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https://github.com/danbider/lightning-pose

Software video centric package for direct video manipulation. Semi supervised animal pose estimation algorithm, Bayesian post processing approach and deep learning package. Improved animal pose estimation via semi-supervised learning, Bayesian ensembling, and cloud-native open-source tools.

Proper citation: Lightning Pose (RRID:SCR_024480) Copy   

•   Source: SciCrunch Registry

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3001096/

Software pipeline to identify MITEs as well as other small Class 2 non autonomous Transposable Elements from genomic DNA data sets. Used for discovering miniature inverted repeat transposable elements from genomic sequences. Can search large genomic data sets including whole genome sequences.

Proper citation: MITE-Hunter (RRID:SCR_020946) Copy   

•   Source: SciCrunch Registry

http://yogo.msu.montana.edu/

A set of software tools created to rapidly build scientific data-management applications. These applications will enhance the process of data annotation, analysis, and web publication. The system provides a set of easy-to-use software tools for data sharing by the scientific community. It enables researchers to build their own custom-designed data management systems. The problem of scientific data management rests on several challenges. These include flexible data storage, a way to share the stored data, tools to curate the data, and history of the data to show provenance. The Yogo Framework gives you the ability to build scientific data management applications that address all of these challenges. The Yogo software is being developed as part of the NeuroSys project. All tools created as part of the Yogo Data Management Framework are open source and released under an OSI approved license.

Proper citation: Yogo Data Management System (RRID:SCR_004239) Copy   

•   Source: SciCrunch Registry

http://openconnectomeproject.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. Connectomes repository to facilitate the analysis of connectome data by providing a unified front for connectomics research. With a focus on Electron Microscopy (EM) data and various forms of Magnetic Resonance (MR) data, the project aims to make state-of-the-art neuroscience open to anybody with computer access, regardless of knowledge, training, background, etc. Open science means open to view, play, analyze, contribute, anything. Access to high resolution neuroanatomical images that can be used to explore connectomes and programmatic access to this data for human and machine annotation are provided, with a long-term goal of reconstructing the neural circuits comprising an entire brain. This project aims to bring the most state-of-the-art scientific data in the world to the hands of anybody with internet access, so collectively, we can begin to unravel connectomes. Services: * Data Hosting - Their Bruster (brain-cluster) is large enough to store nearly any modern connectome data set. Contact them to make your data available to others for any purpose, including gaining access to state-of-the-art analysis and machine vision pipelines. * Web Viewing - Collaborative Annotation Toolkit for Massive Amounts of Image Data (CATMAID) is designed to navigate, share and collaboratively annotate massive image data sets of biological specimens. The interface is inspired by Google Maps, enhanced to allow the exploration of 3D image data. View the fork of the code or go directly to view the data. * Volume Cutout Service - RESTful API that enables you to select any arbitrary volume of the 3d database (3ddb), and receive a link to download an HDF5 file (for matlab, C, C++, or C#) or a NumPy pickle (for python). Use some other programming language? Just let them know. * Annotation Database - Spatially co-registered volumetric annotations are compactly stored for efficient queries such as: find all synapses, or which neurons synapse onto this one. Create your own annotations or browse others. *Sample Downloads - In addition to being able to select arbitrary downloads from the datasets, they have also collected a few choice volumes of interest. * Volume Viewer - A web and GPU enabled stand-alone app for viewing volumes at arbitrary cutting planes and zoom levels. The code and program can be downloaded. * Machine Vision Pipeline - They are building a machine vision pipeline that pulls volumes from the 3ddb and outputs neural circuits. - a work in progress. As soon as we have a stable version, it will be released. * Mr. Cap - The Magnetic Resonance Connectome Automated Pipeline (Mr. Cap) is built on JIST/MIPAV for high-throughput estimation of connectomes from diffusion and structural imaging data. * Graph Invariant Computation - Upload your graphs or streamlines, and download some invariants. * iPad App - WholeSlide is an iPad app that accesses utilizes our open data and API to serve images on the go.

Proper citation: Open Connectome Project (RRID:SCR_004232) Copy   

•   Source: SciCrunch Registry

http://www.cs.gsu.edu/~serghei/?q=drut

Software for Discovery and Reconstruction of Unannotated Transcripts in Partially Annotated Genomes from High-Throughput RNA-Seq Data.

Proper citation: DRUT (RRID:SCR_004351) Copy   

•   Source: SciCrunch Registry

http://plantgrn.noble.org/LegumeIP/

LegumeIP is an integrative database and bioinformatics platform for comparative genomics and transcriptomics to facilitate the study of gene function and genome evolution in legumes, and ultimately to generate molecular based breeding tools to improve quality of crop legumes. LegumeIP currently hosts large-scale genomics and transcriptomics data, including: * Genomic sequences of three model legumes, i.e. Medicago truncatula, Glycine max (soybean) and Lotus japonicus, including two reference plant species, Arabidopsis thaliana and Poplar trichocarpa, with the annotation based on UniProt TrEMBL, InterProScan, Gene Ontology and KEGG databases. LegumeIP covers a total 222,217 protein-coding gene sequences. * Large-scale gene expression data compiled from 104 array hybridizations from L. japonicas, 156 array hybridizations from M. truncatula gene atlas database, and 14 RNA-Seq-based gene expression profiles from G. max on different tissues including four common tissues: Nodule, Flower, Root and Leaf. * Systematic synteny analysis among M. truncatula, G. max, L. japonicus and A. thaliana. * Reconstruction of gene family and gene family-wide phylogenetic analysis across the five hosted species. LegumeIP features comprehensive search and visualization tools to enable the flexible query on gene annotation, gene family, synteny, relative abundance of gene expression.

