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http://dti-tk.sourceforge.net/pmwiki/pmwiki.php
A spatial normalization and atlas construction toolkit optimized for examining white matter morphometry using DTI data with special care taken to respect the tensorial nature of the data. It implements a state-of-the-art registration algorithm that drives the alignment of white matter (WM) tracts by matching the orientation of the underlying fiber bundle at each voxel. The algorithm has been shown to both improve WM tract alignment and to enhance the power of statistical inference in clinical settings. A 2011 study published in NeuroImage ranks DTI-TK the top-performing tool in its class. Key features include: * open standard-based file IO support: NIfTI format for scalar, vector and tensor image volumes * tool chains for manipulating tensor image volumes: resampling, smoothing, warping, registration & visualization * pipelines for WM morphometry: spatial normalization & atlas construction for population-based studies * built-in cluster-computing support: support for open source Sun Grid Engine (SGE) * Interoperability with other popular DTI tools: AFNI, Camino, FSL & DTIStudio * Interoperability with ITK-SNAP: support multi-modal visualization and segmentation
Proper citation: Diffusion Tensor Imaging ToolKit (RRID:SCR_001642) Copy
Project to define a roadmap for diffusion MR imaging of traumatic brain imaging and design an infrastructure to implement the recommendations and tested to ensure feasibility, disseminate results, and facilitate deployment and adoption. The research roadmap and infrastructure development will concentrate on three areas: 1) standardization of diffusion imaging methodology, 2) trial design and patient selection for acute or chronic therapy, and 3) development of multi-center collaborations and repositories for evaluating whether advanced diffusion imaging does improve decision making and TBI patients' outcomes. # DTI MRI reproducability: One of the major areas of investigation in this project is to study the reproducibility of data acquisition and image analysis algorithms. Understanding reproducibility defines a base level of deviation from which scans can be analyzed with statistical significance. As part of this work they are also developing site qualification criteria with the intention of setting limits on the MR system minimal performance for acceptable use in TBI evaluation. # Infrastructure for image storage, analysis and visualization: There is a continuing need to refine and extend software methods for diffusion MRI data analysis and visualization. Not only to translate tools into clinical practice, but also to encourage continuation of the innovation and development of new tools and techniques. To deliver upon these goals they are designing and implementing a storage and computational infrastructure to provide access to shared datasets and intuitive interfaces for analysis and visualization through a variety of tools. A strong emphasis has been placed on providing secure data sharing and the ability to add community defined common data elements. The infrastructure is built upon a Software-as-a-Service model, in which tools are hosted and managed remotely allowing users access through well-defined interfaces. The final service will also facilitate composition or orchestration of workflows composed of different analysis and processing tasks (for example using LONI or XNAT pipelines) with the ultimate goal of providing automated no-click evaluations of diffusion MRI data. # Tool development: The final aspect of this project aims to facilitate and encourage tool development and contribution. By providing access to open datasets, they will create a platform on which tool developers can compare and improve and their tools. When tools are sufficiently mature they can be exposed in the infrastructure mentioned above and used by researchers and other developers.
Proper citation: Diffusion MRI of Traumatic Brain Injury (RRID:SCR_001637) Copy
http://neuroimage.usc.edu/brainstorm/
Software as collaborative, open source application dedicated to analysis of brain recordings: MEG, EEG, fNIRS, ECoG, depth electrodes and animal invasive neurophysiology. User-Friendly Application for MEG/EEG Analysis.
Proper citation: Brainstorm (RRID:SCR_001761) Copy
Public archive providing a comprehensive record of the world''''s nucleotide sequencing information, covering raw sequencing data, sequence assembly information and functional annotation. All submitted data, once public, will be exchanged with the NCBI and DDBJ as part of the INSDC data exchange agreement. The European Nucleotide Archive (ENA) captures and presents information relating to experimental workflows that are based around nucleotide sequencing. A typical workflow includes the isolation and preparation of material for sequencing, a run of a sequencing machine in which sequencing data are produced and a subsequent bioinformatic analysis pipeline. ENA records this information in a data model that covers input information (sample, experimental setup, machine configuration), output machine data (sequence traces, reads and quality scores) and interpreted information (assembly, mapping, functional annotation). Data arrive at ENA from a variety of sources including submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centers and routine and comprehensive exchange with their partners in the International Nucleotide Sequence Database Collaboration (INSDC). Provision of nucleotide sequence data to ENA or its INSDC partners has become a central and mandatory step in the dissemination of research findings to the scientific community. ENA works with publishers of scientific literature and funding bodies to ensure compliance with these principles and to provide optimal submission systems and data access tools that work seamlessly with the published literature. ENA is made up of a number of distinct databases that includes the EMBL Nucleotide Sequence Database (Embl-Bank), the newly established Sequence Read Archive (SRA) and the Trace Archive. The main tool for downloading ENA data is the ENA Browser, which is available through REST URLs for easy programmatic use. All ENA data are available through the ENA Browser. Note: EMBL Nucleotide Sequence Database (EMBL-Bank) is entirely included within this resource.
