Tools   Select Another Resource Report Type

http://www.vectorbase.org

Bioinformatics Resource Center for invertebrate vectors. Provides web-based resources to scientific community conducting basic and applied research on organisms considered potential agents of biowarfare or bioterrorism or causing emerging or re-emerging diseases.

Proper citation: VectorBase (RRID:SCR_005917) Copy   

•   Source: SciCrunch Registry

https://www.facebase.org/content/ocdm

To satisfy the need for standardized terminologies several ontologies, we are developing the Ontology of Craniofacial Development and Malformation. When complete, this ontology will describe several realms of anatomy and development relevant to FaceBase, including: * Human craniofacial anatomy, including developmental progressions * Craniofacial malformations * Mouse craniofacial anatomy * Mappings between mouse and human anatomy These ontologies are currently undergoing active development. As a result, these files should be considered very preliminary. They may not work correctly, and contents will almost certainly undergo significant change. Five (sub) ontologies in this zip archive correspond to the categories described above. * OCDM - Ontology of Craniofacial Development and Malformation: currently imports the CHO, CMO, and the CHMMO. * CHO - Craniofacial Human Ontoloogy: normal adult human craniofacial anatomy derived from the FMA. * CMO - Craniofacial Mouse Ontology: normal adult mouse craniofacial anatomy * CHMMO - Craniofacial Human-Mouse Mapping Ontology: mappings of classes in the * CHO to related (homologous) structures in the CMO. CFMO - Craniofacial Malformation Ontology: abnormal human anatomy, includes the CHO All ontologies are in Protege Frames format (requires Protege 3.x). Ontologies refer to other ontologies via the Protege include mechanism. The CHMMO includes the CHO and the CMO. The OCDM (which is the umbrella ontology) includes all of the rest. Future releases will include translations to the OWL language.

Proper citation: OCDM - Ontology of Craniofacial Development and Malformation (RRID:SCR_005999) Copy   

•   Source: SciCrunch Registry

http://bishopw.loni.ucla.edu/AIR5/

A tool for automated registration of 3D (and 2D) images within and across subjects and within and sometimes across imaging modalities. The AIR library can easily incorporate automated image registration into site specific programs adapted to your particular needs.

Proper citation: Automated Image Registration (RRID:SCR_005944) Copy   

•   Source: SciCrunch Registry

http://bio-bigdata.hrbmu.edu.cn/diseasemeth/

Human disease methylation database. DiseaseMeth version 2.0 is focused on aberrant methylomes of human diseases. Used for understanding of DNA methylation driven human diseases.

Proper citation: DiseaseMeth (RRID:SCR_005942) Copy   

•   Source: SciCrunch Registry

http://jjwanglab.org:8080/gwasdb/

Combines collections of genetic variants (GVs) from GWAS and their comprehensive functional annotations, as well as disease classifications. Used to maximize utilility of GWAS data to gain biological insights through integrative, multi-dimensional functional annotation portal. In addition to all GVs annotated in NHGRI GWAS Catalog, we manually curate GVs that are marginally significant (P value < 10-3) by looking into supplementary materials of each original publication and provide extensive functional annotations for these GVs. GVs are manually classified by diseases according to Disease Ontology Lite and HPO (Human Phenotype Ontology) for easy access. Database can also conduct gene based pathway enrichment and PPI network association analysis for those diseases with sufficient variants. SOAP services are available. You may Download GWASdb SNP. (This file contains all of the significant SNP in GWASdb. In the pvalue column, 0 means this P-value is not reported in the study but it is significant SNP. In the source column, GWAS:A represents the original data in GWAS catalog, while GWAS:B is our curation data which P-value < 10-3)

Proper citation: GWASdb (RRID:SCR_006015) Copy   

•   Source: SciCrunch Registry

http://web.mit.edu/swg/software.htm

Toolbox for post-processing fMRI data. Includes software for comprehensive analysis of sources of artifacts in timeseries data including spiking and motion. Most compatible with SPM processing, but adaptable for FSL as well. * Operating System: MacOS, Windows, Linux * Programming Language: MATLAB * Supported Data Format: ANALYZE

