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SciCrunch Registry is a curated repository of scientific resources, with a focus on biomedical resources, including tools, databases, and core facilities - visit SciCrunch to register your resource.
http://krasnow1.gmu.edu/cn3/index3.html
Multidisciplinary research team devoted to the study of basic neuroscience with a specific interest in the description and generation of dendritic morphology, and in its effect on neuronal electrophysiology. In the long term, they seek to create large-scale, anatomically plausible neural networks to model entire portions of a mammalian brain (such as a hippocampal slice, or a cortical column). Achievements by the CNG include the development of software for the quantitative analysis of dendritic morphology, the implementation of computational models to simulate neuronal structure, and the synthesis of anatomically accurate, large scale neuronal assemblies in virtual reality. Based on biologically plausible rules and biophysical determinants, they have designed stochastic models that can generate realistic virtual neurons. Quantitative morphological analysis indicates that virtual neurons are statistically compatible with the real data that the model parameters are measured from. Virtual neurons can be generated within an appropriate anatomical context if a system level description of the surrounding tissue is included in the model. In order to simulate anatomically realistic neural networks, axons must be grown as well as dendrites. They have developed a navigation strategy for virtual axons in a voxel substrate.
Proper citation: Computational Neuroanatomy Group (RRID:SCR_007150) Copy
http://organelledb.lsi.umich.edu/
Database of organelle proteins, and subcellular structures / complexes from compiled protein localization data from organisms spanning the eukaryotic kingdom. All data may be downloaded as a tab-delimited text file and new localization data (and localization images, etc) for any organism relevant to the data sets currently contained in Organelle DB is welcomed. The data sets in Organelle DB encompass 138 organisms with emphasis on the major model systems: S. cerevisiae, A. thaliana, D. melanogaster, C. elegans, M. musculus, and human proteins as well. In particular, Organelle DB is a central repository of yeast protein localization data, incorporating results from both previous and current (ongoing) large-scale studies of protein localization in Saccharomyces cerevisiae. In addition, we have manually curated several recent subcellular proteomic studies for incorporation in Organelle DB. In total, Organelle DB is a singular resource consolidating our knowledge of the protein composition of eukaryotic organelles and subcellular structures. When available, we have included terms from the Gene Ontologies: the cellular component, molecular function, and biological process fields are discussed more fully in GO. Additionally, when available, we have included fluorescent micrographs (principally of yeast cells) visualizing the described protein localization. Organelle View is a visualization tool for yeast protein localization. It is a visually engaging way for high school and undergraduate students to learn about genetics or for visually-inclined researchers to explore Organelle DB. By revealing the data through a colorful, dimensional model, we believe that different kinds of information will come to light.
Proper citation: Organelle DB (RRID:SCR_007837) Copy
http://iubio.bio.indiana.edu:8089/
Provides summary of gene and genomic information from eukaryotic organism databases. This includes gene symbol and full name, chromosome, genetic and molecular map information, Gene Ontology (Function/Location/Process) and gene homology, product information, links to extended gene information.
Proper citation: Eukaryote Genes (RRID:SCR_008617) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented August 23, 2017.
Annotated database of fluorescence microscope images depicting subcellular location proteins with two interfaces: a text and image content search interface, and a graphical interface for exploring location patterns grouped into Subcellular Location Trees. The annotations in PSLID provide a description of sample preparation and fluorescence microscope imaging.
Proper citation: Protein Subcellular Location Image Database (RRID:SCR_008663) Copy
Image analysis software that learns modular models of things such as cell shape, nuclear shape, vesicular organelle distribution and microtubule distribution directly from 2D or 3D images and can produce specific instances of cell geometries without the need to create them by hand or to segment microscope images. These geometries can be combined with biochemical models to perform spatially realistic cell simulations if used in conjunction with MCell.
Proper citation: CellOrganizer (RRID:SCR_014828) Copy
https://github.com/SantamariaLab/NeuroManager
Simulation submission manager for computational neuroscience. It manages simulation processing, file transfers, and job submission for a heterogeneous mixture of standalone server, cluster, and cloud servers.
Proper citation: NeuroManager (RRID:SCR_015559) Copy
https://www.rosettacommons.org/home
Molecular modeling software package for 3D structure prediction and high resolution design of proteins, nucleic acids, and non natural polymers. Used in computational biology, including de novo protein design, enzyme design, ligand docking, and structure prediction of biological macromolecules and macromolecular complexes.
