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http://www.ebi.ac.uk/pdbe/

The European resource for the collection, organization and dissemination of data on biological macromolecular structures. In collaboration with the other worldwide Protein Data Bank (wwPDB) partners - the Research Collaboratory for Structural Bioinformatics (RCSB) and BioMagResBank (BMRB) in the USA and the Protein Data Bank of Japan (PDBj) - they work to collate, maintain and provide access to the global repository of macromolecular structure data. The main objectives of the work at PDBe are: * to provide an integrated resource of high-quality macromolecular structures and related data and make it available to the biomedical community via intuitive user interfaces. * to maintain in-house expertise in all the major structure-determination techniques (X-ray, NMR and EM) in order to stay abreast of technical and methodological developments in these fields, and to work with the community on issues of mutual interest (such as data representation, harvesting, formats and standards, or validation of structural data). * to provide high-quality deposition and annotation facilities for structural data as one of the wwPDB deposition sites. Several sophisticated tools are also available for the structural analysis of macromolecules.

Proper citation: PDBe - Protein Data Bank in Europe (RRID:SCR_004312) Copy   

•   Source: SciCrunch Registry

http://www.rhea-db.org/

Manually annotated reaction database where all reaction participants (reactants and products) are linked to the ChEBI database (Chemical Entities of Biological Interest) which provides detailed information about structure, formula and charge. Rhea provides built-in validations that ensure both elemental and charge balance of the reactions. The database has been populated with the reactions found in the Enzyme Commission (EC) list (and in the IntEnz and ENZYME databases), extending it with additional known reactions of biological interest. While the main focus of Rhea is enzyme-catalyzed reactions, other biochemical reactions are also included. Rhea is a manually annotated resource and it provides: stable reaction identifiers for each of its reactions; directionality information if the physiological direction of the reaction is known; the possibility to link several reactions together to form overall reactions; extensive cross-references to other resources including enzyme-catalyzed and other metabolic reactions, such as the EC list (in IntEnz), KEGG, MetaCyc and UniPathway; and chemical substructure and similarity searches on compounds in Rhea.

Proper citation: RHEA (RRID:SCR_004713) Copy   

•   Source: SciCrunch Registry

https://github.com/INCF/csa

Software tool for description of connectivity in small and large scale neuronal network models. It provides operators to form more complex sets of connections from simpler ones and also provides parameterization of such sets. Can be used as component of neuronal network simulators or other tools.

Proper citation: Connection-set algebra (RRID:SCR_017397) Copy   

•   Source: SciCrunch Registry

https://lsbr.niams.nih.gov/bsoft/

Software package and a platform for the processing of electron micrographs in structural biology. Supports different image file formats used in electron microscopy (including MRC, SPIDER, IMAGIC, SUPRIM, and PIF)., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Bsoft (RRID:SCR_016503) Copy   

•   Source: SciCrunch Registry

http://scipion.i2pc.es/

Software framework for image processing to obtain 3D models of macromolecular complexes using Electron Microscopy. Open-source project for integration, reproducibility and validation in 3D electron microscopy. It integrates several software packages to execute workflows combining different software tools, while taking care of formats and conversions. Electron Microscopy (3DEM). waiting for pdf from Joe