Proper citation: Artifact Detection Tools (RRID:SCR_005994) Copy   

•   Source: SciCrunch Registry

http://www.brain-map.org/api/index.html

API and demo application for accessing the Allen Brain Atlas Mouse Brain data. Data available via the API includes download high resolution images, expression data from a 3D volume, 3D coordinates of the Allen Reference Atlas, and searching genes with similar gene expression profiles using NeuroBlast. Data made available includes: * High resolution images for gene expression, connectivity, and histology experiments, as well as annotated atlas images * 3-D expression summaries registered to a reference space for the Mouse Brain and Developing Mouse Brain * Primary microarray results for the Human Brain and Non-Human Primate * RNA sequencing results for the Developing Human Brain * MRI and DTI files for Human Brain The API consists of the following resources: * RESTful model access * Image download service * 3-D expression summary download service * Differential expression search services * NeuroBlast correlative searches * Image-to-image synchronization service * Structure graph download service

Proper citation: Allen Brain Atlas API (RRID:SCR_005984) Copy   

•   Source: SciCrunch Registry

http://www.unc.edu/~grwu/Software.html

A software plugin for 3D Slicer that matches morphological signatures of medical images automatically. HAMMER is an acronym for Hierarchical Attribute Matching Mechanism for Elastic Registration (Dinggang Shen, Christos Davatzikos, HAMMER: Hierarchical Attribute Matching Mechanism for Elastic Registration, IEEE Trans. on Medical Imaging, 21(11):1421-1439, Nov 2002) - an elastic registration algorithm for medical images, matching morphological signatures of images in a hierarchical multi-scale regime. White matter lesion (WML) segmentation is a novel multi-spectral WML segmentation protocol via incorporating information from T1-w, T2-w, PD-w and FLAIR MR brain images. (Zhiqiang Lao, Dinggang Shen, Dengfeng Liu, Abbas F Jawad, Elias R Melhem, Lenore J Launer, Nick R Bryan, Christos Davatzikos, Computer-Assisted Segmentation of White Matter Lesions in 3D MR images, Using Pattern Recognition, Academic Radiology, 15(3):300-313, March 2008).

Proper citation: Hammer And WML Modules for 3D Slicer (RRID:SCR_005980) Copy   

•   Source: SciCrunch Registry

http://www.chictr.org/en/

National clinical trial registry by Ministry of Health of China to join World Health Organization International Clinical Trial Registration Platform (WHO ICTRP Primary Registry), and the approved Primary Registry of WHO ICTRP. It registers both Chinese and global clinical trials, receives data from Partner Registers certified by the WHO ICTRP, and submits data to the WHO ICTRP Central Repository for global search. Moreover, based upon the talent and technical platform, consisting of Chinese Evidence-based Medicine Centre of Ministry of Health of China, Virtual Research Centre of Evidence-Based Medicine of Ministry of Education of China, Chinese Cochrane Centre, UK Cochrane Centre and International Clinical Epidemiology Network Resource and Training Centre in West China Hospital, Sichuan University (INCLEN CERTC), ChiCTR is responsible for providing consultations on trial design, central randomization service, guidance on the writing of clinical trial reports and relevant training. WHO takes the lead in establishing the global clinical trial registration system, which is agreed upon by governments from all over the world. There are both ethical and scientific reasons for clinical trial registration. Trial participants expect that their contributions to biomedical knowledge will be used to improve health care for everyone. Open access to information about ongoing and completed trials meets the ethical duty to trial participants, and promotes greater trust and public confidence in clinical research. Furthermore, trial registration ensures that the results of all trials can be tracked down and should help to reduce unnecessary duplication of research through greater awareness of existing trials and results. The mission of ChiCTR is to Unite clinicians, clinical epidemiologists, biostatisticians, epidemiologists and health care managers both at home and abroad, to manage clinical trials in a strict and scientific manner, and to promote their quality in China, so as to provide reliable evidences from clinical trials for health care workers, consumers and medical policy decision makers, and also to use medical resources more effectively to provide better service for Chinese people and all human beings. Any trial performed in human beings is considered as a clinical trial, and should be registered before its implementation. All the registered clinical trials will be granted a unique registration number by WHO ICTRP.

