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http://www.cbgrits.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Time-series data sets spanning twelve time-points between E12-P9 for exploring cerebellar development of the mouse in time and space. The database contains a number of mutant / wildtype microarray datasets including two complete wildtype microarray time-series (C57BL/6 and DBA/2J). The dataset also includes in situ hybridization and bioinformatic analyses. Exploration of this dataset will allow the investigator to assess differential gene expression profiles from a developing mutant cerebella, to assess the temporal changes in gene expression in the wildtype, and to verify the cellular expression of these genes in images from our in situ hybridization library. Using the database, the investigator can explore the developmental expression or differential expression patterns of a particular gene, or create lists of similarly expression genes by building simple search algorithms. These lists can then be mined across all the datasets in both space and time. Cb GRiTS's current datasets represent gene expression analyses from multiple cerebellar mutant and wildtype single time-point and developmental series.

Proper citation: Cerebellar Gene Regulation in Time and Space Database (RRID:SCR_001699) Copy   

•   Source: SciCrunch Registry

http://tango.crg.es/

A computer algorithm to predict aggregation nucleating regions in proteins as well the effect of mutations and environmental conditions on the aggregation propensity of these regions.

Proper citation: TANGO (RRID:SCR_001770) Copy   

•   Source: SciCrunch Registry

http://bioinformatics.dreamhosters.com/?page_id=113#Genomic_Protein_Sequence_Analysis

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 10th,2023. An M software package for Clustering 16S rRNA sequences into operational taxonomic units (OTUs). The download link contain the package and some benchmark data sets.

Proper citation: MSClust (RRID:SCR_001773) Copy   

•   Source: SciCrunch Registry

http://blast.ncbi.nlm.nih.gov/Blast.cgi?PROGRAM=blastx&BLAST_PROGRAMS=blastx&PAGE_TYPE=BlastSearch&SHOW_DEFAULTS=on&LINK_LOC=blasthome

Web application to search protein databases using a translated nucleotide query. Translated BLAST services are useful when trying to find homologous proteins to a nucleotide coding region. Blastx compares translational products of the nucleotide query sequence to a protein database. Because blastx translates the query sequence in all six reading frames and provides combined significance statistics for hits to different frames, it is particularly useful when the reading frame of the query sequence is unknown or it contains errors that may lead to frame shifts or other coding errors. Thus blastx is often the first analysis performed with a newly determined nucleotide sequence and is used extensively in analyzing EST sequences. This search is more sensitive than nucleotide blast since the comparison is performed at the protein level.

Proper citation: BLASTX (RRID:SCR_001653) Copy   

•   Source: SciCrunch Registry

http://www.exploredti.com/

A graphical toolbox developed in Matlab for exploratory diffusion (tensor) MRI and fiber tractography. It includes diffusion reconstruction approaches, analysis and visualization tools for fiber tractography, atlas based segmentation, and connectivity networks. It also provides a wide range of quality assessment and pre-processing tools. Main features: * Visualization of scalar and vector maps of various diffusion tensor properties * Display of principal diffusion vectors, cuboids, and ellipsoids with several color-encodings * Deterministic (streamline) and 'probabilistic' (wild-bootstrap) fiber tractography * Clustering of fiber tracts * Data quality assessment tools * HARDI reconstructions (Q-ball and spherical deconvolution imaging) * Tract-specific measurements * Tract-segment analysis * Motion / distortion correction (with B-matrix rotation!) * Other cool stuff... (see publication link)

Proper citation: ExploreDTI (RRID:SCR_001643) Copy   

•   Source: SciCrunch Registry

https://www.cmtk.org/

A Python-based open source toolkit for magnetic resonance connectome mapping, data management, sharing, visualization and analysis. The toolkit includes the connectome mapper (a full DMRI processing pipeline), a new file format for multi modal data and metadata, and a visualization application.

Proper citation: Connectome Mapping Toolkit (RRID:SCR_001644) Copy   

•   Source: SciCrunch Registry

http://www.aphidbase.com/aphidbase/

Aphid genome database. Facilitates community annotation of pea aphid genome by International Aphid Genomics Consortium (IAGC). It aims to store recently acquired genomic resources on aphids and compare them to other insect resources as functional annotation tools. AphidBase Information System designed to organize and distribute genomic data and annotations for large international community was constructed using open source software tools from Generic Model Organism Database (GMOD).

Proper citation: APHIDBASE (RRID:SCR_001765) Copy   

•   Source: SciCrunch Registry

http://cufflinks.cbcb.umd.edu/

Software that estimates expression at transcript-level resolution and controls for variability evident across replicate libraries.

