Curator Dashboard

A database of manually curated dSNPs on the 3''UTRs of human genes from available publications in PubMed. The advanced web interface allows users to perform proximity searches between miRNA target sites and dSNPs by gene name, miRbase ID, target prediction algorithm, disease, and any nucleotide distance between dSNPs and miRNA target sites. The web interface displays detailed sequence views showing the relationship between dSNPs, miRNA target sites, and SNPs. An interactive visualization tool shows the chromosomal distribution of dSNPs, miRNA target sites (from TargetScan), and SNPs. miRdSNP provides a comprehensive data source of dSNPs and robust tools to capture their spacial relationship with miRNA target sites on the 3''UTRs of human genes. miRdSNP enables researchers to further explore the molecular mechanism of gene dysregulation for dSNPs at posttranscriptional level.

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• SciCrunch
• 13 years ago - by Anonymous

Portal supporting the North East Bioinformatics Collaborative''s project to sequence the genome of the Little Skate. Provided is a clearinghouse for Little Skate Genome Project and other publicly available Skate and Ray (Batoidea) genome data, and tools for data visualization and analysis. Little Skate Genome Project The little skate (Leucoraja erinacea) is a chondrichthyan (cartilaginous) fish native to the east coast of North America. Elasmobranchs (Skates, Rays, and Sharks) exhibit many fundamental vertebrate characteristics, including a neural crest, jaws and teeth, an adaptive immune system, and a pressurized circulatory system. These characteristics have been exploited to promote understanding about human physiology, immunology, stem cell biology, toxicology, neurobiology and regeneration. The development of standardized experimental protocols in elasmobranchs such as L. erinacea and the spiny dogfish shark (Squalus acanthias) has further positioned these organisms as important biomedical and developmental models. Despite this distinction, the only reported chondrichthyan genome is the low coverage (1.4x) draft genome of the elephant shark (Callorhinchus milii). To close the evolutionary gaps in available elasmobranch genome sequence data, and generate critical genomic resources for future biomedical study, the genome of L. erinacea is being sequenced by the North East Bioinformatics Collaborative (NEBC). As close evolutionary relatives, the little skate sequence will facilitate studies that employ dogfish shark and other elasmobranchs as model organisms. Skate tools include the SkateBLAST and the Skate Genome Browsers: Little Skate Mitochondrion, Thorny Skate Mitochondrion, and Ocellate Spot Skate Mitochondrion.

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• SciCrunch
• 15 years ago - by Anonymous

Ontology of Computer retrieval of Information on Scientific Projects (CRISP).

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• SciCrunch
• 13 years ago - by Anonymous

Core facility provides a model for collaborative approaches to use specialized resources and expertise in an integrated process. Core builds on the expertise and resources provided by the Bioinformatics Cores of the five northeastern states that form NECC. The Skate Genome Annotation Workshops and Jamborees offer training and opportunities for faculty and students to work with and annotate genome sequences. Workshops include lectures, tutorials and exercises annotating the genome of the little skate, Leucoraja erinacea.

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• SciCrunch
• 15 years ago - by Anonymous

Software that performs a morphology-based approach for the automatic identification of outlier neurons based on neuronal tree structures. This tool was used by Zawadzki et al. (2012), who reported on and its application to the NeuroMorpho database. For the analysis, each neuron is represented by a feature vector composed of 20 measurements, which are projected into lower dimensional space with PCA. Bivariate kernel density estimation is then used to obtain a probability distribution for cells. Cells with high probabilities are understood as archetypes, while those with the small probabilities are classified as outliers. Further details about the method and its application in other domains can be found in Costa et al. (2009) and Echtermeyer et al. (2011). This version requires Matlab (Mathworks Inc, Natick, USA) and allows the user to apply the workflow using a graphical user interface.

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• SciCrunch
• 15 years ago - by Anonymous

A database thatprovides access to information about toxic compounds (names, synonyms and structures). It is primarily designed for pharmacists, biochemists, and medical scientists, but also researchers working in cognate disciplines. SuperToxic predicts the toxicity of compounds, informs about potential targets in biochemical pathways and shows potential binding partners. The database also includes links to suppliers, where the compound can be obtained for further investigations. The current version of this database compiles approx. 60,000 compounds with about 100,000 synonyms. These molecules are classified according to their toxicity based on more than 2,500,000 measurements.

