Curator Dashboard

Portal and tools for sharing and editing neurophysiological and behavioral data for brain-machine interface research. Users can search for existing data or login with their Google, Facebook, or Twitter account and upload new data. Their main focus is on supporting brain-machine interface research, so we encourage users to not just provide recordings of brain activity data, but also information about stimuli, etc., so that statistical relationships can be found between stimuli and/or subject behavior and brain activity. The Matlab tools are for writing, reading, and converting Neuroshare files, the common file format. A free, open source desktop tool for editing neurophysiological data for brain-machine interface research is also available: https://github.com/ATR-DNI/BrainLiner Since data formats aren''''t standardized between programs and researchers, data and analysis programs for data cannot be easily shared. Neuroshare was selected as the common file format. Neuroshare can contain several types of neurophysiological data because of its high flexibility, including analog time-series data and neuronal spike timing. Some applications have plug-ins or libraries available that can read Neuroshare format files, thus making Neuroshare somewhat readily usable. Neuroshare can contain several types of neurophysiological data, but there were no easy tools to convert data into the Neuroshare format, so they made and are providing a Neuroshare Converter Library and Simple Converter using the library. In future work they will make and provide many more useful tools for data sharing. Shared experiments include: EMG signal, Takemiya Exp, Reconstruct (Visual image reconstruction from human brain activity using a combination of multi-scale local image decoders), SPIKE data, Speech Imagery Dataset (Single-trial classification of vowel speech imagery using common spatial patterns), Functional Multineuron Calcium Imaging (fMCI), Rock-paper-scissors (The data was obtained from subject while he make finger-form of rock/paper/scissors). They also have a page at https://www.facebook.com/brainliner where you can contact us

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• SciCrunch
• 16 years ago - by Anonymous

Software to interpret undetected homolog.Method that calculates probability that homolog of given gene would fail to be detected by homology search in given species, even if homolog were present and evolving normally.

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• RRID
• 4 years ago - by Anonymous

SerbGO is a web-based tool intended to assist researchers determine which microarray tools for gene expression analysis which make use of the GO ontologies are best suited to their projects. SerbGO is a bidirectional application. The user can ask for some features by checking on the Query Form to get the appropriate tools for their interests. The user can also compare tools to check which features are implemented in each one. Platform: Online tool

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• SciCrunch
• 15 years ago - by Anonymous

Leading collaborative interdisciplinary organization that advances research, education, and training in quantum science and engineering. Helps to unify and promote research in quantum science and engineering in the Pittsburgh area. PQI members have faculty appointments from Carnegie Mellon University, Duquesne University, and the University of Pittsburgh in physics, chemistry, and engineering disciplines. Connects with team based science intitiatives and shared facilities.Resources and Facilities for Quantum Research include Carnegie Mellon Nanofabrication Facility,Center for Research Computing, Gertrude E. and John M. Petersen Institute of NanoScience and Engineering (PINSE), Materials Characterization Facility, Pittsburgh Supercomputing Center,QCFD (Quantum Computing/Computational Fluid Dynamics).

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• SciCrunch
• 4 years ago - submitted by Edyta Vieth

Newt-omics is a database, which enables researchers to locate, retrieve and store data sets dedicated to the molecular characterization of newts. Newt-omics is a transcript-centered database, based on an Expressed Sequence Tag (EST) data set from the newt, covering ~50,000 Sanger sequenced transcripts and a set of high-density microarray data, generated from regenerating hearts. Newt-omics also contains a large set of peptides identified by mass spectrometry, which was used to validate 13,810 ESTs as true protein coding. Newt-omics is open to implement additional high-throughput data sets without changing the database structure. Via a user-friendly interface Newt-omics allows access to a huge set of molecular data without the need for prior bioinformatical expertise. The newt Notopthalmus viridescens is the master of regeneration. This organism is known for more than 200 years for its exceptional regenerative capabilities. Newts can completely replace lost appendages like limb and tail, lens and retina and parts of the central nervous system. Moreover, after cardiac injury newts can rebuild the functional myocardium with no scar formation. To date only very limited information from public databases is available. Newt-Omics aims to provide a comprehensive platform of expressed genes during tissue regeneration, including extensive annotations, expression data and experimentally verified peptide sequences with yet no homology to other publicly available gene sequences. The goal is to obtain a detailed understanding of the molecular processes underlying tissue regeneration in the newt, that may lead to the development of approaches, efficiently stimulating regenerative pathways in mammalians. * Number of contigs: 26594 * Number of est in contigs: 48537 * Number of transcripts with verified peptide: 5291 * Number of peptides: 15169

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• SciCrunch
• 15 years ago - by Anonymous

Software for short read alignment and mapping of sequencing reads where the DNA sequence is somehow modified and/or there is more divergence between sample and reference than what fast mappers will handle.

