Curator Dashboard

Research and development organization that hosts a knowledgebase in diverse scientific areas. It also hosts a network of national Indian laboratories, outreach centres, and innovation complexes.

• Organization
• SciCrunch
• 14 years ago - submitted by Andrea Stagg

THIS RESOURCE IS NO LONGER IN SERVICE, documented July 7, 2017. Formerly a commercial organization for clinical diagnostics, blood screening, transplant products and research products, it had been acquired by Hologic in 2012.

• Resource
• SciCrunch
• 14 years ago - by Anonymous

A powerful genomic analysis platform that provides access to hundreds of tools for gene expression analysis, proteomics, SNP analysis, flow cytometry, RNA-seq analysis, and common data processing tasks. A web-based interface provides easy access to these tools and allows the creation of multi-step analysis pipelines that enable reproducible in silico research.

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• SciCrunch
• 17 years ago - by Anonymous

Software R-package for running gene set analysis using various statistical methods, from different gene level statistics and a wide range of gene-set collections. The Piano package contains functions for combining the results of multiple runs of gene set analyses.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Software package for interpreting gene expression data. Used for interpretation of a large-scale experiment by identifying pathways and processes.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

An R/Bioconductor package to identify chromosomal interaction regions generated by chromosome conformation capture (3C) coupled to next-generation sequencing (NGS), a technique termed 3C-seq. It performs data analysis for a number of different experimental designs, as it can analyze 3C-seq data with or without a control experiment and it can be used to facilitate data analysis for experiments with multiple replicates. The r3Cseq package provides functions to perform data normalization, statistical analysis for cis/trans interactions and visualization in order to help scientists identify genomic regions that physically interact with the given viewpoints of interest. This tool greatly facilitates hypothesis generation and the interpretation of experimental results.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 20,2025. A data analysis and extraction tool from the US Census Bureaus with recoding capabilities to customize federal, state, and local data to suit your requirements. DataFerret works with the DataWeb, a network of online data libraries and an infrastructure for intelligent browsing. TheDataweb provides easy access to data from disparate locations across the internet using DataFerrett as its interface. It brings together demographic, economic, environmental, health, and other datasets that are usually separated by geography and/or organization.Using DataFerrett, you can develop an unlimited array of customized spreadsheets that are as versatile and complex as your usage demands. For a listing/description of datasets available using the DataFerrett refer to the Datasets Available tab. DataFerrett helps you locate and retrieve the data you need across the Internet to your desktop or system, regardless of where the data resides. You can develop and customize tables and select the results to create a graph or map for a visual depiction of your data. You can also save your data in the databasket and save the table you have created for reuse. The DataFerrett tool can use a java applet through an internet browser or be installed as an application on your desktop. The DataFerrett Applet requires you to have popup windows enabled in your browser for this website to function properly.

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• SciCrunch
• 17 years ago - by Anonymous

Centre of Excellence in Vision Science that brings together major vision research programs at the The Australian National University with cognate programs at the Universities of Queensland, Sydney and Western Australia. The research is focused on unravelling the cellular basis of visual sensing and processing; on revealing the algorithms that underlie the visual control of behavior and perception; and on discovering the cellular mechanisms that make the eye and retina stable, and whose breakdown causes blindness.

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• SciCrunch
• 13 years ago - by Anonymous

Commercial organization that provides services for assay development, research histopathology, and early stage project consultation.

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• SciCrunch
• 13 years ago - by Anonymous

Data archive of more than 500,000 files of research in the social sciences, hosting 16 specialized collections of data in education, aging, criminal justice, substance abuse, terrorism, and other fields. ICPSR comprises a consortium of about 700 academic institutions and research organizations providing training in data access, curation, and methods of analysis for the social science research community. ICPSR welcomes and encourages deposits of digital data. ICPSR's educational activities include the Summer Program in Quantitative Methods of Social Research external link, a comprehensive curriculum of intensive courses in research design, statistics, data analysis, and social methodology. ICPSR also leads several initiatives that encourage use of data in teaching, particularly for undergraduate instruction. ICPSR-sponsored research focuses on the emerging challenges of digital curation and data science. ICPSR researchers also examine substantive issues related to our collections, with an emphasis on historical demography and the environment.

