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http://www.tubafrost.org/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 9, 2023. In this web site you will find the central European database of OECI-TuBaFrost collecting the information of biobanks or in the project support environment on human material; i.e., frozen tumor tissue specimens, pathology blocks, blood samples in different forms, cell lines, Tissue Micro Arrays, etc. Our goal is by centralizing the tumor tissues information to facilitate the search of doctors / researchers for tumor materials, which they need for their cancer research there with facilitating cancer research. OECI members only can participate in the OECI-TuBaFrost exchange platform, or those introduced by an OECI member. We are a group of pathology and research departments as well as bio-bankers in clinical based biobanking based in comprehensive cancer centers or hospitals with a competence in comprehensive cancer care across Europe. Each participating institute is involved in cancer research resulting in innovative procedures, new drugs, improved diagnosis and new insights in disease development. The overall result is better care and treatment for cancer patients. To maximize the scientific value of the human tissue samples, information about the clinical status of the patient in combination with the quality and type of samples is very important. A TuBaFrost electronic database will securely store all this information. Within the closed project supporting environments, the data collected will include: * Diagnosis - identification of the type of cancer * Type of tissue collected - the origin, i.e. breast, skin, colorectal * Quality of tissue collected - collection and storage details The tissue is stored in the hospital where the donor was diagnosed/treated. It stays there until it is used or sent to another hospital or research center within the TuBaFrost group. The electronic database will track samples throughout the network. The tissue is not sold. The exchange of tissue to other hospitals is regulated by a contract, which uses the national regulations of the country supplying the tissue. Tissue samples within the TuBaFrost collection will only be used for research, which has been approved by ethics committees. This ensures that the tissue is only used for the best quality research and only for the specific reasons given to the ethics committee.

Proper citation: OECI - Tubafrost: The European Human Frozen Tissue Bank (RRID:SCR_004280) Copy   

•   Source: SciCrunch Registry

http://www.ihop-net.org/UniPub/iHOP/

Information system that provides a network of concurring genes and proteins extends through the scientific literature touching on phenotypes, pathologies and gene function. It provides this network as a natural way of accessing millions of PubMed abstracts. By using genes and proteins as hyperlinks between sentences and abstracts, the information in PubMed can be converted into one navigable resource, bringing all advantages of the internet to scientific literature research. Moreover, this literature network can be superimposed on experimental interaction data (e.g., yeast-two hybrid data from Drosophila melanogaster and Caenorhabditis elegans) to make possible a simultaneous analysis of new and existing knowledge. The network contains half a million sentences and 30,000 different genes from humans, mice, D. melanogaster, C. elegans, zebrafish, Arabidopsis thaliana, yeast and Escherichia coli.

Proper citation: Information Hyperlinked Over Proteins (RRID:SCR_004829) Copy   

•   Source: SciCrunch Registry

http://www.erasmusmc.nl/pathologie/clinicalpathology/tissuebank/161255/?lang=en

The Erasmus MC Virtual Tissue Bank is embedded in the department of Pathology. The collection is meant for medical research purposes only. This concerns a typical clinical based pathology biobank. Tissue samples left over from surgical resection specimen are stored under liquid nitrogen and can be requested by Erasmus MC scientists for medical scientific experiments. An application has been developed to enable scientists to search the collection on-line and request tissue samples over the Erasmus MC Intranet. Every request shall be judged according to procedures determined by the Erasmus MC Tissue Bank. A growing need is anticipated for large collections of well-diagnosed fresh frozen tumor tissue and, if available, corresponding pre-malignant and normal tissue samples. Scientific research on patient residual material has to comply with strict rules and regulations. Equipment The Erasmus MC Tissue bank manages the PALM microdissection laser for the center for Biomics, which is available through the center for Biomics ONLY after having followed an introduction course. Additionally, a complete TMA (Tissue Micro Array) platform, fully funded by the Josephine Nefkens Stichting, consisting of a Beecher Automated Tissue Arrayer ATA 27 and a Virtual Microscope or Nanozoomer from Hamamatsu and Medical Solutions with TMA analyses software strongly supports translational research on tissue samples. Complete histologic Images from the Virtual Microscope are available within the Erasmus MC Intranet or available on the Internet either by overview or a direct example.

Proper citation: Erasmus MC Tissue Bank (RRID:SCR_004945) Copy   

•   Source: SciCrunch Registry

http://tomcat.esat.kuleuven.be/txtgate/

TXTGate is a literature index database and is part of an experimental platform to evaluate (combinations of) information extraction and indexing from a variety of biological annotation databases. It is designed towards the summarization and analysis of groups of genes based on text. By means of tailored vocabularies, selected textual fields and MedLine abstracts of LocusLink and SGD are indexed. Subclustering and links to external resources allow for an in-depth analysis of the resulting term profiles. You need to be registered in order to use the TXTGate application. Platform: Online tool

Proper citation: TXTGate (RRID:SCR_005812) Copy   

•   Source: SciCrunch Registry

http://athina.biol.uoa.gr/PRED-CLASS/

A system of cascading neural networks that classifies any protein, given its amino acid sequence alone, into one of four possible classes: membrane, globular, fibrous, mixed.