• SciCrunch
• 9 years ago - submitted by Isabella Froman

An open bioinformatis software repository with no tie to any organization or institution. Contact them to host your software.

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• SciCrunch
• 14 years ago - by Anonymous

PhenomeNet is a cross-species phenotype similarity network. It contains the experimentally observed phenotypes of multiple species as well as the phenotypes of human diseases. PhenomeNet provides a measure of phenotypic similarity between the phenotypes it contains. The latest release (from 22 June 2012) contains 124,730 complex phenotype nodes taken from the yeast, fish, worm, fly, rat, slime mold and mouse model organism databases as well as human disease phenotypes from OMIM and OrphaNet. The network is a complete graph in which edge weights represent the degree of phenotypic similarity. Phenotypic similarity can be used to identify and prioritize candidate disease genes, find genes participating in the same pathway and orthologous genes between species. To compute phenotypic similarity between two sets of phenotypes, we use a weighted Jaccard index. First, phenotype ontologies are used to infer all the implications of a phenotype observation using several phenotype ontologies. As a second step, the information content of each phenotype is computed and used as a weight in the Jaccard index. Phenotypic similarity is useful in several ways. Phenotypic similarity between a phenotype resulting from a genetic mutation and a disease can be used to suggest candidate genes for a disease. Phenotypic similarity can also identify genes in a same pathway or orthologous genes. PhenomeNet uses the axioms in multiple species-dependent phenotype ontologies to infer equivalent and related phenotypes across species. For this purpose, phenotype ontologies and phenotype annotations are integrated in a single ontology, and automated reasoning is used to infer equivalences. Specifically, for every phenotype, PhenomeNet infers the related mammalian phenotype and uses the Mammalian Phenotype Ontology for computing phenotypic similarity. Tools: * PhenomeBLAST - A tool for cross-species alignments of phenotypes * PhenomeDrug - method for drug-repurposing

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• SciCrunch
• 15 years ago - by Anonymous

A suite of tools to address common questions raised in genomic studies - mostly with regard to overlap and proximity relationships between data sets.

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• SciCrunch
• 13 years ago - by Anonymous

A network for supporting resting-state fMRI (R-fMRI) related studies. It connects R-fMRI researchers (as nodes) by their sharings (as edges). Through the network, ideas, comments, resources, tools, experiences, and data can be shared. Researchers (nodes) with basic neuroscience, methodological, or clinical backgrounds can connect with each other in the network. It also contains a preprint server that allows neuroscientists to share their preprints, comment on each others research and get back valuable information about their experiments from their colleagues. This is based on the arXiv model. Ultimately, the network aims to enhance collaborations among researchers, especially to translate knowledge of basic neuroscience and methodology to clinical applications (bench to bedside).

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• SciCrunch
• 13 years ago - by Anonymous

A utility, whose output is a PostScript file of aligned sequences with graphical enhancements. Its main input is an ascii file of pre-aligned sequences. Optional files allow further rendering. The program calculates a similarity score for each residue of the aligned sequences. The output shows: * Secondary Structures * Aligned sequences * Similarities * Accessibility * Hydropathy * User-supplied markers * Intermolecular contacts In addition, similarity score can be written in the bfactor column of a pdb file, to enable direct display of highly conserved areas. You can run ESPript from this server with the HTML interface. It is configured for a maximum of 1,000 sequences. Links to webESPript * ENDscript: you can upload a PDB file or enter a PDB code such as 1M85. The programs DSSP and CNS are executed via the interface, so as to obtain an ESPript figure with a lot of structural information (secondary structure elements, intermolecular contacts). You can also find homologous sequences with a BLAST search, perform multiple sequence alignments with MULTALIN or CLUSTALW and create an image with BOBSCRIPT or MOLSCRIPT to show similarities on your 3D structure. * ProDom: you can enter a sequence identifier to find homologous domains, perform multiple sequence alignments with MULTALIN and click on the link to ESPript. * Predict Protein: you can receive a mail in text (do not use the HTML option when you submit your request in Predict Protein) with aligned sequences and numerous information including secondary structure prediction. Click on a special html link to upload your mail in ESPript. * NPS(at): you can execute the programs BLAST and CLUSTALW to obtain multiple alignments. You can predict secondary structure elements and click on the link to ESPript. This program started in the laboratory of Dr Richard Wade at the Institut de Biologie Structurale, Grenoble. It moved later to the Laboratory of Molecular Biophysics in Oxford, then to the Institut de Pharmacologie et de Biologie Structurale in Toulouse. It is now developed in the Laboratoire de BioCristallographie of Dr Richard Haser, Institut de Biologie et de Chimie des Prot��������ines, Lyon and in the Laboratoire de Biologie Mol��������culaire et de Relations Plantes-Organismes, group of Dr Daniel Kahn, Institut National de la Recherche Agronomique de Toulouse.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Integrated RNA-Seq read analysis., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