Proper citation: Cuffdiff (RRID:SCR_001647) Copy   

•   Source: SciCrunch Registry

http://www.nature.com/jcbfm/index.html

The Journal of Cerebral Blood Flow & Metabolism stands at the interface between basic and clinical neurovascular research, and features timely and relevant research highlighting experimental, theoretical, and clinical aspects of brain circulation, metabolism and imaging. The journal is relevant to any physician or scientist with an interest in brain function, cerebrovascular disease, cerebral vascular regulation and brain metabolism, including neurologists, neurochemists, physiologists, pharmacologists, anesthesiologists, neuroradiologists, neurosurgeons, neuropathologists and neuroscientists. On this website, you will find the full text of articles published online weekly, in advance of print, the current issue and an archive of previous issues. You can also find general information about the journal, and more detailed information for readers, authors, referees, librarians, advertisers, and journalists. Most articles are published online before they appear in print. New papers are uploaded weekly to the Advance online publication (AOP) page. The online publication date is specified for each paper; these versions are identical to the printed version in every respect and may be cited using the digital object identifier (DOI).

Proper citation: Journal of Cerebral Blood Flow and Metabolism (RRID:SCR_001769) Copy   

•   Source: SciCrunch Registry

https://www.metabase.com/

User-contributed list of biological databases available on the internet. Currently there are 1,801 entries, each describing a different database. The databases are described in a semi-structured way by using templates and entries can carry various user comments and annotations. Entries can be searched, listed or browsed by category. The site uses the same MediaWiki technology that powers Wikipedia, The Mediawiki system allows users to participate on many different levels, ranging from authors and editors to curators and designers. MetaBase aims to be a flexible, user-driven (user-created) resource for the biological database community. The main focuses of MetaBase are: * As a basic requirement, MB contains a list of databases, URLs and descriptions of the most commonly used biological databases currently available on the internet. * The system should be flexible, allowing users to contribute, update and maintain the data in different ways. * In the future we aim to generate more communication between the database developer and user communities.

Proper citation: MetaBase (RRID:SCR_001762) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/pennseq/

Software for isoform-specific gene expression quantification in RNA-Seq by modeling non-uniform read distribution. Instead of making parametric assumptions, they give adequate weight to the underlying data by the use of a non-parametric approach. The rationale is that regardless what factors lead to non-uniformity, whether it is due to hexamer priming bias, local sequence bias, positional bias, RNA degradation, mapping bias or other unknown reasons, the probability that a fragment is sampled from a particular region will be reflected in the aligned data. This empirical approach thus maximally reflects the true underlying non-uniform read distribution.

Proper citation: PennSeq (RRID:SCR_001763) Copy   

•   Source: SciCrunch Registry

https://physiomeproject.org/

The Physiome Project is a worldwide public domain effort to provide a computational framework for understanding human and other eukaryotic physiology. It aims to develop integrative models at all levels of biological organization, from genes to the whole organism via gene regulatory networks, protein pathways, integrative cell function, and tissue and whole organ structure/function relations. Additionally, an important goal of the project is to develop applications for teaching physiology. Current projects include the development of: - ontologies to organize biological knowledge and access to databases - markup languages to encode models of biological structure and function in a standard format for sharing between different application programs and for re-use as components of more comprehensive models - databases of structure at the cell, tissue and organ levels - software to render computational models of cell function such as ion channel electrophysiology, cell signaling and metabolic pathways, transport, motility, the cell cycle, etc. in 2 & 3D graphical form - software for displaying and interacting with the organ models which will allow the user to move across all spatial scales Sponsors: This project is supported by the International Union of Physiological Sciences (IUPS), the IEEE Engineering. in Medicine and Biology (EMBS), and the International Federation for Medical and Biological Engineering (IFMBE)

Proper citation: International Union of Physiological Sciences: Physiome Project (RRID:SCR_001760) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

