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http://www.humgen.rwth-aachen.de/
Catalog of all changes detected in PKHD1 (Polycystic Kidney and Hepatic Disease 1) in a locus specific database. Investigators are invited to submit their novel data to this database. These data should be meaningful for clinical practice as well as of relevance for the reader interested in molecular aspects of polycystic kidney disease (PKD). There are also some links and information for ARPKD patients and their parents. Autosomal recessive polycystic kidney disease (ARPKD/PKHD1) is an important cause of renal-related and liver-related morbidity and mortality in childhood. This study reports mutation screening in 90 ARPKD patients and identifies mutations in 110 alleles making up a detection rate of 61%. Thirty-four of the detected mutations have not been reported previously. Two underlying mutations in 40 patients and one mutation in 30 cases are disclosed, and no mutation was detected on the remaining chromosomes. Mutations were found to be scattered throughout the gene without evidence of clustering at specific sites. PKHD1 mutation analysis is a powerful tool to establish the molecular cause of ARPKD in a given family. Direct identification of mutations allows an unequivocal diagnosis and accurate genetic counseling even in families displaying diagnostic challenges.
Proper citation: Autosomal Recessive Polycystic Kidney Disease Mutation Database (RRID:SCR_002290) Copy
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. A knowledgebase of all of the publicly available ChIP-Seq and DNase-Seq data in mouse and human. They have also manually curated metadata to ensure annotation consistency, and developed a user-friendly display matrix for quick navigation and retrieval of data for specific factors, cells, and papers. The community can contribute to this resource.
Proper citation: CistromeMap (RRID:SCR_002173) Copy
http://www.controlled-trials.com
Free-to-view clinical trials register of clinical trials worldwide, it allows users to search, register and share information about randomized controlled trials. Publication services are also available via the range of open access peer-reviewed journals published by BioMed Central. Current Controlled Trials is run by an editorial and technical in-house team. It receives advice from an international Advisory Group, including academics, doctors and health care specialists of international renown. The Advisory Group provides valuable guidance on the current activities and possible new directions of Current Controlled Trials' two databases, the metaRegister of Controlled Trials (mRCT) and the International Standard Randomised Controlled Trial Number (ISRCTN) scheme.
Proper citation: Current Controlled Trials (RRID:SCR_002325) Copy
https://www.genevestigator.com/gv/
A high performance search engine for gene expression that integrates thousands of manually curated public microarray and RNAseq experiments and nicely visualizes gene expression across different biological contexts (diseases, drugs, tissues, cancers, genotypes, etc.). There are two basic analysis approaches: # for a gene of interest, identify which conditions affect its expression. # for condition(s) of interest, identify which genes are specifically expressed in this/these conditions. Genevestigator builds on the deep integration of data, both at the level of data normalization and on the level of sample annotations. This deep integration allows scientists to ask new types of questions that cannot be addressed using conventional tools.
Proper citation: Genevestigator (RRID:SCR_002358) Copy
Ontology used to describe the experimental conditions within cognitive and behavioral experiments, primarily in humans for application and use in the functional neuroimaging community. CogPO has been developed through the integration of the Functional Imaging Biomedical Informatics Research Network (FBIRN) Human Imaging Database (HID) and the BrainMap Database. The design of CogPO concentrates on what can be observed directly: categorization of each paradigm in terms of (1) the stimulus presented to the subjects, (2) the requested instructions, and (3) the returned response.
Proper citation: Cognitive Paradigm Ontology (RRID:SCR_002235) Copy
An automatic whole-brain extraction tool for T1-weighted MRI data (commonly known as skull stripping). Whole-brain segmentation is often the first component in neuroimage pipelines and therefore, its robustness is critical for the overall performance of the system. Many methods have been proposed in the literature, but they often: * work well on certain datasets but fail on others. * require case-specific parameter tuning ROBEX aims for robust skull-stripping across datasets with no parameter settings. It fits a triangular mesh, constrained by a shape model, to the probabilistic output of a supervised brain boundary classifier. Because the shape model cannot perfectly accommodate unseen cases, a small free deformation is subsequently allowed. The deformation is optimized using graph cuts.
Proper citation: ROBEX (RRID:SCR_002534) Copy
http://www.nitrc.org/projects/ncanda-datacore/
Manuals, training materials, and computational tools developed by the National Consortium on Alcohol and NeuroDevelopment in Adolescence (NCANDA) Data Component. The NCANDA consortium consists of an Administrative Component at UC San Diego, the Data Integration Component at SRI International, and five data collection sites, Duke University, Oregon Health & Sciences University, SRI International, University of Pittsburgh, and UC San Diego. Each collection site will collect data from about 150 adolescents, each of them seen for one baseline and three annual follow-up visits.