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• SciCrunch
• 13 years ago - by Anonymous

An interactive multiresolution brain atlas that is based on over 20 million megapixels of sub-micron resolution, annotated, scanned images of serial sections of both primate and non-primate brains and integrated with a high-speed database for querying and retrieving data about brain structure and function. Currently featured are complete brain atlas datasets for various species, including Macaca mulatta, Chlorocebus aethiops, Felis catus, Mus musculus, Rattus norvegicus, Tyto alba and many other vertebrates. BrainMaps is currently accepting histochemical, immunocytochemical, and tracer connectivity data, preferably whole-brain. In addition, they are interested in EM, MRI, and DTI data.

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• SciCrunch
• 14 years ago - by Anonymous

A database on nucleotide sequences of 5S rRNAs and their genes. The database contains 1985 primary structures of 5S rRNA and 5S rDNA, and was last updated in 2002, according to the website. They include 60 archaebacterial, 470 eubacterial, 63 plastid, nine mitochondrial and 1383 eukaryotic sequences. The nucleotide sequences of the 5S rRNAs or 5S rDNAs are divided according to the taxonomic position of the source organisms. The sequences for particular organisms can be retrieved as single files using a taxonomic browser or in multiple sequence structural alignments. The multiple sequence alignments of 5S ribosomal RNAs can be downloaded in TAB-delimited and FASTA formats.

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• SciCrunch
• 17 years ago - by Anonymous

ESTScan is a program that can detect coding regions in DNA sequences, even if they are of low quality. ESTScan will also detect and correct sequencing errors that lead to frameshifts. ESTScan is not a gene prediction program , nor is it an open reading frame detector. In fact, its strength lies in the fact that it does not require an open reading frame to detect a coding region. As a result, the program may miss a few translated amino acids at either the N or the C terminus, but will detect coding regions with high selectivity and sensitivity. ESTScan takes advantages of the bias in hexanucleotide usage found in coding regions relative to non-coding regions. This bias is formalized as an inhomogeneous 3-periodic fifth-order Hidden Markov Model (HMM). Additionally, the HMM of ESTScan has been extended to allows insertions and deletions when these improve the coding region statistics.

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• SciCrunch
• 15 years ago - by Anonymous

A phylogenetic tree of global human mitochondrial DNA variation, based on both coding- and control-region mutations, and including haplogroup nomenclature.

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• SciCrunch
• 13 years ago - by Anonymous

A network that provides support and NIH funding for neuroscience research and drug development through access to contract research organizations for outsourcing and research consultation. Successful applicants will receive funding to conduct biological testing, access to a full range of industry-style drug development services and expertise, and control of the intellectual property for drug candidates. Funded projects include treatments for age-related macular degeneration, ALS, Alzheimer's disease, depression, hearing loss, optic neuropathy and stroke.

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• SciCrunch
• 15 years ago - by Anonymous

An open-source bioinformatic tool to create simulated omic shotgun and amplicon sequence libraries for all main sequencing platforms. The tool is available through multiple interfaces like GUI, CLI and API. It is useful for simulating clinical or environmental microbial communities and complements the use of in vitro mock communities.

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• SciCrunch
• 13 years ago - by Anonymous

An entry of the Cognitive Atlas which defines the term speech perception.

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• SciCrunch
• 15 years ago - by Anonymous

A department within the University of Washington which focuses on both undergraduate and postgraduate education in biochemistry.

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• SciCrunch
• 15 years ago - by Anonymous