Proper citation: LegumeIP (RRID:SCR_008906) Copy   

•   Source: SciCrunch Registry

http://www.readout.info

Matlab toolbox that makes it easy to apply decoding analyses to neural data. The design of the toolbox revolves around four abstract object classes which enables users to interchange particular modules in order to try different analyses while keeping the rest of the processing stream intact. The toolbox is capable of analyzing data from many different types of recording modalities, and examples are given on how it can be used to decode basic visual information from neural spiking activity and how it can be used to examine how invariant the activity of a neural population is to stimulus transformations.

Proper citation: Neural Decoding Toolbox (RRID:SCR_009012) Copy   

•   Source: SciCrunch Registry

http://uberon.org

An integrated cross-species anatomy ontology representing a variety of entities classified according to traditional anatomical criteria such as structure, function and developmental lineage. The ontology includes comprehensive relationships to taxon-specific anatomical ontologies, allowing integration of functional, phenotype and expression data. Uberon consists of over 10000 classes (March 2014) representing structures that are shared across a variety of metazoans. The majority of these classes are chordate specific, and there is large bias towards model organisms and human.

Proper citation: UBERON (RRID:SCR_010668) Copy   

•   Source: SciCrunch Registry

http://brainandsociety.org/the-brain-observatory

Formerly a topical portal studying the brain which collected and imaged 1000 human brains, the Brain Observatory has partnered with the Institute for Brain and Society to build virtual laboratories that will feed directly into the database of images and knowledge created in the context of the Human Brain Library. The Brain Observatory will also host exhibits, conferences, and events aimed at promoting a heightened awareness of brain research and how its results can benefit personal brain fitness and mental health.

Proper citation: Brain Observatory (RRID:SCR_010641) Copy   

•   Source: SciCrunch Registry

http://databrary.org/

Project aims to promote data sharing, archiving, and reuse among researchers who study human development. Focuses on creating tools for scientists to store, manage, preserve, analyze and share video and related data.

Proper citation: Databrary (RRID:SCR_010471) Copy   

•   Source: SciCrunch Registry

http://www.complex.iastate.edu/download/Picky/

A software tool for selecting optimal oligonucleotides (oligos) that allows the rapid and efficient determination of gene-specific oligos based on given gene sets, and can be used for large, complex genomes such as human, mouse, or maize.

Proper citation: Picky (RRID:SCR_010963) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/hdbig/

A collection of software tools for high dimensional brain imaging genomics. These tools are designed to perform comprehensive joint analysis of heterogeneous imaging genomics data. HDBIG-SR is an HDBIG toolkit for sparse regression while HDBIG-SCCA is an HDBIG toolkit for sparse association.

Proper citation: HDBIG (RRID:SCR_014120) Copy   

•   Source: SciCrunch Registry

http://www.nitrc.org/projects/cta_toolbox

A Matlab tool to perform statistical analysis on cortical thickness signals on brain surfaces obtained from Freesurfer. It is used for multi-resolutional analysis of such cortical thickness signals and detecting group differences. It is based on the Spectral Graph Wavelet Transform (SGWT) toolbox and provides plug and play methods for deriving Wavelet Multiscale Descriptor (WMD), cortical thickness smoothing using SGWT, Multivariate General Linear Model (MGLM), and False Discovery Rate (FDR).

Proper citation: Wisconsin Cortical Thickness Analysis (CTA) Toolbox (RRID:SCR_014180) Copy   

•   Source: SciCrunch Registry

http://grassius.org/

A public resource composed of a collection of databases, computational and experimental resources that relate to the control of gene expression in the grasses, and their relationship with agronomic traits. As knowledge on the interactions of transcription factors (TFs) and cis-regulatory elements in the promoters of the genes that they regulate continues to accumulate, the information is acquired by GRASSIUS, either through contributions by the community, or by literature analysis. The overarching objective of GRASSIUS is to provide a one-stop resource that will facilitate research and communication within the plant community with regards to genome-wide regulation of gene expression processes.

Proper citation: GRASSIUS (RRID:SCR_012999) Copy   

•   Source: SciCrunch Registry

http://krasnow1.gmu.edu/CENlab/software.html

Stochastic reaction-diffusion simulator in Java which is used for simulating neuronal signaling pathways.

Proper citation: NeuroRD (RRID:SCR_014769) Copy   

•   Source: SciCrunch Registry

http://www.rcsb.org/#Category-welcome

Collection of structural data of biological macromolecules. Database of information about 3D structures of large biological molecules, including proteins and nucleic acids. Users can perform queries on data and analyze and visualize results.

