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http://purl.bioontology.org/ontology/SSE

Memorial Sloan-Kettering Cancer Center''s ontology of surgical secondary events (adverse events).

Proper citation: Surgical Secondary Events (RRID:SCR_007894) Copy   

•   Source: SciCrunch Registry

http://rfam.xfam.org/

The Rfam database is a collection of RNA families, each represented by multiple sequence alignments, consensus secondary structures and covariance models (CMs). The families in Rfam break down into three broad functional classes: Non-coding RNA genes, structured cis-regulatory elements and self-splicing RNAs. Typically these functional RNAs often have a conserved secondary structure which may be better preserved than the RNA sequence. The CMs used to describe each family are a slightly more complicated relative of the profile hidden Markov models (HMMs) used by Pfam. CMs can simultaneously model RNA sequence and the structure in an elegant and accurate fashion. Rfam is also available via FTP. You can find data in Rfam in various ways... * Analyze your RNA sequence for Rfam matches * View Rfam family annotation and alignments * View Rfam clan details * Query Rfam by keywords * Fetch families or sequences by NCBI taxonomy * Enter any type of accession or ID to jump to the page for a Rfam family, sequence or genome

Proper citation: Rfam (RRID:SCR_007891) Copy   

•   Source: SciCrunch Registry

https://www.univ-rennes1.fr/

The University of Rennes 1 is one of the two main universities in the city of Rennes, France. It is under the Academy of Rennes. It specializes in science, technology, law, economy, management and philosophy.

Proper citation: University of Rennes 1; Rennes; France (RRID:SCR_007649) Copy   

•   Source: SciCrunch Registry

http://www.researchcrossroads.org/index.php?option=com_content&view=article&id=205&Itemid=68

A database of funding opportunities from both public and private funding sources. Search by keyword and the funding opportunities matching your criteria are displayed. Click on the funding title to view the complete record. You may also add opportunities to the ResearchCrossroads database if you have registered.

Proper citation: ResearchCrossroads Funding Opportunities Database (RRID:SCR_007920) Copy   

•   Source: SciCrunch Registry

http://brig.sourceforge.net/

A cross-platform (Windows/Mac/Unix) application that can display circular comparisons between a large number of genomes, with a focus on handling genome assembly data.

Proper citation: BRIG (RRID:SCR_007802) Copy   

•   Source: SciCrunch Registry

http://patricbrc.vbi.vt.edu/portal/portal/patric/IncumbentBRCs?page=eric

ERIC is a resource of annotated enterobacterial genomes. Information is available and accessed through a open web portal uniting biological data and analysis tools. ERIC contains information on Escherichia, Shigella, Salmonella, Yersinia, and other microorgansims. ERIC has recently been moved over to PATRIC: The PATRIC BRC is now responsible for all bacterial species in the NIAID Category A-C Priority Pathogen lists for biodefense research, and pathogens causing emerging/reemerging infectious diseases. For ERIC users, we understand that the resource was valuable to your work. As such, we will be doing our very best to create a useful PATRIC resource to continue supporting your work. We realize that the transition will cause disruptions. However, it is a priority for us to work with established BRC users and communities to identify and prioritize our transition efforts. We have concentrated on the transfer of genomic data for this initial release. We anticipate adding new data, tools, and website features over the next several months. We look forward to working with you during the next 5 years., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ERIC (RRID:SCR_007644) Copy   

•   Source: SciCrunch Registry

http://thomsonreuters.com/metacore/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on March 17, 2022. An integrated software suite for functional analysis of experimental data. The scope of data types includes microarray and SAGE gene expression, SNPs and CGH arrays, proteomics, metabolomics, pathway analysis, Y2H and other custom interactions. MetaCore is based on a proprietary manually curated database of human protein-protein, protein-DNA and protein compound interactions, metabolic and signaling pathways and the effects of bioactive molecules in gene expression.

Proper citation: MetaCore (RRID:SCR_008125) Copy   

•   Source: SciCrunch Registry

http://medgene.med.harvard.edu/MEDGENE/

An algorithm that generates lists of genes associated with a gene or one or more disorders. The algorithm can be used in high-throughput screening experiments, can create disease-specific micro-arrays, and can sort the results of gene profiling data. Based on the co-citations of all Medline records, MedGene can retrieve the following relationships: 1. A list of human genes associated with a particular human disease in ranking order 2. A list of human genes associated with multiple human diseases in ranking order 3. A list of human diseases associated with a particular human gene in ranking order 4. A list of human genes associated with a particular human gene in ranking order 5. The sorted gene list from other disease related high-throughput experiments, such as micro-array 6. The sorted gene list from other gene related high-throughput experiments, such as micro-array

Proper citation: MedGene (RRID:SCR_008122) Copy   

•   Source: SciCrunch Registry

http://www.nibb.ac.jp/brish/indexE.html

Database of detailed protocols for single and double in situ hybridization (ISH) method, probes used by Yamamori lab and others useful for studies of brain, and many photos of mammalian (mostly mouse and monkey) brains stained with various gene probes. Also includes a brain atlas of gene expression. Currently, the atlas comprises a series of un-annotated images showing the localization of a particular probe or molecule, e.g., AChE.

