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https://commonfund.nih.gov/hubmap

Project to facilitate research on single cells within tissues by supporting data generation and technology development to explore the relationship between cellular organization and function, as well as variability in normal tissue organization at the level of individual cells. Framework for functional mapping the human body with cellular resolution.Designed to support diverse spatial and non-spatial omics and imaging data types and to integrate with a wide range of analysis workflows.

Proper citation: The Human BioMolecular Atlas Program (RRID:SCR_016922) Copy   

•   Source: SciCrunch Registry

http://toc.lbg.ac.at/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on July 31,2025. The projected cluster includes the LBIs for Applied Cancer Research, Clinical Oncology and Photodynamic Therapy, Gynecology and Gynecologic Oncology, Stem Cell Transplantation and Surgical Oncology. The aim of the projected cluster Translational Oncology is the cooperative investigation of genetic and molecular biological characteristics of the tumor cells involved in minimal residual disease (MRD) in vitro and translation of the experimental and diagnostic results into the clinical practice involving therapeutic modalities with the newest generation of antitumoral drugs. Minimal residual disease is the designation for the occurrence of a low number of tumor cells remaining clinically undetected following curative therapy that give rise to tumor relapses. MRD is a central question in cancer therapy, since a major subpopulation of patients which underwent curative resection and therapy ultimately relapse and would have received more aggressive adjuvant therapy, provided that residual disease had been clearly proven. Otherwise low-risk patients would have not been treated aggressively in an adjuvant setting. MRD can be detected by methods in bone marrow or by extremely sensitive PCR (polymerase-chain-reaction)-based methods in peripheral blood. PCR-based methods allow for the characterization of tumor-specific gene expression in circulating tumor cells and thereby provide additional information in regard to malignity of cells and prognosis. The different participating institutions have extensive experience in patient care, organization of clinical studies and laboratory investigation. In particular, expert knowledge in stem cell transplantation and histological detection of MRD, multicentric clinical testing of new anticancer drugs, specialized treatment of various selected tumor entities such as neuroendocrine tumors, gene expression analysis of circulating tumor cells and tumor signatures, and in vitro characterization of chemosensitivity as well as tumor cell biology have been acquired at the individual LBIs in the past and are complementary to each other to be combined in a larger cluster structure. The detection of circulating tumor cells will be supported by ongoing EU (OVCAD OVarian CAncer Diagnosis) and GenAU projects aiming at identification of ovarian cancer cells in the blood. The assessment of methylated DNA sequences (suppressor genes) in peripheral blood as an indicator of MRD can be performed with the help of OncoLab Diagnostics GmbH. Cooperative action in this cluster, using a common tumor bank/clinical data collection and the combined clinical and experimental efforts are the base for the execution of the presented MRD project.

Proper citation: Ludwig Boltzmann Cluster Translationale Onkologie (RRID:SCR_000020) Copy   

•   Source: SciCrunch Registry

http://www.epilepsygenetics.eu/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16,2023. Group of clinical care and epilepsy research centers who are committed to improving the lives of people with epilepsy through an understanding of the genetics of epilepsy. The consoritum was in an effort to speed discovery to epilepsy genetics by pooling the resources of several research centres., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: EPIGEN (RRID:SCR_000093) Copy   

•   Source: SciCrunch Registry

https://trialweb.dcri.duke.edu/tads/index.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 16,2023. Multi-site clinical research study examining the short- and long-term effectiveness of an antidepressant medication and psychotherapy alone and in combination for treating depression in adolescents ages 12 to 17. For teens treated in TADS, the trial is designed to provide best-practice practical care for depression.

Proper citation: TADS - Treatment for Adolescents with Depression Study (RRID:SCR_000037) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/data/annotation/html/RmiR.Hs.miRNA.html

Software package for various databases of microRNA Targets.

