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https://ipfx.readthedocs.io/

Software Python package for computing intrinsic cell features from electrophysiology data. Used to compute intrinsic cell features from intracellular electrophysiology data.

Proper citation: Intrinsic Physiology Feature Extractor (RRID:SCR_028075) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/release/bioc/html/tximeta.html

Software R package for reference sequence checksums for provenance identification in RNA-seq. Performs numerous annotation and metadata gathering tasks on behalf of users during the import of transcript counts and abundance from quantification tools such as salmon. Data are imported as SummarizedExperiment objects with associated GenomicRanges metadata. Correct metadata is added automatically via reference sequence digests, facilitating genomic analyses and assisting in computational reproducibility.

Proper citation: tximeta (RRID:SCR_028005) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages/release/bioc/html/DMRcate.html

Software application for de novo identification and extraction of differentially methylated regions (DMRs) from the human genome using Whole Genome Bisulfite Sequencing (WGBS) and Illumina Infinium Array (450K and EPIC) data. Provides functionality for filtering probes possibly confounded by SNPs and cross-hybridisation. Includes GRanges generation and plotting functions.

Proper citation: DMRcate (RRID:SCR_028007) Copy   

•   Source: SciCrunch Registry

https://jokergoo.github.io/rGREAT/

Software R package for functional enrichment on genomic regions. Functional enrichment analysis directly performed on genomic regions.

Proper citation: rGREAT (RRID:SCR_028008) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/web/packages/compareGroups/

Software R package to create tables displaying results of univariate analyses, stratified or not by categorical variable groupings.

Proper citation: compareGroups (RRID:SCR_027994) Copy   

•   Source: SciCrunch Registry

http://www.edarstudy.eu/

A European collaborative study to develop and validate new biomarkers for Alzheimer's disease. Central in the project is the development of an assay for the measurement of beta amyloid oligomers in cerebrospinal fluid and plasma. In order to validate the assay for beta amyloid oligomers, cerebrospinal fluid and plasma will be repeatedly collected in subjects with Alzheimer's disease, other types of dementia, mild cognitive impairment, and control subjects.

Proper citation: EDAR study: biomarkers for Alzheimer's disease (RRID:SCR_004445) Copy   

•   Source: SciCrunch Registry

http://www.brain-connectivity-toolbox.net

A large selection of complex network measures in Matlab that are increasingly used to characterize structural and functional brain connectivity datasets. Several people have contributed to the toolbox, and if you wish to contribute with a new function or set of functions, please contact Olaf Sporns. All efforts have been made to avoid errors, but users are strongly urged to independently verify the accuracy and suitability of toolbox functions for the chosen application. Please report bugs or substantial improvements.

Proper citation: Brain Connectivity Toolbox (RRID:SCR_004841) Copy   

•   Source: SciCrunch Registry

http://www.nationalbiobanks.fi/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023.To guarantee the top level of expertise in modern genetic and biological analyses, we have built an infrastructure that facilitates the collection of genome-wide information on the genetic background of diseases as well as functional information on the molecules that are critical in the disease process. Furthermore we have established the necessary storage, database and computational resources for the expert analyses of the massive amount of collected biological information. Our scientific expertise, technology platforms and large nationwide sample collections facilitate a highly competitive environment for research and education in molecular medicine of the 21st century. The biobanking wet lab effort is concentrated to KTL/Biomedicum Large scale DNA extraction and storage facility. The facility presently houses DNA from more than 200 000 individuals and is co-ordinated by National Public Health Institute. It is equipped with state of the art bar coding system for sample tracking, an automated Gentra DNA extraction equipment, liquid handling robots, storage facilities, and tailor made data management tools for optimal confidentiality and quality control.

Proper citation: National Biobank of Finland (RRID:SCR_004679) Copy   

•   Source: SciCrunch Registry

http://www.alsconsortium.org/neals_samples.php

Repository of serum, plasma, cerebrospinal fluid (CSF), whole blood, extracted DNA, and urine samples from NEALS and Massachusetts General Hospital Neurology Clinical Trials Unit (NCTU) research studies of amyotrophic lateral sclerosis (ALS). Samples from this repository are available to researchers for the purpose of furthering the understanding of ALS or developing disease biomarkers. Applications will be accepted at any time, but the committee meets bi-monthly to review applications. The application requires a brief description and scientific justification for the use of the samples. Priority will be given to members of NEALS and investigators from sites that participated in the collection of samples. Investigators must provide IRB approval from their institution. Applications may be submitted to: mghneuroclinicaltrialsunit (at) partners.org (please cc: tlincoln (at) partners.org) NEALS collects an administrative fee of $1,000 at the time of application submission to offset processing costs. If an application for samples is denied, 80% of the administrative fee will be returned. The administrative fee is waived for NEALS members. Checks may be made payable to: The Northeast ALS Consortium.