Proper citation: SCIPION (RRID:SCR_016738) Copy   

•   Source: SciCrunch Registry

http://www.evocontology.org/site/Main/EvocOntologyDotOrg

THIS RESOURCE IS NO LONGER IN SERVICE, documented May 10, 2017. A pilot effort that has developed a centralized, web-based biospecimen locator that presents biospecimens collected and stored at participating Arizona hospitals and biospecimen banks, which are available for acquisition and use by researchers. Researchers may use this site to browse, search and request biospecimens to use in qualified studies. The development of the ABL was guided by the Arizona Biospecimen Consortium (ABC), a consortium of hospitals and medical centers in the Phoenix area, and is now being piloted by this Consortium under the direction of ABRC. You may browse by type (cells, fluid, molecular, tissue) or disease. Common data elements decided by the ABC Standards Committee, based on data elements on the National Cancer Institute''s (NCI''s) Common Biorepository Model (CBM), are displayed. These describe the minimum set of data elements that the NCI determined were most important for a researcher to see about a biospecimen. The ABL currently does not display information on whether or not clinical data is available to accompany the biospecimens. However, a requester has the ability to solicit clinical data in the request. Once a request is approved, the biospecimen provider will contact the requester to discuss the request (and the requester''s questions) before finalizing the invoice and shipment. The ABL is available to the public to browse. In order to request biospecimens from the ABL, the researcher will be required to submit the requested required information. Upon submission of the information, shipment of the requested biospecimen(s) will be dependent on the scientific and institutional review approval. Account required. Registration is open to everyone., documented September 6, 2016. Set of orthogonal controlled vocabularies that unifies gene expression data by facilitating a link between the genome sequence and expression phenotype information. The system associates labelled target cDNAs for microarray experiments, or cDNA libraries and their associated transcripts with controlled terms in a set of hierarchical vocabularies. eVOC consists of four orthogonal controlled vocabularies suitable for describing the domains of human gene expression data including Anatomical System, Cell Type, Pathology and Developmental Stage. The four core eVOC ontologies provide an appropriate set of detailed human terms that describe the sample source of human experimental material such as cDNA and SAGE libraries. These expression terms are linked to libraries and transcripts allowing the assessment of tissue expression profiles, differential gene expression levels and the physical distribution of expression across the genome. Analysis is currently possible using EST and SAGE data, with microarray data being incorporated. The eVOC data is increasingly being accepted as a standard for describing gene expression and eVOC ontologies are integrated with the Ensembl EnsMart database, the Alternate Transcript Diversity Project and the UniProt Knowledgebase. Several groups are currently working to provide shared development of this resource such that it is of maximum use in unifying transcript expression information.

Proper citation: eVOC (RRID:SCR_010704) Copy   

•   Source: SciCrunch Registry

https://github.com/ledancs/hFigures

A Javascript library that aims to deliver a starting point for interactive health data visualization. Examples and demos are available on the site. hFigures was built with d3.js and a copy of the library is included in this repository. All rights and license terms apply to the d3.js library accordingly.

Proper citation: hFigures (RRID:SCR_014201) Copy   

•   Source: SciCrunch Registry

http://degradome.uniovi.es

A database of human, chimpanzee, mouse, and rat proteases and protease inhibitors, as well as as the growing number of hereditary diseases caused by mutations in protease genes. Analysis of the human and mouse genomes has allowed us to annotate 581 human, 580 chimpanzee, 667 mouse, and 655 rat protease genes. Proteases are classified in five different classes according to their mechanism of catalysis. Proteases are a diverse and important group of enzymes representing >2% of the human, chimpanzee, mouse and rat genomes. This group of enzymes is implicated in numerous physiological processes. The importance of proteases is illustrated by the existence of 99 different hereditary diseases due to mutations in protease genes. Furthermore, proteases have been implicated in multiple human pathologies, including vascular diseases, rheumatoid arthritis, neurodegenerative processes, and cancer. During the last ten years, our laboratory has identified and characterized more than 60 human protease genes. Due to the importance of proteolytic enzymes in human physiology and pathology, we have recently introduced the concept of Degradome, as the complete repertoire of proteases expressed by a tissue or organism. Thanks to the recent completion of the human, chimpanzee, mouse, and rat genome sequencing projects, we were able to analyze and compare for the first time the complete protease repertoire in those mammalian organisms, as well as the complement of protease inhibitor genes. This webpage also contains the Supplementary Material of Human and mouse proteases: a comparative genomic approach Nat Rev Genet (2003) 4: 544-558, Genome sequence of the brown Norway rat yields insights into mammalian evolution Nature (2004) 428: 493-521, A genomic analysis of rat proteases and protease inhibitors Genome Res. (2004) 14: 609-622, and Comparative genomic analysis of human and chimpanzee proteases Genomics (2005) 86: 638-647.