Proper citation: ChiCTR - Chinese Clinical Trial Registry (RRID:SCR_006037) Copy   

•   Source: SciCrunch Registry

http://www.human-phenotype-ontology.org

Downloadable dataset of Human Phenotype Ontology (HPO) annotations. Provides standardized vocabulary of phenotypic abnormalities encountered in human disease.

Proper citation: Human Phenotype Ontology Annotations (RRID:SCR_006219) Copy   

•   Source: SciCrunch Registry

http://www.ddduk.org/

The Deciphering Developmental Disorders (DDD) study aims to find out if using new genetic technologies can help doctors understand why patients get developmental disorders. To do this we have brought together doctors in the 23 NHS Regional Genetics Services throughout the UK and scientists at the Wellcome Trust Sanger Institute, a charitably funded research institute which played a world-leading role in sequencing (reading) the human genome. The DDD study involves experts in clinical, molecular and statistical genetics, as well as ethics and social science. It has a Scientific Advisory Board consisting of scientists, doctors, a lawyer and patient representative, and has received National ethical approval in the UK. Over the next few years, we are aiming to collect DNA and clinical information from 12,000 undiagnosed children in the UK with developmental disorders and their parents. The results of the DDD study will provide a unique, online catalogue of genetic changes linked to clinical features that will enable clinicians to diagnose developmental disorders. Furthermore, the study will enable the design of more efficient and cheaper diagnostic assays for relevant genetic testing to be offered to all such patients in the UK and so transform clinical practice for children with developmental disorders. Over time, the work will also improve understanding of how genetic changes cause developmental disorders and why the severity of the disease varies in individuals. The Sanger Institute will contribute to the DDD study by performing genetic analysis of DNA samples from patients with developmental disorders, and their parents, recruited into the study through the Regional Genetics Services. Using microarray technology and the latest DNA sequencing methods, research teams will probe genetic information to identify mutations (DNA errors or rearrangements) and establish if these mutations play a role in the developmental disorders observed in patients. The DDD initiative grew out of the groundbreaking DECIPHER database, a global partnership of clinical genetics centres set up in 2004, which allows researchers and clinicians to share clinical and genomic data from patients worldwide. The DDD study aims to transform the power of DECIPHER as a diagnostic tool for use by clinicians. As well as improving patient care, the DDD team will empower researchers in the field by making the data generated securely available to other research teams around the world. By assembling a solid resource of high-quality, high-resolution and consistent genomic data, the leaders of the DDD study hope to extend the reach of DECIPHER across a broader spectrum of disorders than is currently possible.

Proper citation: Deciphering Developmental Disorders (RRID:SCR_006171) Copy   

•   Source: SciCrunch Registry

http://www.birncommunity.org/tools-catalog/human-imaging-database-hid/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented October 5, 2017.

Database management system developed to handle the increasingly large and diverse datasets collected as part of the MBIRN and FBIRN collaboratories and throughout clinical imaging communities at large. The HID can be extended to contain relevant information concerning experimental subjects, assessments of subjects, the experimental data collected, the experimental protocols, and other metadata normally included with experiments.

Proper citation: Human Imaging Database (RRID:SCR_006126) Copy   

•   Source: SciCrunch Registry

http://www-bionet.sscc.ru/sitex/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on August 19,2019. Analyzing protein structure projection on exon-intron structure of corresponding gene through years led to several fundamental conclusions about structural and functional organization of the protein. According to these results we decided to map the protein functional sites. So we created the database SitEx that keep the information about this mapping and included the BLAST search and 3D similar structure search using PDB3DScan for the polypeptide encoded by one exon, participating in organizing the functional site. This will help: # to study the positions of the functional sites in exon structure; # to make the complex analysis of the protein function; # to exposure the exons that took part in exon shuffling and came from bacterial genomes; # to study the peculiarities of coding the polypeptide structures. Currently, SitEx contains information about 9994 functional sites presented in 2021 proteins described in proteomes of 17 organisms.