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• SciCrunch
• 17 years ago - by Anonymous

Project exploring the spectrum of genomic changes involved in more than 20 types of human cancer that provides a platform for researchers to search, download, and analyze data sets generated. As a pilot project it confirmed that an atlas of changes could be created for specific cancer types. It also showed that a national network of research and technology teams working on distinct but related projects could pool the results of their efforts, create an economy of scale and develop an infrastructure for making the data publicly accessible. Its success committed resources to collect and characterize more than 20 additional tumor types. Components of the TCGA Research Network: * Biospecimen Core Resource (BCR); Tissue samples are carefully cataloged, processed, checked for quality and stored, complete with important medical information about the patient. * Genome Characterization Centers (GCCs); Several technologies will be used to analyze genomic changes involved in cancer. The genomic changes that are identified will be further studied by the Genome Sequencing Centers. * Genome Sequencing Centers (GSCs); High-throughput Genome Sequencing Centers will identify the changes in DNA sequences that are associated with specific types of cancer. * Proteome Characterization Centers (PCCs); The centers, a component of NCI's Clinical Proteomic Tumor Analysis Consortium, will ascertain and analyze the total proteomic content of a subset of TCGA samples. * Data Coordinating Center (DCC); The information that is generated by TCGA will be centrally managed at the DCC and entered into the TCGA Data Portal and Cancer Genomics Hub as it becomes available. Centralization of data facilitates data transfer between the network and the research community, and makes data analysis more efficient. The DCC manages the TCGA Data Portal. * Cancer Genomics Hub (CGHub); Lower level sequence data will be deposited into a secure repository. This database stores cancer genome sequences and alignments. * Genome Data Analysis Centers (GDACs) - Immense amounts of data from array and second-generation sequencing technologies must be integrated across thousands of samples. These centers will provide novel informatics tools to the entire research community to facilitate broader use of TCGA data. TCGA is actively developing a network of collaborators who are able to provide samples that are collected retrospectively (tissues that had already been collected and stored) or prospectively (tissues that will be collected in the future).

• Resource
• SciCrunch
• 13 years ago - by Anonymous

The GOToolBox web server provides a series of programs allowing the functional investigation of groups of genes, based on the Gene Ontology resource. The web version of the GOToolBox is free for non-commercial users only. Users from commercial companies are allowed to use the site during a reasonable testing period. For a regular use of the web version, a license fee should be paid. We have developed methods and tools based on the Gene Ontology (GO) resource allowing the identification of statistically over- or under-represented terms in a gene dataset; the clustering of functionally related genes within a set; and the retrieval of genes sharing annotations with a query gene. GO annotations can also be constrained to a slim hierarchy or a given level of the ontology. The source codes are available upon request, and distributed under the GPL license. Platform: Online tool