Proper citation: NEALS Sample Repository (RRID:SCR_004271) Copy   

•   Source: SciCrunch Registry

http://www.geenivaramu.ee/en/

The Estonian Biobank is the population-based biobank of the EGCUT. The project is conducted in accordance with the Estonian Genes Research Act and all participants have signed a broad informed consent form (www.biobank.ee and Metspalu 2004, Drug Dev. Res.). As of December 2011, the biobank contains 51,515 participants (gene donors). The database of genotypic, phenotypic, health and genealogical information represents about 5% of Estonia''s adult population, and is the largest cohort ever gathered in Estonia. The age, sex and geographical distribution of this cohort reflect the structure of the adult population in Estonia. The database enables to conduct research in order to find links between genes, environmental factors, lifestyles and complex diseases or other traits. Active use of the biobank has started and although the first users are researchers all over the world with hundreds of different projects currently underway, industry is also interested. At the international level, the EGCUT will join the BBMRI follow-up program (ERIC) and through this channel provide service (biobanking, genotyping, sequencing and data analysis) for the centers in Europe who need it. Currently, the first follow-up study is underway and the molecular information of the cohort will be increased. For example, we have over 12 000 DNA samples analyzed by high density genotyping arrays and over 10 000 plasma samples analyzed by NMR scans, over 1000 individuals with RNA expression arrays, 2000 individuals with clinical laboratory analysis (over 40 tests) and over 60 full genomes are under deep sequencing. The infrastructure of the EGCUT includes a laboratory for DNA genotyping and next generation sequencing all based on Illumina platforms (HiScanSQ, HiSeq2000 and robotics), an IT unit (databases) with required computing power and storage space (1.2PB), data analysis team (bioinformatics and statistical genetics) and last but not least, a patient recruitment unit (health records, lifestyle and environmental information and biological samples ����?����������?? DNA, plasma and WBC from all 51515 gene donors). This is all located on 1000m2 in a brand new laboratory building, Riia str 23, Tartu, Estonia.

Proper citation: Estonian Genome Center (RRID:SCR_004467) Copy   

•   Source: SciCrunch Registry

http://www.oncoreuk.org/

No longer functioning as an independent charity, onCore UK is a national cancer biobanking organization. Our mission is to serve as an action team that informs, coordinates and develops cancer biobanking to enable research towards the discovery and development of new interventions against cancer. We also offer advice to researchers who need to collect and store samples for their own specific projects. Our main strategic objectives are: * To empower research using human biosamples to find new and effective means of preventing, detecting or treating cancer. * To improve access by researchers to the human biosamples they require for their work. * To facilitate an environment in which patients, the public, health professionals, researchers, funders of research, policy makers and regulators can work together to support cancer biobanking and the research it underpins. * To provide practical information, coordination and development for current and future people and organizations involved in cancer biobanking to ensure that they are not unnecessarily hindered in their work. * To provide an accurate and regularly updated picture of the cancer biobanking provision in the UK that will inform future decisions by funders supporting research using donated human biosamples. * To distribute the human biosamples that onCore UK has in its custody. onCore UK conducts its business within the overall scope of the National Cancer Research Institute (NCRI) and for the benefit of cancer research. In the past we have also worked with selected NHS hospitals in different parts of the country to collect biosamples and relevant clinical data donated by cancer patients. These biosamples are stored in a secure repository and researchers can apply to use them. We make anonymized biosamples and data available for scientifically and ethically approved research on a cost-recovery basis. onCore UK works with other cancer biobanks in the UK via the NCRI Confederation of Cancer Biobanks (CCB), and with other biobanks internationally, to improve access for researchers to larger numbers of high quality biosamples, to harmonize how biobanks work and to share expertise for the benefit of all involved.