Proper citation: SitEx (RRID:SCR_006122) Copy   

•   Source: SciCrunch Registry

http://central.xnat.org

Online repository of open access images including MR Sessions, MRI, Freesurfer APARC, Freesurfer ASEGs, Clinical Assessments, Atlas Scaling Factors, and Fast Segmentations data. CENTRAL currently contains 374 Projects, 3808 Subjects, and 5174 Imaging Sessions (June 2014). Central is powered by XNAT (The Extensible Neuroimaging Archive Toolkit), an open source software platform designed to facilitate management and exploration of neuroimaging and related data. XNAT includes a secure database backend and a rich web-based user interface.

Proper citation: XNAT Central (RRID:SCR_006235) Copy   

•   Source: SciCrunch Registry

https://compbio.dfci.harvard.edu/predictivenetworks//

A flexible, open-source, web-based application and data services framework that enables the integration, navigation, visualization and analysis of gene interaction networks. The primary goal of PN is to allow biomedical researchers to evaluate experimentally derived gene lists in the context of large-scale gene interaction networks. The PN analytical pipeline involves two key steps. The first is the collection of a comprehensive set of known gene interactions derived from a variety of publicly available sources. The second is to use these ''known'' interactions together with gene expression data to infer robust gene networks. The regression-based network inference algorithm creates a graph of gene interactions in which cycles may be present (but no self-loops). Based on information-theoretic techniques, a causal gene interaction network is inferred from both prior knowledge (interactions extracted from biomedical literature and structured biological databases) and gene expression data. A prediction model is fitted for each gene, given its parents, enabling assessment of the predictive ability of the network model.

Proper citation: Predictive Networks (RRID:SCR_006110) Copy   

•   Source: SciCrunch Registry

http://brainvis.wustl.edu/wiki/index.php/Caret:About

Software package to visualize and analyze structural and functional characteristics of cerebral and cerebellar cortex in humans, nonhuman primates, and rodents. Runs on Apple (Mac OSX), Linux, and Microsoft Windows operating systems.

Proper citation: Computerized Anatomical Reconstruction and Editing Toolkit (RRID:SCR_006260) Copy   

•   Source: SciCrunch Registry

http://www.stembase.ca

A publicly accessible database containing data on Affymetrix DNA microarray experiments, and Serial Analysis of Gene Expression, mostly on human and mouse stem cell samples and their derivatives to facilitate the discovery of gene functions relevant to stem cell control and differentiation. It has grown in both size and scope into a system with analysis tools that examine either the whole database at once, or slices of data, based on tissue type, cell type or gene of interest. There is currently more than 210 stem cell samples in 60 different experiments, with more being added regularly. The samples were originated by researchers of the Stem Cell Network and processed at the Core Facility of Stemcore Laboratories under the management of Ms. Pearl Campbell in the frame of the Stem Cell Genomics Project. Periodically, new expression data is submitted to the Gene Expression Omnibus (GEO) repository at the National Center for Biotechnological Information, in order to allow researchers to compare the data deposited in StemBase to a large amount of gene expression data sets. StemBase is different from GEO in both focus and scope. StemBase is concerned exclusively with stem cell related data. we are focused in Stem Cell research. We have made a significant effort to ensure the quality and consistency of the data included. This allows us to offer more specialized analysis tools related to Stem Cell data. GEO is intended as a large scale public archive. Deposition in a public repository such as GEO is required by most important scientific journals and it is advantageous for a further diffusion of the data since GEO is more broadly used than StemBase.