Proper citation: Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) (RRID:SCR_012820) Copy   

•   Source: SciCrunch Registry

http://www.digimorph.org/

A dynamic archive of information on digital morphology and high-resolution X-ray computed tomography of biological specimens serving imagery for more than 750 specimens contributed by almost 150 collaborating researchers from the world''s premiere natural history museums and universities. Browse through the site and see spectacular imagery and animations and details on the morphology of many representatives of the Earth''s biota. Digital Morphology, part of the National Science Foundation Digital Libraries Initiative, develops and serves unique 2D and 3D visualizations of the internal and external structure of living and extinct vertebrates, and a growing number of ''invertebrates.'' The Digital Morphology library contains nearly a terabyte of imagery of natural history specimens that are important to education and central to ongoing cutting-edge research efforts. Digital Morphology visualizations are now in use in classrooms and research labs around the world and can be seen in a growing number of museum exhibition halls. The Digital Morphology site currently presents: * QuickTime animations of complete stacks of serial CT sections * Animated 3D volumetric movies of complete specimens * Stereolithography (STL) files of 3D objects that can be viewed interactively and rapidly prototyped into scalable physical 3D objects that can be handled and studied as if they were the original specimens * Informative introductions to the scanned organisms, often written by world authorities * Pertinent bibliographic information on each specimen * Useful links * A course resource for our ''Digital Methods for Paleontology'' course, in which students learn how to generate all of the types of imagery displayed on the Digital Morphology site

Proper citation: DigiMorph (RRID:SCR_004416) Copy   

•   Source: SciCrunch Registry

http://research.calacademy.org/redirect?url=http://researcharchive.calacademy.org/research/ichthyology/catalog/fishcatmain.asp

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. The Catalog of Fishes is the authoritative reference for taxonomic fish names, featuring a searchable on-line database. The Catalog of Fishes covers more than 53,000 species and subspecies, over 10,000 genera and subgenera, and includes in excess of 16,000 bibliographic references. The Catalog of Fishes consists of three hardbound volumes of 900-1000 pages each, along with a CD-ROM. The online database is updated about every 8 weeks and is now about twice the size of the published version. It is one of the oldest and most complete databases for any large animal group. References are over 30,000. Valid species are over 30,000. This work is an essential reference for taxonomists, scientific historians, and for any specialist dealing with fishes. Entries for species, for example, consist of species/subspecies name, genus, author, date, publication, pages, figures, type locality, location of type specimen(s), current status (with references), family/subfamily, and important publication, taxonomic, or nomenclatural notes. Nearly all original descriptions have been examined, and much effort has gone into determining the location of type specimens. The Genera are updated from Eschmeyer''s 1990 Genera of Recent Fishes. Both genera and species are listed in a classification using recent taxonomic schemes. Also included are a lengthy list of museum acronyms, an interpretation of the International Code of Zoological Nomenclature, and Opinions of the International Commission involving fishes.

Proper citation: Catalog of Fishes (RRID:SCR_004408) Copy   

•   Source: SciCrunch Registry

http://pgn.cornell.edu/

Resource for the storage, retrieval and annotation of plant ESTs, with a focus on comparative genomics. PGN comprises an analysis pipeline and a website, and presently contains mainly data from the Floral Genome Project. However, it accepts submission from other sources. All data in PGN is directly derived from chromatograms and all original and intermediate data are stored in the database. The current datasets on PGN come from the floral genome project and includes the following species: Acorus americanus, Amborella trichopoda, Asparagus officinalis, Cucumis sativus, Eschscholzia californica, Eschscholzia californica, Illicium parviflorum, Ipomopsis aggregata, Liriodendron tulipifera, Mesembryanthemum crystallinum, Mimulus guttatus, Nuphar advena, Papaver somniferum, Persea americana, Prymnesium parvum, Ribes americanum, Saruma henryi, Stenogyne rugosa, Vaccinium corymbosa, Welwitschia mirabilis, Yucca filamentosa, Zamia fischeri. For functional annotation, blast is used to compare find the best match of each unigene sequence to in the Genbank NR database, and the in complete coding sequences from Arabidopsis. These annotations are stored in the database and serve as the primary source of annotation. The annotation framework will be extended to Gene Ontology annotations in the future.

Proper citation: PGN (RRID:SCR_004559) Copy   

•   Source: SciCrunch Registry

http://pdbml.pdb.org/

Markup Language that provides a representation of PDB data in XML format. The description of this format is provided in XML schema of the PDB Exchange Data Dictionary. This schema is produced by direct translation of the mmCIF format PDB Exchange Data Dictionary Other data dictionaries used by the PDB have been electronically translated into XML/XSD schemas and these are also presented in the list below. * PDBML data files are provided in three forms: ** fully marked-up files, ** files without atom records ** files with a more space efficient encoding of atom records * Data files in PDBML format can be downloaded from the RCSB PDB website or by ftp. * Software tools for manipulating PDB data in XML format are available.

Proper citation: Protein Data Bank Markup Language (RRID:SCR_005085) Copy   

•   Source: SciCrunch Registry