Proper citation: Mammalian Degradome Database (RRID:SCR_007624) Copy   

•   Source: SciCrunch Registry

http://www.glycosciences.de/glycocd/

Manually curated, comprehensive repository of clusters of differentiation (CDs) which are a) defined as distinct oligosaccharide sequences as part of either glycoproteins and/or glycosphingolipids and b) defined as proteins which have carbohydrate recognition sites (CRDs) or as carbohydrate binding lectins. The data base is generated by exhaustive search of literature and other online data banks related to carbohydrates and proteins. This data bank is the beginning of an effort to provide concise, relevant information of carbohydrate-related CDs in a user- friendly manner. For users convenience the data bank under menu browse of GlycoCD is arranged in two section namely carbohydrate recognition CDs (CRD CD) and glycan CD. The carbohydrate recognition CD part is the collection of proteins which recognize glycan structures by means of the CRDs. Glycan CD is the part in which CDs are summarized which characterize specific oligosaccharide structures. The GlycoCD databank has been developed with the aim to assist the immunologist, cell biologist as well as the clinician who wants to keep up with the present knowledge in this field of glycobiology.

Proper citation: Glyco-CD (RRID:SCR_001574) Copy   

•   Source: SciCrunch Registry

http://simbioms.org/

SIMBioMS (System for Information Management in BioMedical Studies) is a multi-module solution for data management in biomedical studies. Any research concerning human samples and/or utilizing high-throughput technologies yields such amount of information that conventional data storage solution might not be sufficient. We offer here three software modules: * Sample Information Management System (SIMS), * Assay Information Management System (AIMS) * Sample avAILability system (SAIL) * Emanta Administration tool (Emanta) All three software modules were developed as a part of the integrated EU project MolPAGE (Molecular Phenotyping to Accelerate Genomic Epidemiology) and the collaborative research project ENGAGE (European Network of Genomic and Genetic Epidemiology). SIMS and AIMS can work either as united system or as two completely independent components. In turn, SAIL is an independent web-based system for indexing of phenotypes availability in different cohorts and collections. All systems are packaged in such a way that they can easily be installed either as local (e.g. on a laptop) or as centralized databases (to be used by a group of people). SIMS and AIMS benefit from customizable interface, editable vocabularies and a choice of options for tackling data confidentiality issues. The systems provides a user with efficient means of control over data exchange process and at the same time helps to format the metadata in compliance with the standards accepted in functional genomics. Since SIMBioMS is an open source project, source files can be downloaded and changed by the user if needed.

Proper citation: SIMBioMS (RRID:SCR_005745) Copy   

•   Source: SciCrunch Registry

http://ki.se/en/meb/twingene-and-genomeeutwin

In collaboration with GenomeEUtwin, the TwinGene project investigates the importance of quantitative trait loci and environmental factors for cardiovascular disease. It is well known that genetic factors are of considerable importance for some familial lipid syndromes and that Type A Behavior pattern and increased lipid levels infer increased risk for cardiovascular disease. It is furthermore known that genetic factors are of importance levels of blood lipid biomarkers. The interplay of genetic and environmental effects for these risk factors in a normal population is less well understood and virtually unknown for the elderly. In the TwinGene project twins born before 1958 are contacted to participate. Health and medication data are collected from self-reported questionnaires, and blood sampling material is mailed to the subject who then contacts a local health care center for blood sampling and a health check-up. In the simple health check-up, height, weight, circumference of waist and hip, and blood pressure are measured. Blood is sampled for DNA extraction, serum collection and clinical chemistry tests of C-reactive protein, total cholesterol, triglycerides, HDL and LDL cholesterol, apolipo��protein A1 and B, glucose and HbA1C. The TwinGene cohort contains more than 10000 of the expected final number of 16000 individuals. Molecular genetic techniques are being used to identify Quantitative Trait Loci (QTLs) for cardiovascular disease and biomarkers in the TwinGene participants. Genome-wide linkage and association studies are ongoing. DZ twins have been genome-scanned with 1000 STS markers and a subset of 300 MZ twins have been genome-scanned with Illumina 317K SNP platform. Association of positional candidate SNPs arising from these genomscans are planned. The TwinGene project is associated with the large European collaboration denoted GenomEUtwin (www.genomeutwin.org, see below) which since 2002 has aimed at gathering genetic data on twins in Europe and setting up the infrastructure needed to enable pooling of data and joint analyses. It has been the funding source for obtaining the genome scan data. Types of samples: * EDTA whole blood * DNA * Serum Number of sample donors: 12 044 (sample collection completed)