Proper citation: European Nucleotide Archive (ENA) (RRID:SCR_006515) Copy
Brain Innovation B.V. is developing scientific software in the field of human and animal brain imaging, neural network simulation and computer-based experimental control. Our current major product, BrainVoyager QX, is a commercially available cross-platform neuroimaging tool, which is used in hundreds of labs across the planet. Turbo-BrainVoyager is an easy to use program for real-time data analysis, which allows to observe a subject''s or patient''s brain activity during an ongoing functional MRI scanning session. TMS Neuronavigator provides the hard- and software to navigate a TMS coil to desired anatomical or functionally defined brain regions. We also provide free software products. BrainVoyager Brain Tutor allows to learn about brain areas by clicking on rotatable 3D brain models. StimulDX is a powerful stimulation software based on Microsofts DirectX API, which we will make available for free download in the near future.
Proper citation: Brain Innovation: Home of the BrainVoyager Product Family (RRID:SCR_006660) Copy
Microarray data management and analysis system for NCI / Center for Cancer Research scientists / collaborators. Data is secured and backed up on a regular basis, and investigators can authorize levels of access privileges to their projects, allowing data privacy while still enabling data sharing with collaborators.
Proper citation: mAdb (RRID:SCR_006677) Copy
Service providing functional analysis of proteins by classifying them into families and predicting domains and important sites. They combine protein signatures from a number of member databases into a single searchable resource, capitalizing on their individual strengths to produce a powerful integrated database and diagnostic tool. This integrated database of predictive protein signatures is used for the classification and automatic annotation of proteins and genomes. InterPro classifies sequences at superfamily, family and subfamily levels, predicting the occurrence of functional domains, repeats and important sites. InterPro adds in-depth annotation, including GO terms, to the protein signatures. You can access the data programmatically, via Web Services. The member databases use a number of approaches: # ProDom: provider of sequence-clusters built from UniProtKB using PSI-BLAST. # PROSITE patterns: provider of simple regular expressions. # PROSITE and HAMAP profiles: provide sequence matrices. # PRINTS provider of fingerprints, which are groups of aligned, un-weighted Position Specific Sequence Matrices (PSSMs). # PANTHER, PIRSF, Pfam, SMART, TIGRFAMs, Gene3D and SUPERFAMILY: are providers of hidden Markov models (HMMs). Your contributions are welcome. You are encouraged to use the ''''Add your annotation'''' button on InterPro entry pages to suggest updated or improved annotation for individual InterPro entries.
Proper citation: InterPro (RRID:SCR_006695) Copy
http://www.mitk.org/DiffusionImaging
A selection of image analysis algorithms for the processing of diffusion-weighted MR images. Features & Highlights * Tensor and q-ball reconstruction * Glyph visualization * Quantification and partial volume clustering of tensor and q-ball images * Global fiber tractography, visualization, and tract post-processing * Brain network statistics and visualization (connectomics) * Interactive exploration of Tract-based spatial statistics (TBSS) results * Intra-voxel incoherent motion (IVIM) estimation * Synthetic data generation Additional system specific requirements: * Windows: If you have problems running the Windows application, please install the Microsoft Redistributable Packages for VS 2008: 32 bit or 64 bit * Linux: the Qt framework, version 4.6.2 or later Tested systems: Windows 7, Windows Vista; Ubuntu 12.04 and newer; OS X 10.6 (Snow Leopard), OS X 10.8 (Mountain Lion) The OS X 10.6 installer is compatible with OS X 10.7 (Lion) so there is no dedicated disk image build under 10.7. The MITK Diffusion application is based on the MITK research platform and the most of it is open-source. The available code is embedded into the source code of MITK as a module and can be accessed through the public git repository.