Proper citation: Rosetta (RRID:SCR_015701) Copy
http://code.google.com/p/amap-align/
Source code that performs multiple alignment of peptidic sequences. It utilizes posterior decoding and a sequence-annealing alignment, instead of the traditional progressive alignment method.
Proper citation: AMAP (RRID:SCR_015969) Copy
http://zhanglab.ccmb.med.umich.edu/EDTSurf/
Software that constructs triangulated surfaces for macromolecules. It generates three major macromolecular surfaces: van der Waals surface, solvent-accessible surface and molecular surface (solvent-excluded surface) and also identifies cavities which are inside of macromolecules. Used in accurate calculation of protein surfaces in the protein structural and functional studies including ligand-protein docking and virtual screening.
Proper citation: Edtsurf (RRID:SCR_016083) Copy
http://bioinformatics.hungry.com/clearcut/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023.Software as a stand-alone reference implementation for the Relaxed Neighbor Joining (RNJ) algorithm. Used in distance-based phylogenetic tree reconstruction method to process large sequence datasets., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: Clearcut (RRID:SCR_016059) Copy
http://genes.mit.edu/burgelab/maxent/Xmaxentscan_scoreseq.html
Software tool as a framework for modeling the sequences of short sequence motifs based on the maximum entropy principle (MEP). Used for sequence motifs such as those involved in RNA splicing.
Proper citation: MAxEntScan (RRID:SCR_016707) Copy
https://bitbucket.org/biobakery/biobakery/wiki/Home
Analysis environment and collection of individual software tools to process raw shotgun metagenome or metatranscriptome sequencing data for quantitative microbial community profiling. Used for a metaomics data analysis., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: biobakery (RRID:SCR_016596) Copy
http://emg.nysbc.org/redmine/projects/leginon/wiki/Leginon_Homepage
System designed for automated collection of images from a transmission electron microscope.
Proper citation: Leginon (RRID:SCR_016731) Copy
https://github.com/schatzlab/genomescope
Open source software package for fast genome analysis from unassembled short reads. Used to estimate genome heterozygosity, repeat content, and size from sequencing reads using a kmer-based statistical approach.
Proper citation: GenomeScope (RRID:SCR_017014) Copy
Natural history collections. Offers a stable, straightforward and flexible framework for biodiversity data. Community-developed biodiversity data standard. It includes a glossary of terms (in other contexts these might be called properties, elements, fields, columns, attributes, or concepts) intended to facilitate the sharing of information about biological diversity by providing identifiers, labels, and definitions. Darwin Core is primarily based on taxa, their occurrence in nature as documented by observations, specimens, samples, and related information.
Proper citation: Darwin Core (RRID:SCR_016778) Copy
Web tool to search multiple public variant databases simultaneously and provide a unified interface to facilitate the search process. Used for integration of human and model organism genetic resources to facilitate functional annotation of the human genome. Used for analysis of human genes and variants by cross-disciplinary integration of records available in public databases to facilitate clinical diagnosis and basic research.
Proper citation: MARRVEL (RRID:SCR_016871) Copy
https://github.com/yarden/MISO/blob/fastmiso/docs/source/sashimi.rst
Software tool for quantitative visualization of aligned RNA-Seq reads that enables quantitative comparison of exon usage across samples or experimental conditions.
Proper citation: Sashimiplot (RRID:SCR_016861) Copy
http://pklab.med.harvard.edu/scde/pagoda.links.html
Software tool for analyzing transcriptional heterogeneity to detect statistically significant ways in which measured cells can be classified. Used to resolve multiple, potentially overlapping aspects of transcriptional heterogeneity by testing gene sets for coordinated variability among measured cells.
Proper citation: PAGODA (RRID:SCR_017099) Copy
Portal to provide integrated and federated system that interconnects diverse microbiome data sets, bioinformatics tools, and community resources. Built on guiding principles for FAIR data. Open source, community driven microbiome data marketplace and tool exchange for users to integrate their own data and tools with broader community. Partners with CyVerse and XSEDE.
Proper citation: iMicrobe (RRID:SCR_017108) Copy
https://combine-lab.github.io/salmon/
Software tool for quantifying expression of transcripts using RNA-seq data. Provides fast and bias-aware quantification of transcript expression. Transcriptome-wide quantifier to correct for fragment GC-content bias.
Proper citation: Salmon (RRID:SCR_017036) Copy
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