Proper citation: KI Biobank - TwinGene (RRID:SCR_006006) Copy   

•   Source: SciCrunch Registry

http://hcsquared.eu/home

HC2 is an EU funded project that aims to promote, support and help define future lines of research in Human Computer Confluence (HCC). HCC is the study of the intersection of HCI, Cognitive Neuroscience, VR/AR, Presence, Pervasive Computing and how they can enable new forms of sensing, perception, interaction and understanding. In a sense it is the study of the disappearing interface. HCC, Human-Computer Confluence, is an ambitious research program studying how the emerging symbiotic relation between humans and computing devices can enable radically new forms of sensing, perception, interaction, and understanding. The horizontal character of HCC makes it a fascinating and fertile interdisciplinary field, but it can also compromise its growth, with researchers scattered across disciplines and groups worldwide. To address this we are building a community of HCC researchers. There are lots of ways you can join in. Add your name to the HCC Players Map, take advantage of our Exchange Program to work with colleagues at your favorite lab, sign up for our Summer School or just follow us on Twitter and LinkedIn to see what''s happening. In order to foster interdisciplinary research and promote HCC research we have set up an Exchange Program. Students that wish to apply for financial support from our Exchange Program should follow the steps provided. The Exchange Program is open to all graduate students (Masters and PhD). A maximum of 500 Euro support will be provided per student.

Proper citation: HC2: Human-Computer Confluence (RRID:SCR_005549) Copy   

•   Source: SciCrunch Registry

http://www.chernobyltissuebank.com/

The CTB (Chernobyl Tissue Bank) is an international cooperation that collects, stores and disseminates biological samples from tumors and normal tissues from patients for whom the aetiology of their disease is known - exposure to radioiodine in childhood following the accident at the Chernobyl power plant. The main objective of this project is to provide a research resource for both ongoing and future studies of the health consequences of the Chernobyl accident. It seeks to maximize the amount of information obtained from small pieces of tumor by providing multiple aliquots of RNA and DNA extracted from well documented pathological specimens to a number of researchers world-wide and to conserve this valuable material for future generations of scientists. It exists to promote collaborative, rather than competitive, research on a limited biological resource. Tissue is collected to an approved standard operating procedure (SOP) and is snap frozen; the presence or absence of tumor is verified by frozen section. A representative paraffin block is also obtained for each case. Where appropriate, we also collect fresh and paraffin-embedded tissue from loco-regional metastases. Currently we do not issue tissue but provide extracted nucleic acid, paraffin sections and sections from tissue microarrays from this material. The project is coordinated from Imperial College, London and works with Institutes in the Russian Federation (the Medical Radiological Research Centre in Obninsk) and Ukraine (the Institute of Endocrinology and Metabolism in Kiev) to support local scientists and clinicians to manage and run a tissue bank for those patients who have developed thyroid tumors following exposure to radiation from the Chernobyl accident. Belarus was also initially included in the project, but is currently suspended for political reasons.

Proper citation: Chernobyl Tissue Bank (RRID:SCR_010662) Copy   

•   Source: SciCrunch Registry

http://abacas.sourceforge.net

Software that contiguates (align, order, orientate), visualizes and designs primers to close gaps on shotgun assembled contigs based on a reference sequence. ABACAS finds alignment positions and identifies syntenies of assembled contigs against the reference, then generates a pseudomolecule taking overlapping contigs and gaps into account.

Proper citation: ABACAS (RRID:SCR_015852) Copy   

•   Source: SciCrunch Registry

https://CRAN.R-project.org/package=APIS

Software R package to assign offspring to their parents without any prior information other than offspring and parental genotypes, and user-defined, acceptable error rate among assigned offspring. Auto-adaptive parentage inference software that tolerates missing parents.

Proper citation: APIS (RRID:SCR_025445) Copy   

•   Source: SciCrunch Registry

https://github.com/farkkilab/tribus

Software tool for cell type based analysis of multiplexed imaging data. Interactive knowledge-based classifier for multiplexed images and proteomic datasets that avoids hard-set thresholds and manual labeling. Recovers fine-grained cell types, matching the gold standard annotations by human experts, can target ambiguous populations and discover phenotypically distinct cell subtypes.

Proper citation: TRIBUS (RRID:SCR_027367) Copy   

•   Source: SciCrunch Registry