Proper citation: MITK Diffusion (RRID:SCR_006846) Copy
http://bio.math.berkeley.edu/eXpress/index.html
THIS RESOURCE IS NO LONGER IN SERVICE. Documented January 29, 2018.
From website: "Note that the eXpress software is also no longer being developed. We recommend you use kallisto instead." Kallisto can be found at http://pachterlab.github.io/kallisto/.
Software for streaming quantification for high-throughput DNA/RNA sequencing.
Can be used in any application where abundances of target sequences need to be estimated from short reads sequenced from them.
Proper citation: eXpress (RRID:SCR_006873) Copy
http://biit.cs.ut.ee/gprofiler/
Web server for functional enrichment analysis and conversions of gene lists. Web based tool for functional profiling of gene lists from large scale experiments. Has web interface with powerful visualization. Used for analyzing data from any organism.
Proper citation: g:Profiler (RRID:SCR_006809) Copy
Encyclopedia of DNA elements consisting of list of functional elements in human genome, including elements that act at protein and RNA levels, and regulatory elements that control cells and circumstances in which gene is active. Enables scientific and medical communities to interpret role of human genome in biology and disease. Provides identification of common cell types to facilitate integrative analysis and new experimental technologies based on high-throughput sequencing. Genome Browser containing ENCODE and Epigenomics Roadmap data. Data are available for entire human genome.
Proper citation: ENCODE (RRID:SCR_006793) Copy
http://intramural.nimh.nih.gov/sscc/index.html
Scientific and Statistical Computing Core of the NIMH Intramural Research Program supporting functional neuroimaging research at the NIH. This includes development of new data analysis techniques, their implementation in the AFNI software, advising researchers on the analysis methods, and instructing them in the use of software tools. Support methods: A. Provision of software for analysis for FMRI data (AFNI package: http://afni.nimh.nih.gov) * AFNI has been developed for the last 10 years by Dr Cox, et al. (6 years in Milwaukee, 4 years at NIMH) * Formal and informal instruction in the use of AFNI, including outlines of the statistical methods used in the programs * Installation of AFNI on NIH computers (Mac OS X, Unix, Linux) approximately 120 NIH systems have used AFNI in the last month (80 NIMH, 20 NINDS, 20 other) * Realtime monitoring of FMRI data at scanners * Continuing development of new modules for AFNI to meet needs of NIH researchers B. Consulting with NIH researchers about FMRI data analysis issues, concerns, and methods
Proper citation: NIMH DIRP Scientific and Statistical Computing Core (RRID:SCR_006958) Copy
http://www.icpsr.umich.edu/SAMHDA/
Database of the nation''s substance abuse and mental health research data providing public use data files, file documentation, and access to restricted-use data files to support a better understanding of this critical area of public health. The goal is to increase the use of the data to most accurately understand and assess substance abuse and mental health problems and the impact of related treatment systems. The data include the U.S. general and special populations, annual series, and designs that produce nationally representative estimates. Some of the data acquired and archived have never before been publicly distributed. Each collection includes survey instruments (when provided), a bibliography of related literature, and related Web site links. All data may be downloaded free of charge in SPSS, SAS, STATA, and ASCII formats and most studies are available for use with the online data analysis system. This system allows users to conduct analyses ranging from cross-tabulation to regression without downloading data or relying on other software. Another feature, Quick Tables, provides the ability to select variables from drop down menus to produce cross-tabulations and graphs that may be customized and cut and pasted into documents. Documentation files, such as codebooks and questionnaires, can be downloaded and viewed online.