Proper citation: BraInSitu: A homepage for molecular neuroanatomy (RRID:SCR_008081) Copy   

•   Source: SciCrunch Registry

http://www.iephb.nw.ru/labs/lab38/spirov/hox_pro/hox-pro00.html

The database HOX Pro contains information about organization, functions and evolution of gene ensembles, key roles in which play homeobox-genes. The HOX-Pro database is aimed at: 1. analysis and classification of regulatory and coding regions in diverse homeobox and related genes; 2. describing mutations and knock-outs of hox-genes, as well as hereditary diseases related to these genes; 3. graphical representation, comparisons and classification of hox-genes expression patterns and profiles (sea urchin blastula, Drosophila blastoderm and imaginal discs, vertebrate limbs, mammalian brain, human EC cells); 4. comparative analysis of organization of hox-based genetic networks the nematode Caenorhabditis elegans the sea urchins Strongylocentrotus purpuratus and other echinids, the fruit flies Drosophila melanogaster and D.virilis, the vertebrates chicken and mouse; 5. analysis of phylogeny and evolution of homeobox genes and clusters. The HOX Pro contains a broad spectrum of information including images, diagrams and animations. Currently this amounts to approximately 700 html-pages together with 400 images which contain information on 200 groups of genes and 90 promoters, in turn linked to maps of 15 HOX clusters and 9 genetic networks. For today it is known about 700 sequences of individual hox-genes of animals classified approximately in 200 homologous or paralogous groups. The HOX Pro database contains data on the structural and functional organization of the transcriptional regulatory machinery of homeobox and functionally related genes. The hierarchical organization of transcription regulation of metazoan genes is incorporated into the database schema. HOX Pro includes a hypertext description of the mechanisms of homeobox gene activation as well as the functional characteristics of proteins encoded by homeobox-containing and functionally related genes.

Proper citation: HOX Pro (RRID:SCR_008115) Copy   

•   Source: SciCrunch Registry

http://caps.ncbs.res.in/imotdb/

The interacting motif database or iMOTdb , lists interacting motifs that are identified for all structural entries in the PDB. The conserved patterns or finger prints are identified for individual structural entries and also grouped together for reporting the common motifs shared among all superfamily members. The iMOT package has been employed for identifying the motifs in the database. Realization of conserved residues that represent a protein family is crucial for clearer understanding of biological function as well as for the better recognition of additional members in sequence databases. Functionally important residues are recognized well due to their high degree of conservation in closely related sequences and are annotated in functional motif databases. Structural motifs are central to the integrity of the fold and require careful analysis for their identification. It reports the availability of a database of spatially interacting motifs in single protein structures as well as those among distantly related protein structures that belong to a superfamily. Spatial interactions amongst conserved motifs are automatically measured using sequence similarity scores and distance calculations. Interactions between pairs of conserved motifs are described in the form of pseudoenergies. iMOTdb database provides information for 854,488 motifs corresponding to 60,849 protein structural domains and 22,648 protein structural entries. Interacting motifs has been shown to assist our understanding of proteins structure and function. Information on such motifs should be of valuable in protein folding, modeling and engineering experiments. As shown in previous studies conserved spatially interacting motifs act as important constraint in pattern based remote homology search methods. The iMOT DB is provided with links to aid sequence search protocol using PHI-BLAST and SCAN MOT employing the interacting motifs. The interacting motifs representing the superfamilies of proteins are derived from structural alignments obtained from PASS2. These motifs are finger prints for a given protein family and provides useful insights regarding the structural and functional role regarding the protein. Pseudo potential evaluated between the various pairs of motifs reflects the interacting strength between the regions and highlights the thermodynamic stability of the local substructure. The database would thus provide useful insight into the understanding of the folding, structural modeling and envisaging mutational exercise on a given polypeptide.