https://github.com/INCF/MUSIC

Software that allows large scale neuron simulators to communicate during runtime. It allows exchange of data among parallel applications in a cluster environment, interconnects large-scale neuronal network simulators with each other or with other tools, participates in multi-simulations, and is continuously developed and extended. Three simulators currently have MUSIC interfaces: Moose, NEURON and NEST. Three applications execute in parallel while exchanging data via MUSIC. The software interface promotes interoperability by allowing models written for different simulators to be simulated together in a larger system. It enables re-usability of models or tools by providing a standard interface. As data are distributed over a number of processors, it is non-trivial to coordinate data transfer so that it reaches the correct destination at the correct time. Current and future simulators can make use of MUSIC - compliant general purpose tools and participate in multi-simulations, for example when: * Different parts of a complex nervous system model are optimally implemented in different simulators, and need to communicate with each other. * Post-processing of generated data is needed, where the amounts of data are too large for intermediate storage, and requires the simulator to pass the data directly to the post-processing module. A standard interface enables straight-forward independent third-party development and community sharing of interoperable software tools for parallel processing. * Library and utilities are written in C++, uses MPI. * It is possible to add a MUSIC interface to existing simulators. * Works independently, no assumptions are made about other applications to facilitate development of general purpose tools. * Performance Data transport with high bandwidth and low latency.

Proper citation: MUlti SImulation Coordinator (RRID:SCR_001756) Copy   

•   Source: SciCrunch Registry

http://dynamicbrain.neuroinf.jp/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 19. 2022. Platform to promote studies on dynamic principles of brain functions through unifying experimental and computational approaches in cellular, local circuit, global network and behavioral levels. Provides services such as data sets, popular research findings and articles and current developments in field. This site has been archived since FY2019 and is no longer updated.

Proper citation: Dynamic Brain Platform (RRID:SCR_001754) Copy   

•   Source: SciCrunch Registry

http://cmic.cs.ucl.ac.uk/camino/

Free, open-source, object-oriented software package for analysis and reconstruction of Diffusion MRI data, tractography and connectivity mapping. The toolkit implements standard techniques, such as diffusion tensor fitting, mapping fractional anisotropy and mean diffusivity, deterministic and probabilistic tractography. It also contains more specialized and cutting-edge techniques, such as Monte-Carlo diffusion simulation, multi-fibre and HARDI reconstruction techniques, multi-fibre PICo, compartment models, and axon density and diameter estimation. Camino has a modular design to enable construction of processing pipelines that include modules from other software packages. The toolkit is primarily designed for unix platforms and structured to enable simple scripting of processing pipelines for batch processing. Most users use linux, MacOS or a unix emulator like cygwin running under windows. However, the core code is written in Java and thus is simple to call from other platforms and programming environments, such as matlab running under unix or windows.

Proper citation: Camino (RRID:SCR_001638) Copy   

•   Source: SciCrunch Registry

http://csg.sph.umich.edu//abecasis/MACH/index.html

A Markov Chain based software tool for haplotyping, genotype imputation and disease association analysis that can resolve long haplotypes or infer missing genotypes in samples of unrelated individuals.

Proper citation: MACH 1.0 (RRID:SCR_001759) Copy   

•   Source: SciCrunch Registry

http://opensnp.org/

Database of raw data from people who have shared their direct-to-customer (DTC) genetic results from 23andMe, deCODEme or FamilyTreeDNA. Logged-In users can search the database for users with specific phenotypes and mass-download all corresponding SNP-datasets. This allows you to get datasets like All genotyping files of openSNP-users that have Alzheimer and the corresponding control group. They are currently working on providing API-access. You can also use JSON to get access to openSNP-data and some other ways: If you want to automate the file-downloads for a given phenotype the RSS-feeds could help you. Inside the RSS-XML there are 2 flags you could use to automatically create correct genotype-groups: gives you the variation of this user at the phenotype you are looking at and gives you the download link. If you were genotyped by 23andMe, deCODEme or FamilyTreeDNA (contact them regarding others) you can upload the raw genotype data which you can download from your DTC test provider. The data will then be openly available for the world to see and download. They also parse these SNPs and annotate them. For annotation they include the manually curated SNPedia and find Open Access primary publications which appear in the journals of The Public Library of Science (PLoS), an Open Access publishing group. Additionally they screen Mendeley, a crowd-sourced repository of scientific publications. You can also publish some of your phenotypes so some day it might get possible to associate some SNPs with phenotypes. You can also share your knowledge about SNPs and phenotypes with other users and can socialize.

Proper citation: openSNP (RRID:SCR_001636) Copy   

•   Source: SciCrunch Registry

http://www.kaust.edu.sa/

Private research university in Thuwal, Saudi Arabia that offers undergraduate and graduate degree programs in Biological and Environmental Science and Engineering (BESE), Computer, Electrical, and Mathematical Science and Engineering (CEMSE), and Physical Science and Engineering (PSE).

Proper citation: King Abdullah University of Science and Technology; Makkah Province; Saudi Arabia (RRID:SCR_001758) Copy   

•   Source: SciCrunch Registry