• Resource
• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented July 7, 2017. Welcome to the home of GOLEM: An interactive, graphical gene-ontology visualization, navigation,and analysis tool on the web. GOLEM is a useful tool which allows the viewer to navigate and explore a local portion of the Gene Ontology (GO) hierarchy. Users can also load annotations for various organisms into the ontology in order to search for particular genes, or to limit the display to show only GO terms relevant to a particular organism, or to quickly search for GO terms enriched in a set of query genes. GOLEM is implemented in Java, and is available both for use on the web as an applet, and for download as a JAR package. A brief tutorial on how to use GOLEM is available both online and in the instructions included in the program. We also have a list of links to libraries used to make GOLEM, as well as the various organizations that curate organism annotations to the ontology. GOLEM is available as a .jar package and a macintosh .app for use on- or off- line as a stand-alone package. You will need to have Java (v.1.5 or greater) installed on your system to run GOLEM. Source code (including Eclipse project files) are also available. GOLEM (Gene Ontology Local Exploration Map)is a visualization and analysis tool for focused exploration of the gene ontology graph. GOLEM allows the user to dynamically expand and focus the local graph structure of the gene ontology hierarchy in the neighborhood of any chosen term. It also supports rapid analysis of an input list of genes to find enriched gene ontology terms. The GOLEM application permits the user either to utilize local gene ontology and annotations files in the absence of an Internet connection, or to access the most recent ontology and annotation information from the gene ontology webpage. GOLEM supports global and organism-specific searches by gene ontology term name, gene ontology id and gene name. CONCLUSION: GOLEM is a useful software tool for biologists interested in visualizing the local directed acyclic graph structure of the gene ontology hierarchy and searching for gene ontology terms enriched in genes of interest. It is freely available both as an application and as an applet.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 5, 2023. This site has a collection of cortical connectivity datasets and modeling software components that can be downloaded and used for modeling of cortical circuits. The toolbox combines Matlab functions and neuroanatomical data sets useful in the analysis of structural or functional brain networks. Several people have made contributions and if you wish to contribute yourself with a new function or set of functions please contact osporns_at_indiana.edu.The following is a collection of commonly used large scale cortical connectivity data sets compiled from tract-tracing studies. Hence nodes represent cortical areas and links represent large cortico-cortical tracts. * macaque71.mat (BD network). Macaque cortical connectivity: 71 nodes 746 links. Reference: Young (1993). Contributor: OS. Used in e.g. Sporns (2002). * fve30.mat; fve32.mat (BD networks). Two version the macaque visual cortex. fve30.mat: 30 nodes 311 links. fve32.mat: 32 nodes 320 links. Reference: Felleman and van Essen (1991). Contributor: OS. Used in e.g. Sportns et al. (2000) Sporns and Kotter (2004). * macaque47.mat (BD network). Large scale cortico-cortical connectivity matrix of the visual and sensorimotor areas in the macaque. 47 nodes; 505 links. Used in e.g. Honey et al. (2007). Contributor: RK. * cat.mat (WD networks). Connection matrices of cat cortex. CIJall contains all cortical and thalamic areas: 95 nodes 2126 links. CIJctx contains only 52 cortical areas: 52 nodes 820 links. Reference: Scannell et al. (1999). Contributor: OS. Used in e.g. Sporns and Zwi (2004) Sporns and Kotter (2004). * DSIhumanctx.mat (WU networks).

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2025. Software program to aid in designing of primers and creation of primer sheets. The program allows users to select a background and enter mutaions. An initial primer is then suggested. User can manipulate the selected primer to add or remove nucleotides from either 5? or 3? ends. A set of parameters reflecting the goodness of the primer is updated on the fly, as the user makes changes. Once happy with the primer, the information is saved in a primer sheet, which can then be uploaded to the BGME lab primer database on the Wiki.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Software application to visualize and navigate large trees in hyperbolic space. Features include: * visualize large trees with hundreds of nodes or more * rotate and drag the display in cartesian space * search and select nodes * copy clusters for pasting into other programs * color-code branches * label branches (eg, common family members) * zoom in and out * view phylogenetic trees and other hierarchical clusters, such as gene expression profile clusters * run on several platforms: Mac, Windows, Unix/Linux

• Resource
• SciCrunch
• 12 years ago - by Anonymous

Software that can accurately and sensitivity classify short reads of next-generation sequencing (NGS) into protein domain families. It is based on profile HMM and a supervised graph contribution algorithm. Compared to existing tools, it has high sensitivity and specificity in classifying short reads into their native domain families.

• Resource
• SciCrunch
• 13 years ago - by Anonymous

Web server to predict eukaryotic selenoproteins and SECIS (SElenoCysteine Insertion Sequences) elements along nucleotide sequences. SECISearch3 replaces its predecessor SECISearch as a tool for prediction of eukaryotic SECIS elements. Seblastian is a method for selenoprotein gene detection that uses SECISearch3 and then predicts selenoprotein sequences encoded upstream of SECIS elements. Seblastian is able to both identify known selenoproteins and predict new selenoproteins.

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• SciCrunch
• 13 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented July 7, 2017. Collection of inference methods used to predict functional linkages between proteins. These methods include the Phylogenetic Profile method which uses the presence and absence of proteins across multiple genomes to detect functional linkages; the Gene Cluster method which uses genome proximity to predict functional linkage; Rosetta Stone which uses a gene fusion event in a second organism to infer functional relatedness; and the Gene Neighbor method which uses both gene proximity and phylogenetic distribution to infer linkage.

• Resource
• SciCrunch
• 17 years ago - by Anonymous

A software pipeline for building loci from short-read sequences, such as those generated on the Illumina platform. It was developed to work with restriction enzyme-based data, such as RAD-seq, for the purpose of building genetic maps and conducting population genomics and phylogeography.

• Resource
• SciCrunch
• 13 years ago - by Anonymous