Proper citation: onCore UK (RRID:SCR_004348) Copy   

•   Source: SciCrunch Registry

http://bbmri-eric.eu

BBMRI is a pan-European and internationally broadly accessible research infrastructure and a network of existing and de novo biobanks and biomolecular resources. The infrastructure will include samples from patients and healthy persons, representing different European populations (with links to epidemiological and health care information), molecular genomic resources and biocomputational tools to optimally exploit this resource for global biomedical research. During the past 3 years BBMRI has grown into a 53-member consortium with over 280 associated organizations (largely biobanks) from over 30 countries, making it the largest research infrastructure project in Europe. During the preparatory phase the concept of a functional pan-European biobank was formulated and has now been presented to Member States of the European Union and for associated states for approval and funding. BBMRI will form an interface between specimens and data (from patients and European populations) and top-level biological and medical research. This can only be achieved through a distributed research infrastructure with operational units in all participating Member States. BBMRI will be implemented under the ERIC (European Research Infrastructure Consortium) legal entity. BBMRI-ERIC foresees headquarters (central coordination) in Graz, Austria, responsible for coordination of the activities of National Nodes established in participating countries. BBMRI is in the process of submitting its application to the European Commission for a legal status under the ERIC regulation, with an expected start date at the end of 2011. Major synergism, gain of statistical power and economy of scale will be achieved by interlinking, standardizing and harmonizing - sometimes even just cross-referencing - a large variety of well-qualified, up-to date, existing and de novo national resources. The network should cover (1) major European biobanks with blood, serum, tissue or other biological samples, (2) molecular methods resource centers for human and model organisms of biomedical relevance, (3) and biocomputing centers to ensure that databases of samples in the repositories are dynamically linked to existing databases and to scientific literature as well as to statistical expertise. Catalog of European Biobanks www.bbmriportal.eu Username: guest / Password: catalogue The catalogue is intended to be used as a reference for scientists seeking information about biological samples and data suitable for their research. The BBMRI catalogue of European Biobanks provides a high-level description of Europe''s biobanks characteristics using a portal solution managing metadata and aggregate data of biobanks. The catalogue can be queried by country, by biobank, by ICD-groups, by specimen types, by specific strengths, by funding and more. A search function is available for all data.

Proper citation: Biobanking and Biomolecular Resources Research Infrastructure (BBMRI) (RRID:SCR_004226) Copy   

•   Source: SciCrunch Registry

http://disco.neuinfo.org

DISCO is an information integration approach designed to facilitate interoperation among Internet resources. It consists of a set of tools and services that allows resource providers who maintain information to share it with automated systems such as NIF. NIF is then able to harvest the information and keep those sets of information up-to-date. How is this accomplished? By using a series of files and/or scripts which are then placed in the root directory of the resource developer''s resource. (NIF can also host the files on its servers and crawl for changes there.) Once the files of the resource providers are in place, and DISCO is notified, the DISCO server can then recognize and consume the information shared, providing machine understandable information to NIF Integrator Servers (also known as Aggregators) about your resource. What can DISCO do for my resource? * Inform search engines about your resource and keep your NIF Registry resource description up-to-date. * Expose your data (semi-structured datasets or fields within your structured database) through NIF''s Data Federation you choose what data will be shared. * Create links from an NCBI database (e.g., PubMed, Protein, Nucleotide, etc.) to your data records in NIF using Entrez LinkOut. * Advertise your terminology or ontological information. * Share your resource''s news with the NIF community., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: DISCO (RRID:SCR_004586) Copy   

•   Source: SciCrunch Registry

http://www.yandell-lab.org/software/maker.html

Software genome annotation pipeline. Portable and easily configurable genome annotation pipeline. Used to allow smaller eukaryotic and prokaryotic genomeprojects to independently annotate their genomes and to create genome databases. MAKER identifies repeats, aligns ESTs and proteins to genome, produces ab-initio gene predictions and automatically synthesizes these data into gene annotations having evidence based quality values.

Proper citation: MAKER (RRID:SCR_005309) Copy   

•   Source: SciCrunch Registry

http://www.sanger.ac.uk/resources/software/alien_hunter/

Alien_hunter is an application for the prediction of putative Horizontal Gene Transfer (HGT) events with the implementation of Interpolated Variable Order Motifs (IVOMs). This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. An IVOM approach exploits compositional biases using variable order motif distributions and captures more reliably the local composition of a sequence compared to fixed-order methods. Optionally the predictions can be parsed into a 2-state 2nd order Hidden Markov Model (HMM), in a change-point detection framework, to optimize the localization of the boundaries of the predicted regions. The predictions (embl format) can be automatically loaded into the freely available Artemis genome viewer.