Proper citation: Database of Spatially Interacting Motifs in Proteins (RRID:SCR_008194) Copy   

•   Source: SciCrunch Registry

http://www.saltlakecity.va.gov/psychology_postdoc/index.asp

This web site is an overview of the post-doctoral psychology training program at the VA Salt Lake City Health Care System (VA SLC HCS). Its purpose is to help prospective psychology post-docs learn about the training and professional growth opportunities that are available. The VA Salt Lake City Health Care System postdoctoral fellowship is a full-time, 12-month continuous appointment focused on specialty training in the evaluation and treatment of veterans with Post-Traumatic Stress Disorder. Postdoctoral Fellows will be active members of two interdisciplinary treatment teams: - The PTSD Clinical Team through the Mental Health Department - The Polytrauma Team through the Physical Medicine and Rehabilitation Department. Fellows will also provide community outreach to returning veterans from Afghanistan and Iraq. Especially relevant to the VA Mental Health Strategic Plan, psychological services are provided within the complementary areas of emotional trauma (e.g., military combat, military sexual trauma), physical trauma (e.g., TBI, orthopedic injuries), substance abuse, and couples/family discord, primarily within the OEF/OIF veteran population. Sponsors: This work is funded by the US Department of Veterans Affairs, Salt Lake City.

Proper citation: Psychology Post-doctoral Training Program, US Department of Veterans affairs, Salt Lake City, UT (RRID:SCR_008076) Copy   

•   Source: SciCrunch Registry

http://sig.biostr.washington.edu/projects/brain/

The UW Integrated Brain Project is one project within the national Human Brain Project, a national multi-agency effort to develop informatics tools for managing the exploding amount of information that is accumulating about the human brain. The objective of the UW Integrated Brain Project effort is to organize and integrate distributed functional information about the brain around the structural information framework that is the long term goal of our work. This application therefore extends the utility of the Digital Anatomist Project by using it to organize non-structural information. The initial driving neuroscience problem that is being addressed is the management, visualization and analysis of cortical language mapping data. In recent years, advances in imaging technology such as PET and functional MRI have allowed researchers to observe areas of the cortex that are activated when the subject performs language tasks. These advances have greatly accelerated the amount of data available about human language, but have also emphasized the need to organize and integrate the sometimes contradictory sources of data, in order to develop theories about language organization. The hypothesis is that neuroanatomy is the common substrate on which the diverse kinds of data can be integrated. A result of the work done by this project is a set of software tools for generating a 3-D reconstruction of the patient''s own brain from MRI, for mapping functional data to this reconstruction, for normalizing individual anatomy by warping to a canonical brain atlas and by annotating data with terms from an anatomy ontology, for managing individual lab data in local laboratory information systems, for integrating and querying data across separate data management systems, and for visualizing the integrated results. Sponsors: This Human Brain Project research is funded jointly by the National Institute on Deafness and Other Communication Disorders, the National Institute of Mental Health, and the National Institute on Aging.

Proper citation: University of Washington Integrated Brain Project (RRID:SCR_008075) Copy   

•   Source: SciCrunch Registry

http://www.gladstone.ucsf.edu/gladstone/site/gind/

GIND provides a highly interactive academic environment and state-of-the-art research facilities that are ideal for training in neuroscience and biomedical research. GIND Investigators hold university appointments at UCSF and participate in educational activities, including the teaching and training of graduate students and postdoctoral fellows. Additionally, GIND is actively engaged in efforts to translate scientific discoveries into better treatments for major diseases of the nervous system. Sponsors: Support for GIND comes from the University of California at San Francisco.

Proper citation: Gladstone Institute of Neurological Disease (RRID:SCR_008072) Copy   

•   Source: SciCrunch Registry

http://mmil.ucsd.edu/

An interdisciplinary group of scientists and clinicians who study the human brain using a variety of imaging, recording, and computational techniques. Their primary goal is to bridge non-invasive imaging technologies to the underlying neurophysiology of brain neuronal circuits for a better understanding of healthy human brain function, and mechanisms of disruption of this function in diseases such as Alzheimer's, epilepsy and stroke. The other goal of the MMIL is to develop and apply advanced imaging techniques to understanding the human brain and its disorders. In order to ground these methodological developments in their underlying neurobiology, invasive studies in humans and animals involving optical and micro physiological measures are also performed. These methodologies are applied to understanding normal function in sleep, memory and language, development and aging, and diseases such as dementia, epilepsy and autism.