Proper citation: PRED-CLASS (RRID:SCR_006216) Copy   

•   Source: SciCrunch Registry

https://github.com/DiltheyLab/HLA-LA

Software implements new graph alignment model for human leukocyte antigen, based on projection of linear alignments onto variation graph. Enables accurate HLA type inference from whole genome and whole exome Illumina data; from long-read Oxford Nanopore and Pacific Biosciences data and from genome assemblies.

Proper citation: HLA-LA (RRID:SCR_022283) Copy   

•   Source: SciCrunch Registry

https://biofam.github.io/MOFA2/

Software framework for unsupervised integration of multi-omics data sets. Used for discovering principal sources of variation in multi omics data sets.

Proper citation: MOFA (RRID:SCR_022992) Copy   

•   Source: SciCrunch Registry

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

Public archive providing a comprehensive record of the world''''s nucleotide sequencing information, covering raw sequencing data, sequence assembly information and functional annotation. All submitted data, once public, will be exchanged with the NCBI and DDBJ as part of the INSDC data exchange agreement. The European Nucleotide Archive (ENA) captures and presents information relating to experimental workflows that are based around nucleotide sequencing. A typical workflow includes the isolation and preparation of material for sequencing, a run of a sequencing machine in which sequencing data are produced and a subsequent bioinformatic analysis pipeline. ENA records this information in a data model that covers input information (sample, experimental setup, machine configuration), output machine data (sequence traces, reads and quality scores) and interpreted information (assembly, mapping, functional annotation). Data arrive at ENA from a variety of sources including submissions of raw data, assembled sequences and annotation from small-scale sequencing efforts, data provision from the major European sequencing centers and routine and comprehensive exchange with their partners in the International Nucleotide Sequence Database Collaboration (INSDC). Provision of nucleotide sequence data to ENA or its INSDC partners has become a central and mandatory step in the dissemination of research findings to the scientific community. ENA works with publishers of scientific literature and funding bodies to ensure compliance with these principles and to provide optimal submission systems and data access tools that work seamlessly with the published literature. ENA is made up of a number of distinct databases that includes the EMBL Nucleotide Sequence Database (Embl-Bank), the newly established Sequence Read Archive (SRA) and the Trace Archive. The main tool for downloading ENA data is the ENA Browser, which is available through REST URLs for easy programmatic use. All ENA data are available through the ENA Browser. Note: EMBL Nucleotide Sequence Database (EMBL-Bank) is entirely included within this resource.

Proper citation: European Nucleotide Archive (ENA) (RRID:SCR_006515) Copy   

•   Source: SciCrunch Registry

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

Open source database system and analysis tools for molecular interaction data. All interactions are derived from literature curation or direct user submissions. Direct user submissions of molecular interaction data are encouraged, which may be deposited prior to publication in a peer-reviewed journal. The IntAct Database contains (Jun. 2014): * 447368 Interactions * 33021 experiments * 12698 publications * 82745 Interactors IntAct provides a two-tiered view of the interaction data. The search interface allows the user to iteratively develop complex queries, exploiting the detailed annotation with hierarchical controlled vocabularies. Results are provided at any stage in a simplified, tabular view. Specialized views then allows "zooming in" on the full annotation of interactions, interactors and their properties. IntAct source code and data are freely available.

Proper citation: IntAct (RRID:SCR_006944) Copy   

•   Source: SciCrunch Registry

http://www.imgt.org/IMGTindex/IMGTgene-db.html

IMGT/GENE-DB is the comprehensive IMGT genome database for immunoglobulin (IG) and T cell receptor (TR) genes from human and mouse, and, in development, from other vertebrates. IMGT/GENE-DB is the international reference for the IG and TR gene nomenclature and works in close collaboration with the HUGO Nomenclature Committee, Mouse Genome Database and genome committees for other species. IMGT/GENE-DB allows a search of IG and TR genes by locus, group and subgroup, which are CLASSIFICATION concepts of IMGT-ONTOLOGY. Short cuts allow the retrieval gene information by gene name or clone name. Direct links with configurable URL give access to information usable by humans or programs. An IMGT/GENE-DB entry displays accurate gene data related to genome (gene localization), allelic polymorphisms (number of alleles, IMGT reference sequences, functionality, etc.) gene expression (known cDNAs), proteins and structures (Protein displays, IMGT Colliers de Perles). It provides internal links to the IMGT sequence databases and to the IMGT Repertoire Web resources, and external links to genome and generalist sequence databases. IMGT/GENE-DB manages the IMGT reference directory used by the IMGT tools for IG and TR gene and allele comparison and assignment, and by the IMGT databases for gene data annotation., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: IMGT/GENE-DB (RRID:SCR_006964) 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

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

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