Proper citation: Alien hunter (RRID:SCR_004575) Copy   

•   Source: SciCrunch Registry

http://www.biomax.us/

Our robust searchable Tissue Bank database at US Biomax contains normal, non-cancerous disease and cancer samples, just a fraction of total paraffin tissue bank. Use advanced search function to define your search. Some of them have H&E images. Our tissue repository, tissue bank has huge paraffin tissue blocks, a large selection of histology tissue section slides of human cancer, normal tissue, rhesus and cynomolgus normal fresh frozen tissue as well as paraffin blocks and slides. It has also normal human organs in paraffin embedded tissue blocks as well as rhesus and cynomolgus monkey normal organ tissues. Snap frozen (fresh frozen) tissue of rhesus/cynomolgus monkey are also available. We also provide tissue array, custom tissue microarray (with samples you provided or from our tissue bank) as well as OEM services. Other products/services available include tissue microarray, paraffin tissue sections, histology services and quantitative telomerase detection kit.

Proper citation: US Biomax (RRID:SCR_004295) Copy   

•   Source: SciCrunch Registry

Issue

https://reich.hms.harvard.edu/software

EIGENSOFT package combines functionality from our population genetics methods (Patterson et al. 2006) and our EIGENSTRAT stratification method (Price et al. 2006). The EIGENSTRAT method uses principal components analysis to explicitly model ancestry differences between cases and controls along continuous axes of variation; the resulting correction is specific to a candidate marker''s variation in frequency across ancestral populations, minimizing spurious associations while maximizing power to detect true associations. The EIGENSOFT package has a built-in plotting script and supports multiple file formats and quantitative phenotypes. Source code, documentation and executables for using EIGENSOFT 3.0 on a Linux platform can be downloaded. New features of EIGENSOFT 3.0 include supporting either 32-bit or 64-bit Linux machines, a utility to merge different data sets, a utility to identify related samples (accounting for population structure), and supporting multiple file formats for EIGENSTRAT stratification correction.

Proper citation: Eigensoft (RRID:SCR_004965) Copy   

•   Source: SciCrunch Registry

http://www.mssm.edu/research/institutes/institute-for-personalized-medicine/biobank

The Mount Sinai Biobank is a large collection of DNA and plasma samples that are stored in a way that protects patients'' privacy while allowing research to be performed on de-identified clinical information from Mount Sinai''s data warehouse system. The Biobank''s goal is to acquire samples from a total of 100,000 donors over a period of several years. Mount Sinai is one of only a handful of places nationwide establishing biobanks on such a large scale. Funded by the Charles R. Bronfman Institute for Personalized Medicine, the Biobank project is a research project that is approved by the Mount Sinai Institutional Review Board and is continuously reviewed. Biobank Facts: * 17947 donors between 18 and 89 years of age have already participated in Biobank. * 194111 aliquots of DNA and * 212005 aliquots of plasma are available for future research.

Proper citation: Mount Sinai Biobank (RRID:SCR_004845) Copy   

•   Source: SciCrunch Registry

https://eyegene.nih.gov

National network of research laboratories for genetic testing of eye disease. They offer testing for affected individuals coupled to registry of clinical information available through patient registry. Large data set for investigators to identify additional genetic risk factors and to explore relationship between genetic disease (genotype) and its clinical manifestation (phenotype).

Proper citation: eyeGENE (RRID:SCR_004523) Copy   

•   Source: SciCrunch Registry

http://ugene.unipro.ru/

A multiplatform open-source software to assist molecular biologists without much expertise in bioinformatics to manage, analyze and visualize their data. UGENE integrates widely used bioinformatics tools within a common user interface. The toolkit supports multiple biological data formats and allows the retrieval of data from remote data sources. It provides visualization modules for biological objects such as annotated genome sequences, Next Generation Sequencing (NGS) assembly data, multiple sequence alignments, phylogenetic trees and 3D structures. Most of the integrated algorithms are tuned for maximum performance by the usage of multithreading and special processor instructions. UGENE includes a visual environment for creating reusable workflows that can be launched on local resources or in a High Performance Computing (HPC) environment. UGENE is written in C++ using the Qt framework. The built-in plugin system and structured UGENE API make it possible to extend the toolkit with new functionality.

Proper citation: Unipro UGENE (RRID:SCR_005579) Copy   

•   Source: SciCrunch Registry