Proper citation: RmiR.Hs.miRNA (RRID:SCR_000101) Copy   

•   Source: SciCrunch Registry

https://kpmp.org

Project to ethically obtain and evaluate human kidney biopsies from participants with Acute Kidney Injury (AKI) or Chronic Kidney Disease (CKD), create a kidney tissue atlas, define disease subgroups, and identify critical cells, pathways, and targets for novel therapies. Used to develop the next generation of software tools to visualize and understand the various components of kidney diseases and to optimize data collection. Multi site collaboration comprised of patients, clinicians, and investigators from across the United States.

Proper citation: Kidney Precision Medicine Project (RRID:SCR_016920) Copy   

•   Source: SciCrunch Registry

https://github.com/Frederik-D-Weber/cosleep

Software Python tool for sleep EEG analysis. Used for Closed and Open loop in Slow Ocillations, Sleep Stimulation in Auditory or Recording in full PSG using OpenBCI Cyton.

Proper citation: COsleep (RRID:SCR_017053) Copy   

•   Source: SciCrunch Registry

https://www.synapse.org/#!Synapse:syn11459638

Dockerized environment for winning algorithm in 2017 Multiple Myeloma DREAM Challenge, Sub-Challenge 3.

Proper citation: Multiple Myeloma survival predictor (RRID:SCR_017651) Copy   

•   Source: SciCrunch Registry

https://github.com/AndreMacedo88/VEnCode

Software tool to perform intersectional genetics-related operations to find VEnCodes using databases provided by FANTOM5 consortium, namely CAGE enhancer and transcription start site (TSS) databases.

Proper citation: VEnCode (RRID:SCR_018024) Copy   

•   Source: SciCrunch Registry

http://crispr.dbcls.jp/

Software for designing CRISPR/Cas guide RNA with reduced off target sites. Used for rational design of CRISPR/Cas target. Web server for selecting rational CRISPR/Cas targets from input sequence. Server currently incorporates genomic sequences of human, mouse, rat, marmoset, pig, chicken, frog, zebrafish, Ciona, fruit fly, silkworm, Caenorhabditis elegans, Arabidopsis, rice, Sorghum and budding yeast.

Proper citation: CRISPRdirect (RRID:SCR_018186) Copy   

•   Source: SciCrunch Registry

http://circadb.hogeneschlab.org/

Database of mammalian circadian gene expression profiles. Works with link outs to Wikipedia, HomoloGene, Refseq, etc.. Open source database of circadian transcriptional profiles from time course expression experiments from mice and humans.

Proper citation: CircaDB (RRID:SCR_018078) Copy   

•   Source: SciCrunch Registry

http://bigg.ucsd.edu/

A knowledgebase of Biochemically, Genetically and Genomically structured genome-scale metabolic network reconstructions. BiGG integrates several published genome-scale metabolic networks into one resource with standard nomenclature which allows components to be compared across different organisms. BiGG can be used to browse model content, visualize metabolic pathway maps, and export SBML files of the models for further analysis by external software packages. Users may follow links from BiGG to several external databases to obtain additional information on genes, proteins, reactions, metabolites and citations of interest.

Proper citation: BiGG Database (RRID:SCR_005809) Copy   

•   Source: SciCrunch Registry

http://the_brain.bwh.harvard.edu/uniprobe/

Database that hosts experimental data from universal protein binding microarray (PBM) experiments (Berger et al., 2006) and their accompanying statistical analyses from prokaryotic and eukaryotic organisms, malarial parasites, yeast, worms, mouse, and human. It provides a centralized resource for accessing comprehensive data on the preferences of proteins for all possible sequence variants ("words") of length k ("k-mers"), as well as position weight matrix (PWM) and graphical sequence logo representations of the k-mer data. The database's web tools include a text-based search, a function for assessing motif similarity between user-entered data and database PWMs, and a function for locating putative binding sites along user-entered nucleotide sequences.