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• SciCrunch
• 17 years ago - by Anonymous

Patient-derived specimens are essential to research in genomics, proteomics, and biomarkers. We provide banking for biological fluid and tissue specimens as well as human DNA and RNA. We provide secure archival sample storage as well as clinically-annotated specimen biobanks for defined research projects. The core serves the human research blood and tissue banking needs of clinical and translational researchers. Samples can be banked by an individual PI or by a consortium of investigators. All samples are tracked and archived using a secure tracking database, the Einstein-Montefiore Bio-Repository Databank (EM-BRED), http://informatics30.aecom.yu.edu/em-bred/default.aspx. EM-BRED provides qualified investigators with a solution to securely link patient specimens to clinical and pathological data. It consists of a user-friendly query engine that allows for comprehensive specimen search, and ultimately to build clinical annotations of relevance. The facility works under the best practices set out by NCI and ISBER (2006) for collection, storage, and retrieval of human biological materials for research.

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• SciCrunch
• 15 years ago - by Anonymous

A web service to extract Protein-protein interaction (PPI)-relevant articles from MEDLINE that provides protein interaction information (PPI) articles for biologists, baseline system performance for bio-text mining researchers and a compact PubMed-search environment for PubMed users. It accepts PubMed input formats including All Fields, Author, Journal, MeSH Terms, Publication Date, Title, and Title/Abstract with Boolean operations (AND, OR, and NOT). However, the output is the list of articles prioritized by PPI confidence rates. Some words (mostly gene/protein names) which contributed for PPI prediction are underlined and linked to Entrez or Entrez Gene. Even though our system focuses on a PubMed search environment, it also provides a CGI access for bio-text mining researchers. Using the CGI program, a list of PubMed IDs can be obtained as a query result, thus it can be utilized as a baseline system performance. PIE the search is based on a winning approach in the BioCreative III ACT competition (BC3)1. For input queries, MEDLINE articles are first retrieved through the PubMed service. PPI scores are calculated for the retrieved articles, and the articles are re-ranked based on scores. To effectively capture PPI patterns from biomedical literature, their approach utilizes both word and syntactic features for machine learning classifiers. Dependency parsing, gene mention tagging, and term-based features are utilized along with a Huber classifier.

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• SciCrunch
• 13 years ago - by Anonymous

A commercial service organization from Zyagen.

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• SciCrunch
• 14 years ago - by Anonymous

A SVM (support vector machine-based software tool for prediction of most probable microRNA coding regions in genome scale sequences.

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• SciCrunch
• 13 years ago - by Anonymous

An encyclopedia that is dedicated to a ligand and binding site oriented view of the protein structural space. SuperSite integrates evolutionary information in the proteins as well as predicted binding sites from LigsiteCSC. A point set match algorithm is implemented that allows to screen the surface of a protein for the occurrence of possible binding sites as well as a similarity screen for similar compounds based on fingerprints. SuperSite allows users to discover the ligand space of the PDB, check for evolutionary conservation of residues using HSSP files, display possible binding sites of proteins via the LigsiteCSC algorithm, similarity screen for ligands contained in the SuperSite, and screen a protein for the possible similarity of binding pockets towards certain known drug binding sites.

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• SciCrunch
• 17 years ago - by Anonymous

Collaborative environment of building and validating electronic phenotype algorithms using electronic medical records (EMRs) and natural language processing (NLP) for use in genome-wide association studies (GWAS). On this site you can: View existing algorithms, Enter or create new algorithms, Collaborate with others to create or review algorithms, View implementation details for existing algorithms. The Electronic Medical Records and Genomics Network (eMERGE) has investigated whether data captured through routine clinical care using electronic medical records (EMRs) can identify disease phenotypes with sufficient positive and negative predictive values for use in genome-wide association studies (GWAS). Most EMRs captured key information (diagnoses, medications, laboratory tests) used to define phenotypes in a structured format; in addition, natural language processing has also been shown to improve case identification rates. PheKB is an outgrowth of that validation effort. Phenotype algorithms can be viewed by data modalities or methods used: CPT codes, ICD 10 codes, ICD 9 codes, Laboratories, Medications, Vital Signs, Natural Language Processing Algorithms can also be viewed by: * Implementation results (positive predictive value, sensitivity, publications) * Institution * Work Group