Proper citation: NCANDA: Data Integration Component (RRID:SCR_002447) Copy
http://www.nitrc.org/projects/parser_4d/
A tool for analyzing 4D images with pathology. Originally developed for processing longitudinal images of patients with traumatic brain injury, the tool contains new image analysis algorithms that combine registration and segmentation in a coherent framework, accounting for extreme changes due to extensive tissue damage.
Proper citation: 4D-PARSeR Pathological Anatomy Regression via Segmentation and Registration (RRID:SCR_002480) Copy
Consortium to develop novel in vitro predictive screening tools and in vivo translational models and biomarkers to improve adverse drug reaction (ADR) hazard identification. This project studies the metabolic effects of eight drugs (among which are paracetamol and diclofenac ) with known side effects in the liver. By looking into the mechanics on a level ranging from the molecule to the patient, the researchers in this project aim to find biomarkers and develop tools for the early prediction of side effects of drugs. One of the breakthroughs in the project is the discovery that a person''''s genetic profile appears to be one of the mechanics that have an influence on the resistance to adverse drug reactions. The ability to identify adverse effects in an early stage will prevent much discomfort in patients and economic loss. Several PhD theses have been written from this project.
Proper citation: Towards novel translational safety biomarkers for adverse drug toxicity (RRID:SCR_004006) Copy
http://www.sanger.ac.uk/resources/databases/exomiser/query/exomiser2
A Java program that functionally annotates variants from whole-exome sequencing data starting from a VCF (Variant Call Format) file (version 4). The functional annotation code is based on Annovar and uses UCSCKnownGene transcript definitions and hg19 genomic coordinates. Variants are prioritized according to user-defined criteria on variant frequency, pathogenicity, quality, inheritance pattern, phenotype data from human and model organisms, and proximity in the interactome to phenotypically similar genes.
Proper citation: Exomiser (RRID:SCR_002192) Copy
https://www.proteinspire.org/MOPED/
An expanding multi-omics resource that enables rapid browsing of gene and protein expression information from publicly available studies on humans and model organisms. MOPED also serves the greater research community by enabling users to visualize their own expression data, compare it with existing studies, and share it with others via private accounts. MOPED uniquely provides gene and protein level expression data, meta-analysis capabilities and quantitative data from standardized analysis utilizing SPIRE (Systematic Protein Investigative Research Environment). Data can be queried for specific genes and proteins; browsed based on organism, tissue, localization and condition; and sorted by false discovery rate and expression. MOPED links to various gene, protein, and pathway databases, including GeneCards, Entrez, UniProt, KEGG and Reactome. The current version of MOPED (MOPED 2.5) The current version of MOPED (MOPED 2.5, 2014) contains approximately 5 million total records including ~260 experiments and ~390 conditions.
Proper citation: MOPED - Model Organism Protein Expression Database (RRID:SCR_006065) Copy
http://www.research.va.gov/programs/tissue_banking/als/
A human tissue bank that collects, processes, stores and gives out research specimens for future scientific studies. Presently, the VABBB is obtaining neurologic tissue specimens from Veterans who suffer from amyotrophic lateral sclerosis (ALS) and other illnesses that affect Veterans, along with relevant clinical data, essential for research. Currently, neither the cause nor prevention of ALS is known. Medical researchers are currently examining environmental, toxic, genetic, traumatic, medical, and occupational influences as possible contributors to the development and progression of ALS. Veterans have a higher risk of developing ALS compared with non-Veterans; however, the reasons for this higher risk are currently unknown. Any Veteran with ALS in the U.S. may enroll in the VABBB.
Proper citation: VA Biorepository Brain Bank (RRID:SCR_006546) Copy
Web-based tool for the ontological analysis of large lists of genes. It can be used to determine biological annotations or combinations of annotations that are significantly associated to a list of genes under study with respect to a reference list. As well as single annotations, this tool allows users to simultaneously evaluate annotations from different sources, for example Biological Process and Cellular Component categories of Gene Ontology., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: GeneCodis (RRID:SCR_006943) Copy
Website for brain experimental data and other resources such as stimuli and analysis tools. Provides marketplace and discussion forum for sharing tools and data in neuroscience. Data repository and collaborative tool that supports integration of theoretical and experimental neuroscience through collaborative research projects. CRCNS offers funding for new class of proposals focused on data sharing and other resources.
Proper citation: CRCNS (RRID:SCR_005608) Copy
A web portal that provides access to data, tools and materials that will aid in craniofacial research. Included is access to genomic and imaging based data sets from a variety of species, including zebrafish, human and mouse.