Proper citation: UniPROBE (RRID:SCR_005803) Copy   

•   Source: SciCrunch Registry

http://edwardslab.bmcb.georgetown.edu/downloads/

The Peptide Sequence Database contains putative peptide sequences from human, mouse, rat, and zebrafish. Compressed to eliminate redundancy, these are about 40 fold smaller than a brute force enumeration. Current and old releases are available for download. Each species'' peptide sequence database comprises peptide sequence data from releveant species specific UniGene and IPI clusters, plus all sequences from their consituent EST, mRNA and protein sequence databases, namely RefSeq proteins and mRNAs, UniProt''s SwissProt and TrEMBL, GenBank mRNA, ESTs, and high-throughput cDNAs, HInv-DB, VEGA, EMBL, IPI protein sequences, plus the enumeration of all combinations of UniProt sequence variants, Met loss PTM, and signal peptide cleavages. The README file contains some information about the non amino-acid symbols O (digest site corresponding to a protein N- or C-terminus) and J (no digest sequence join) used in these peptide sequence databases and information about how to configure various search engines to use them. Some search engines handle (very) long sequences badly and in some cases must be patched to use these peptide sequence databases. All search engines supported by the PepArML meta-search engine can (or can be patched to) successfully search these peptide sequence databases.

Proper citation: Peptide Sequence Database (RRID:SCR_005764) Copy   

•   Source: SciCrunch Registry

http://www.snpedia.com/index.php/SNPedia

Wiki investigating human genetics including information about the effects of variations in DNA, citing peer-reviewed scientific publications. It is used by Promethease to analyze and help explain your DNA. It is based on a wiki model in order to foster communication about genetic variation and to allow interested community members to help it evolve to become ever more relevant. As the cost of genotyping (and especially of fully determining your own genomic sequence) continues to drop, we''''ll all want to know more - a lot more - about the meaning of these DNA variations and SNPedia will be here to help. SNPedia has been launched to help realize the potential of the Human Genome Project to connect to our daily lives and well-being. For more information see the Wikipedia page, http://en.wikipedia.org/wiki/SNPedia * Download URL: http://www.SNPedia.com/index.php/Bulk * Web Service URL: http://bots.SNPedia.com/api.php

Proper citation: SNPedia (RRID:SCR_006125) Copy   

•   Source: SciCrunch Registry

https://www.facebase.org/node/252

THIS RESOURCE IS NO LONGER IN SERVICE,documented on January,18, 2022. FaceBase Biorepository is now collecting biological samples from people with cleft lip/palate and their family members. Information for Prospective Cases: Clefts of the lip and/or palate can be caused by a wide range of genetic, environmental and other factors. The FaceBase Biorepository will serve as a common source of both biological samples and information that can be made available to investigators trying to determine the underlying cause of these common birth defects. Genetic studies, in particular, will benefit from both family history information and having samples from affected individuals as well as their family members. DNA is the information containing molecules found in all the cells of our body and can be easily obtained from material such as blood or saliva samples. As part of the FaceBase Biorepository, we are requesting families to submit biological samples from specific family members as well as information from other family members that might be affected with either the same condition or a similar condition. The medical and family history information that is collected includes other relevant information such as exposure to possible environmental causes during pregnancy. The biorepository is managed by Nichole Nidey, a research study coordinator, and Jeff Murray, a pediatric clinical geneticist and researcher. They are available to speak with family members regarding questions they may have, including providing information about the biorepository and making arrangements for the collection of samples for those who wish to participate. All participation is voluntary. Your name or other personally identifiable information (name, address, etc) will be removed before information is placed in the biorepository. Summary data to show how the database itself has been used overall as well as updates on whether specific findings might have been made using this database will be available on the FaceBase website at www.facebase.org. A newsletter containing this information will also be given to families and referring clinicians so that they may discuss the specifics with the families if there appears to be information that might be relevant in a particular case. Families will also need to sign a consent form that has been approved by the Institutional Review Board at the University of Iowa. Also, any submitted samples or data can also be removed from the database at any time should the family no longer wish to participate. Investigators interested in requesting DNA samples or for more information, please contact cleftresearch (at) uiowa.edu, Nichole Nidey, nichole-nidey (at) uiowa.edu or (319) 353-4365, or Jeff Murray, jeff-murray (at) uiowa.edu.