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• SciCrunch
• 15 years ago - by Anonymous

A web-based tool that supports more than 50 different classes of queries against nearly a dozen different types of text, scientific abstract or bioinformatic databases. The typical query supported by PolySearch is Given X, find all Y''s where X or Y can be diseases, tissues, cell compartments, gene/protein names, SNPs, mutations, drugs and metabolites. PolySearch also exploits a variety of techniques in text mining and information retrieval to identify, highlight and rank informative abstracts, paragraphs or sentences.

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• SciCrunch
• 13 years ago - by Anonymous

A desktop application for push-button automated sequence analysis that can utilize cloud computing resources. CloVR is implemented as a single portable virtual machine (VM) that provides several automated analysis pipelines for microbial genomics, including 16S, whole genome and metagenome sequence analysis. The CloVR VM runs on a personal computer, utilizes local computer resources and requires minimal installation, addressing key challenges in deploying bioinformatics workflows. In addition CloVR supports use of remote cloud computing resources to improve performance for large-scale sequence processing.

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• SciCrunch
• 13 years ago - by Anonymous

A portable software infrastructure designed to analyze massive genomics datasets produced by contemporary and emerging technologies, in particular Next Generation Sequencing (NGS) platforms. It consists of a comprehensive suite of infrastructure tools focused on enabling the end-to-end analysis of sequence data ? from from raw base calling to analyzed variants ready for interpretation by users. SeqWare is tool agnostic, it is a framework for building analysis workflows and does not provide specific implementations out-of-the-box. You use SeqWare to create high-throughput infrastructure for NGS analysis using whatever analysis tools you like. SeqWare currently provides 5 main tools specifically designed to support massively parallel sequencing technologies. All tools can be used together or separately: * MetaDB: provides a common database to store metadata used by all components. * Portal: a LIMS-like web application to manage samples, record computational events, and present results back to end users. * Pipeline: a workflow engine that is capable of wrapping and combining other tools (BFAST, BWA, SAMtools, etc) into complex pipelines, recording metadata about the analysis, and facilitates automation of pipelines based on metadata. * Web Service: a programmatic API that lets people build new tools on top of the project * Query Engine: a NoSQL database designed to store and query variants and other events inferred from sequence data.

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• SciCrunch
• 13 years ago - by Anonymous

A web ontology for the semantic representation of the computer assisted brain trauma rehabilitation domain. This is a novel and emerging domain, since it employs the use of robotic devices, adaptation software and machine learning to facilitate interactive, adaptive and personalized rehabilitation care, patient monitoring and assisted living.

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• SciCrunch
• 13 years ago - by Anonymous

A biomedical research institute that aims to understand and develop more effective treatments for human disease, focusing on critical research areas such as heart disease, cancer, lupus and Alzheimer's disease.

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• SciCrunch
• 15 years ago - by Anonymous

Analysis-tool which identifies singular node motifs in a network. Network nodes can be described by node-motifs. It is an improvement to the method described in Costa et al. (2009).

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• SciCrunch
• 15 years ago - by Anonymous

A database of scents. Users can search their structure or by scent tree, and can also add or search for specific scents by name. The database SuperScent was established to supply users with detailed information on the variety of odor components. The version of the database presented here comprises the 2D/3D structures of approximately 2100 volatiles and around 9200 synonyms as well as physicochemical properties, commercial availability and references. The volatiles are classified according to their origin, functionality and odorant groups. The information was extracted from the literature and web resources. SuperScent offers several search options, e.g. name, Pubchem ID number, species, functional groups, or molecular weight.

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• SciCrunch
• 17 years ago - by Anonymous

A sample script on how to map some numbers to brain regions, using the Talairach-Tournoux Atlas database. For example, put the value 0.379 in each hippocampus voxel, and the value 0.666 in each superior temporal gyrus voxel.

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• SciCrunch
• 15 years ago - by Anonymous