Proper citation: Multimodal Imaging Laboratory (RRID:SCR_008071) Copy   

•   Source: SciCrunch Registry

http://dictybase.org

This website contains the genome sequence of Dictyostelium discoideum. The determination of the entire information content of the Dictyostelium genome will be of great value to those working with this organism directly, as well as to those who would like to determine the functions of homologous genes from other species. Dictyostelium discoideum, a soil-living amoeba, is an excellent organism for the study of the molecular mechanisms of cell motility, signal transduction, cell-type differentiation and developmental processes. Genes involved in any of these processes can be knocked-out rapidly by targeted homologous recombination. Since Dictyostelium is haploid, mutants are readily isolated and the REMI (restriction enzyme mediated integration) technique of insertional mutagenesis allows the facile cloning of disrupted genes. The Dictyostelium genome is being sequenced with the chromosomal shotgun methodology on a chromosome by chromosome basis. The six Dictyostelium chromosomes with sizes ranging from four to seven Mb are being separated by PFGE (Pulsed Field Gel Electrophoresis) by Edward Cox, Princeton University. Chromosomal libraries with insert sizes between 1 and 4 kb are being generated by the Sanger Centre using pUC18 as a vector. For shotgun sequencing both forward and reverse reads from each clone randomly selected from the chromosome-enriched libraries are being produced. The read pairs will represent a useful mapping resource to assess contig order. For every Mb of DNA an estimated number of 20,000 - 25,000 single shotgun reads will be necessary. The hereditary information is carried on 6 chromosomes with sizes ranging from 4 to 7 Mb resulting in a total of about 34 Mb of DNA, a multicopy 90 kb extrachromosomal element that harbours the rRNA genes, and the 55 kb mitochondrial genome. The estimated number of genes in the genome is 8,000 to 10,000 and many of the known genes show a high degree of sequence similarity to homologues in vertebrate species.

Proper citation: Dictyostelium discoideum genome database (RRID:SCR_008149) Copy   

•   Source: SciCrunch Registry

http://locus.jouy.inra.fr/cgi-bin/lgbc/mapping/common/intro2.pl?BASE=goat

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 16, 2013. This website contains information about the mapping of the caprine genome. It contains loci list, phenes list, cartography, gene list, and other sequence information about goats. This website contains 731 loci, 271 genes, and 1909 homologue loci on 112 species. It also allows users to summit their own data for Goatmap. ARK-Genomics is not-for-profit and has collaborators from all over the world with an interest in farm animal genomics and genetics. ARK-Genomics was initially set up in 2000 with a grant awarded from the BBSRC IGF (Investigating Gene Function) initiative and from core resources of the Roslin Institute to provide a laboratory for automated analysis of gene expression using state-of-the-art genomic facilities. Since then, ARK-Genomics has expanded considerably, building up considerable expertise and resources.

Proper citation: GoatMap Database (RRID:SCR_008144) Copy   

•   Source: SciCrunch Registry

http://cor.physiol.ox.ac.uk/

Cellular Open Resource is a Microsoft Windows environment for cellular modeling that is built around CellML (except for reactions and metadata which are not supported). It offers, through CellML, an ''out of the box'' access to a large database of single cell models. COR was among the early adopters of this standard, eventually forming the first publicly available CellML-based modeling and collaboration environment. From the onset, COR was designed to provide an environment that could not only be used by experienced modelers, but also by experimentalists, teachers and students. It therefore tries to combine a user-friendly interface with a computationally efficient numerical engine. In this paper, we introduce the philosophy behind COR, explain its user interface and current functionality, including the editing and running of CellML files, highlight lessons learned from user feedback and problems experienced during the development of COR and conclude by exploring future development potential. Sponsors: This study has been supported by a grant from the UK Biotechnology and Biological Sciences Research Council (BB/E024955/1). Keyword: Cell, Model, Cellular, Modeling, Open resource, Microsoft, Environment, Database, Experimentalist, Teacher, Student, Modeler, Computationally, Development,

Proper citation: Cellular Open Resource (RRID:SCR_008022) Copy   

•   Source: SciCrunch Registry

http://web.bioinformatics.cicbiogune.es/AM/AnnotationModules.php

A tool for finding significant combinations of multisource annotations in gene lists.

Proper citation: Annotation-Modules (RRID:SCR_008025) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/Projects/Microbes/

This website includes a list of projects that the Sanger Institute is currently working on or completed. All projects consist of the genomic sequencing of different bacteria. Each description of the bacteria includes its classification, a description, and the types of diseases that the bacteria is likely to cause. The Sanger Institute bacterial sequencing effort is concentrated on pathogens and model organisms. Data is accessible in a number of ways; for each organism there is a BLAST server, allowing users to search the sequences with their own query and retrieve the matching contigs. Sequences can also be downloaded directly by FTP. Data is accessible in a number of ways; for each organism there is a BLAST server, allowing you to search the sequences with your own query and retrieve the matching contigs. Sequences can also be downloaded directly by FTP. The primary sequence viewer and annotation tool, Artemis is available for download. This is a portable Java program which is used extensively within the Microbial Genomes group for the analysis and annotation of sequence data from cosmids to whole genomes. The Artemis Comparison Tool (ACT) is also useful for interactive viewing of the comparisons between large and small sequences.

Proper citation: Bacterial Genomes (RRID:SCR_008141) Copy   

•   Source: SciCrunch Registry