Proper citation: FaceBase Biorepository (RRID:SCR_006001) Copy   

•   Source: SciCrunch Registry

http://www.dartmouth.edu/~rswenson/Atlas/

On line labeled atlas of the human brain developed by Dr. Rand Swenson of Dartmouth Medical School. It includes gross anatomical and MRI-generated slices (Axial T1-weighted MRI and Coronal T2 MRI weighted, along with Magnetic resonance arteriogram (MRA) and Magnetic resonance venogram (MRV)images. Labels may be turned on and off. A companion on-line textbook is also available. The site says it is still under construction, although the copyright is 2009. * Atlas of Gross Brain Topography * Atlas of the Brain Stem in Cross Section * Atlas of the Brain in Axial Slices * Atlas of the Brain in Coronal Slices * Atlas of the Head in Axial Slices * Axial T1-weighted MRI * Axial T2-weighted MRI * Coronal T1 MRI * Coronal T2 MRI * Magnetic resonance arteriogram (MRA) * Magnetic resonance venogram (MRV)

Proper citation: Atlas of the Brain (RRID:SCR_005967) Copy   

•   Source: SciCrunch Registry

http://202.120.189.88/drvis/

Dr.VIS collects and locates human disease-related viral integration sites. So far, about 600 sites covering 5 virus organisms and 11 human diseases are available. Integration sites in Dr.VIS are located against chromosome, cytoband, gene and refseq position as specific as possible. Viral-cellular junction sequences are extracted from papers and nucleotide databases, and linked to corresponding integration sites Graphic views summarizing distribution of viral integration sites are generated according to chromosome maps. Dr.VIS is built with a hope to facilitate research of human diseases and viruses. Dr.VIS provides curated knowledge of integration sites from chromosome region narrow to genomic position, as well as junction sequences if available. Dr.VIS is an open resource for free.

Proper citation: Dr.VIS - Human Disease-Related Viral Integration Sites (RRID:SCR_005965) Copy   

•   Source: SciCrunch Registry

https://www.clinicaltrialsregister.eu

Database of European clinical trials containing information on interventional clinical trials on medicines. The information available dates from 1 May 2004 when national medicine regulatory authorities began populating the EudraCT database, the application that is used by national medicine regulatory authorities to enter clinical trial data. The EU Clinical Trials Register website launched on 22 March 2011 enables users to search for information which has been included in the EudraCT database. Users are able to: * view the description of a phase II-IV adult clinical trial where the investigator sites are in European Union member states and the European Economic Area; * view the description of any pediatric clinical trial with investigator sites in the European Union and any trials which form part of a pediatric investigation plan (PIP) including those where the investigator sites are outside the European Union. * download up to 20 results (per request) in a text file (.txt). The details in the clinical trial description include: * the design of the trial; * the sponsor; * the investigational medicine (trade name or active substance identification); * the therapeutic areas; * the status (authorized, ongoing, complete).

Proper citation: EU Clinical Trials Register (RRID:SCR_005956) Copy   

•   Source: SciCrunch Registry

https://www.facebase.org/facial_norms/

Database of high-quality craniofacial anthropometric normative data for the research and clinical community based on digital stereophotogrammetry. Unlike traditional craniofacial normative datasets that are limited to measures obtained with handheld calipers and tape measurers, the anthropometric data provided here are based on digital stereophotogrammetry, a method of 3D surface imaging ideally suited for capturing human facial surface morphology. Also unlike more traditional normative craniofacial resources, the 3D Facial Norms Database allows users to interact with data via an intuitive graphical interface and - given proper credentials - gain access to individual-level data, allowing users to perform their own analyses.

Proper citation: 3D Facial Norms Database (RRID:SCR_005991) Copy   

•   Source: SciCrunch Registry