Proper citation: FaceBase (RRID:SCR_005998) Copy
https://www.iscaconsortium.org/
THIS RESOURCE IS NO LONGER IN SERVICE. Documented on June 22, 2022. A rapidly growing group of clinical cytogenetics and molecular genetics laboratories committed to improving quality of patient care related to clinical genetic testing using new molecular cytogenetic technologies including array comparative genomic hybridization (aCGH) and quantitative SNP analysis by microarrays or bead chip technology. They improve clinical care by providing a large publicly available database and forum where clinicians and researchers can share knowledge to expedite the understanding of copy number variation (CNV) in an abnormal population. The ISCA database contains whole genome array data from a subset of the ISCA Consortium clinical diagnostic laboratories. Array analysis was carried out on individuals with phenotypes including intellectual disability, autism, and developmental delay. Efforts of the Consortium include: # Clinical Utility: The ISCA Consortium has made recommendations regarding the appropriate clinical indications for cytogenetic array testing (Miller et al. AJHG 2010, PMID: 20466091). Currently, discussions are focused on pediatric applications for children with unexplained developmental delay, intellectual disability, autism and other developmental disabilities. A separate committee has been developed to address appropriate cancer genetic applications (http://www.urmc.rochester.edu/ccmc/). # Evidence-based standards for cytogenomic array design: The Consortium will develop recommendations for standards for the design, resolution and content of cytogenomic arrays using an evidence-based process and an international panel of experts in clinical genetics, clinical laboratory genetics (cytogenetics and molecular genetics), genomics and bioinformatics. This design is intended to be platform and vendor-neutral (common denominator is genome sequence coordinates), and is a dynamic process with input from the broader genetics community and evidence-based review by the expert panel (which will evolve into a Standing Committee with international representation). # Public Database for clinical and research community: It is essential that publicly available databases be created and maintained for cytogenetic array data generated in clinical testing laboratories. The ISCA data will be held in dbGaP and dbVar at NCBI/NIH and curated by a committee of clinical genetics laboratory experts. The very high quality of copy number data (i.e., deletions and duplications) coming from clinical laboratories combined with expert curation will produce an invaluable resource to the clinical and research communities. # Standards for interpretation of cytogenetic array results: Using the ISCA Database, along with other genomic and genetics databases, the Consortium will develop recommendations for the interpretation and reporting of pathogenic vs. benign copy number changes as well as imbalances of unknown clinical significance.
Proper citation: ISCA Consortium (RRID:SCR_006168) Copy
http://www.ncbi.nlm.nih.gov/clinvar/
Archive of aggregated information about sequence variation and its relationship to human health. Provides reports of relationships among human variations and phenotypes along with supporting evidence. Submissions from clinical testing labs, research labs, locus-specific databases, expert panels and professional societies are welcome. Collects reports of variants found in patient samples, assertions made regarding their clinical significance, information about submitter, and other supporting data. Alleles described in submissions are mapped to reference sequences, and reported according to HGVS standard.
Proper citation: ClinVar (RRID:SCR_006169) Copy
http://cibsr.stanford.edu/tools/human-brain-project/artrepair-software.html
A toolbox for SPM to improve fMRI analysis of high motion pediatric and clinical subjects. The toolbox includes special algorithms for motion adjustment, data repair, and noise filtering, and methods to find outlier subjects in group studies. Visualization tools are included for quality checking the data, including a movie format for viewing all data and all contrast estimates on every voxel of every subject. Methods are included to quantify results into percent signal change. * Operating System: OS Independent * Programming Language: MATLAB * Supported Data Format: ANALYZE, NIfTI-1 * execution requires: SPM
Proper citation: ArtRepair for robust fMRI (RRID:SCR_005990) Copy
Founded in 1942, the UC Department of Psychiatry and Behavioral Neuroscience is transforming behavioral health care through basic, clinical and translational research programs. Our vision is to be leaders in advancing the understanding and treatment of psychiatric disorders.
Proper citation: UC College of Medicine Department of Psychiatry and Behavioral Neuroscience (RRID:SCR_005347) Copy
http://www.oeb.harvard.edu/faculty/hartl/old_site/lab/publications/GeneMerge.html
THIS RESOURCE IS NO LONGER IN SERVCE, documented September 2, 2016. Web-based and standalone application that returns a wide range of functional genomic data for a given set of study genes and provides rank scores for over-representation of particular functions or categories in the data. It uses the hypergeometric test statistic which returns statistically correct results for samples of all sizes and is the #2 fastest GO tool available (Khatri and Draghici, 2005). GeneMerge can be used with any discrete, locus-based annotation data, including, literature references, genetic interactions, mutant phenotypes as well as traditional Gene Ontology queries. GeneMerge is particularly useful for the analysis of microarray data and other large biological datasets. The big advantage of GeneMerge over other similar programs is that you are not limited to analyzing your data from the perspective of a pre-packaged set of gene-association data. You can download or create gene-association files to analyze your data from an unlimited number of perspectives. Platform: Online tool, Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible
Proper citation: GeneMerge (RRID:SCR_005744) Copy
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