that implements an algorithm for optimal alignment of sequences with Structural Variations (SVs).

• Resource
• SciCrunch
• 13 years ago - by Anonymous

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.

• Resource
• SciCrunch
• 15 years ago - by Anonymous

The goal of our research is to uncover the neural circuitry that mediates some of the remarkable processing capabilities of the retina. The retina to operates at high spatial and temporal resolution over more than 7 orders of magnitude, to detect the direction of motion, to blank and then recover after saccades, to generate at least a dozen different abstract representations of the visual world. How is all of this, and much more, possible in this tissuepaper-thin array of neurons? Videos and images describing this include: * The retinal hypercircuit. * How the Retina Works * Take a Tour through the Retina * Cartoon of the retina showing layering of neurons * Directional Selectivity * Feedback and Crossover inhibition * Multiple Representations of the Visual Scene ** Pseudo Array Recording Methods ** Multiple Representations of the Visual World ** Regions of Frequency Space * Regions of space/time frequency * Space-time rasters for ON and OFF cells * Patching a neuron in a retinal slice * Targeting Retinal Neuron Subregions with Arficial Rhodopsins

• Resource
• SciCrunch
• 15 years ago - by Anonymous

A targeting model that defines where mutations occur (by specifying the relative rates at which DNA motifs in the Ig sequence are mutated), and a nucleotide substitution model that defines the resulting mutation (by specifying the probability of each base mutating to each of the other three possibilities as a function of the surrounding bases).

• Resource
• SciCrunch
• 13 years ago - by Anonymous

An interactive software program that integrates phenotypic data exploration, selection, management and quality control using a unified platform for association studies of rare and common variants.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on December 5th, 2022. An open-source platform designed for organic sharing and collaborative work, it provides the CTSA Consortium with a convenient web platform for networking, exchanging resources, and collaborating. Created and maintained as a tool for the CTSA Consortium, it can be implemented by organizations, either in a standalone installation or via cloud-based hosting provided by Zaloni, Inc. The installation package is available at http://www.getsharecenter.org/, including a package optimized for research networks. ShareCenter integrates with VIVO and is a demonstration site for the new CTSAconnect project that will coalesce the VIVO and eagle-i ontologies. CTSA personnel can use ShareCenter to connect and share with each other, while CTSAs can (a) set up the open-source package, which includes a version optimized for research networks or (b) easily create their own private ''''channel'''' on CTSA ShareCenter. * Search for resources and people. * Contribute your institute''''s gems. * Look cool for being a top contributor! ShareCenter Features * Easy search and access: Find content easily using faceted search. * Team based workspaces: Easily create and manage private collaboration spaces. * Connect with other users and follow their activities: Connect with other CTSA members. Follow their activities. * Subscriptions and Notifications: Subscribe to interesting content and receive notifications when your requests are filled. * Sophisticated categorization of information: Content can be categorized by key function areas, taxonomy and keywords. * Incentives for sharing: Reward users for sharing resources, ideas, expertise, skills.

• Resource
• SciCrunch
• 15 years ago - by Anonymous

• Resource
• SciCrunch
• 15 years ago - submitted by Andrea Stagg