Proper citation: Substance Abuse and Mental Health Data Archive (RRID:SCR_007002) Copy
This project encompasses development of novel biological network analysis methods and infrastructure for querying biological data in a semantically-enabled format, and aims to create a semantic interactome model. Research within the BioMANTA project will focus on computational modelling and analysis, primarily using Semantic Web technologies and Machine Learning methods, of large-scale protein-protein interaction and compound activity networks across a wide variety of species. A range of information such as kinetic activity, tissue expression, and subcellular localization and disease state attributes will be included in the resulting data model. Protein interactions are a fundamental component of biological processes. Many proteins are functional only in multimeric complexes, or require interaction partners to achieve their correct localisation or function. For this reason, the study of protein-protein interaction (PPI) networks has become an area of growing interest in computational biology. Through the use of Semantic Web technologies such as Resource Description Framework (RDF) and Web Ontology Language (OWL), interaction data is modelled to create a knowledge representation in which meaning is vested in the ontology rather than instances of data. Stochastic and computational intelligence methods are applied to this data to infer high coverage networks. Semantic inferencing is used to infer previously unknown and meaningful pathways. Major project components: - The BioMANTA Ontology:- An OWL DL ontology incorporating the PSI-MI Ontology, the NCBI Taxonomy, and elements of BioPax ontology and Gene Ontology (describing subcellular localisation). This allows us to re-use existing ontologies, thereby reducing overheads associated with knowledge acquisition in the ontology development process. We are able to integrate existing public data that contain annotation in these formats. - Data conversion & semantic protein integration:- A set of software components that convert protein-protein databases (DIP, MPact, IntAct, etc.) from PSI-MI XML to RDF compliant with the BioMANTA ontology. These software allow us to make these protein-protein interaction datasets (and more generally, any PSI-MI XML data) semantically available for querying and inference within BioMANTA. - A RDF triple store based on RDF Molecules and the MapReduce architecture:- A proof-of-concept RDF triple store using RDF molecules and Hadoop scale-out architectures. Regular RDF graphs are deconstructed into RDF molecules, which are distributed over distributed compute nodes in the MapReduce architecture, and are subsequently combined to form equivalent RDF graphs. Such an approach makes the distributed SPARQL querying and reasoning on RDF triple stores possible. - A quantitative framework to integrate networks extracted from independent data sources (gene expression, subcellular localization, and ortholog mapping):- The model is multi-layer, with a first layer based on Decision Trees where each Decision tree is built on each dataset independently. The tree nodes are cut using Shannon''s entropy (mutual information); the decision of these independent trees is integrated using logistic regression, and the parameters are optimised using maximum likelihood. Sponsors: This resource is supported by the Pfizer Global Research and Development, the Institute for Molecular Bioscience (IMB), and the University of Queensland, Australia.
Proper citation: BioMANTA (RRID:SCR_007177) Copy
Portal for Macromolecular X-Ray Crystallography to produce and support an integrated suite of programs that allows researchers to determine macromolecular structures by X-ray crystallography, and other biophysical techniques. Used in the education and training of scientists in experimental structural biology for determination and analysis of protein structure.
Proper citation: CCP4 (RRID:SCR_007255) Copy
http://www.mbio.ncsu.edu/BioEdit/bioedit.html
Software tool as biological sequence alignment editor written for Windows 95/98/NT/2000/XP/7 and sequence analysis program. Provides sequence manipulation and analysis options and links to external analysis programs to view and manipulate sequences with simple point and click operations., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: BioEdit (RRID:SCR_007361) Copy
Software Python package for simulation and analysis of neuronal networks using the NEURON simulator.Used to facilitate development, parallel simulation, analysis, and optimization of biological neuronal networks.
Proper citation: NetPyNE (RRID:SCR_014758) Copy
http://www.kitware.com/opensource/volview.html
A software for volume visualization that can be used by researchers to explore and analyze medical and scientific data. This software uses a variety of tools to load and visualize the data on either a 2D or 3D display. Theses tools include volume rendering, maximum intensity projections and oblique reformatting. Visualizations can be saved mid-session and be reopened at a later time.
Proper citation: VolView (RRID:SCR_014569) Copy
Ratings or validation data are available for this resource
http://www.bioinformatics.babraham.ac.uk/projects/fastqc/
Quality control software that perform checks on raw sequence data coming from high throughput sequencing pipelines. This software also provides a modular set of analyses which can give a quick impression of the quality of the data prior to further analysis.
Proper citation: FastQC (RRID:SCR_014583) Copy
http://bowtie-bio.sourceforge.net/bowtie2/index.shtml
Ultrafast and memory efficient tool for aligning sequencing reads to long reference sequences. Supports gapped, local, and paired end alignment modes. More suited to finding longer, gapped alignments in comparison with original Bowtie method.
Proper citation: Bowtie 2 (RRID:SCR_016368) Copy
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