Proper citation: StemBase (RRID:SCR_006252) Copy   

•   Source: SciCrunch Registry

http://www.ctf.org/

A non-profit dedicated to ending neurofibromatosis (NF) through research. It is the leading nonprofit funding source of NF research in the world. The mission of The Children''s Tumor Foundation is to: * Encourage and support research and the development of treatments and cures for neurofibromatosis types 1 and 2, schwannomatosis, and related disorders (hereafter collectively referred to as NF); * Support persons with NF, their families, and caregivers by providing thorough, accurate, current, and readily accessible information; * Assist in the development of clinical centers, best practices, and other patient support mechanisms (but not including direct medical care) to create better access to quality healthcare for affected individuals; and, * Expand public awareness of NF to promote earlier and accurate diagnoses by the medical community, increase the non-affected population''s understanding of the challenges facing people with NF, and encourage financial and other forms of support from public and private sources. Through the implementation of the Foundation''s research initiatives, progress is being made on all fronts and for all types of NF; from discovery studies understanding the molecular signaling deficits that cause the manifestations of NF to the growth of preclinical drug screening initiatives and the emergence of a growing number of clinical trials. The Foundation advances research through strategically integrated programs that speed therapies from the lab to the patient.

Proper citation: Childrens Tumor Foundation (RRID:SCR_006280) Copy   

•   Source: SciCrunch Registry

http://www.cafevariome.org/

Clearinghouse and exchange portal for gene variant (mutation) data produced by diagnostics laboratories, offering users a portal through which to announce, discover and acquire a comprehensive listing of observed neutral and disease-causing gene variants in patients and unaffected individuals. Cafe Variome is not a ''''database'''' for the hosting/display/release of data, but a shop window for finding data. As such, it holds only core info for each record, and uses this merely to enable holistic searching across resources. Diagnostics laboratories routinely assess DNA samples from patients with various inherited disorders, and so produce a great wealth of data on the genetic basis of disease. Unfortunately, those data are not usually shared with others. To address this gross deficiency, a novel system has been developed that aims to facilitate the automated transfer of diagnostic laboratory data to the wider community, via an internet based Cafe for routinely exchanging genetic variation data. The flow of research data concerning the genetic basis of health and disease is critical to understanding and developing treatments for a range of genetic diseases. Overall, the project aims to lower the barriers and provide incentives for a willing community to share data, and thereby facilitate the broader exploitation of diagnostic laboratory data. Cafe Variome aims to address the above data flow problems by: # Minimizing the effort required to publish variant data # Ensuring attribution for data creators working in diagnostic laboratories Key elements of the project strategy are: * Data publication will be automated by endowing standard analysis tools used by laboratories with an online data submission function. Submissions will be received by a central Internet depot, which will serve as a place where published datasets are advertised, and subsequently discovered by diverse 3rd parties. * Each dataset will be unambiguously linked with the data submitter''''s identity, and systems devised to facilitate citation of published variant datasets so they can be cited in the literature. Data creators will thus be credited for their contributions. Data submitters can use Cafe Variome to simply announce or publicize their data to the world. To enable this, only core, non-identifiable data is submitted to the central repository, enabling users to search and discover records of interest in the source repository. The data are not automatically handed on to the user (unless intended by the submitters). Hence, the concept is used to deal with the challenge of maximally sharing data whilst fully respecting ethico-legal considerations.

Proper citation: cafe variome (RRID:SCR_006162) Copy   

•   Source: SciCrunch Registry

http://www.patientcrossroads.com/

A trusted third-party gatekeeper of patient data from participants in a rare disease ecosystem, collecting and managing the information in a scalable, cost-effective manner. Each patient registry provides critical disease knowledge which makes that disease easier to study, increasing the probability a treatment can be developed. PatientCrossroads takes a network approach to patient registry programs. Unlike companies that merely sell registry software, we offer a full range of administration, management, and genetic curation services. What does this consolidated, patient-centric approach to patient registries mean? * Patients can more easily find registries and provide their valuable data (including locations of blood and tissue samples as well as reports of diagnoses, disease symptoms, treatment usage, and lifestyle activities) * Patients can be confident in the privacy of their de-identified data and the knowledge that PatientCrossroads does not sell patient data * Researchers and pharmaceutical companies have a larger, more easily accessible pool of potential patients for research studies and clinical trials targeting specific rare diseases * Pharmaceutical companies can collect post-market surveillance data in a more scalable and cost-effective manner * Rare disease advocacy and research foundations can more easily organize their global patient populations for inclusion in trials and studies

Proper citation: PatientCrossroads (RRID:SCR_006279) Copy   

•   Source: SciCrunch Registry