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http://www.sph.umich.edu/csg/abecasis/LAMP/

Software for linkage and association modeling in pedigrees that uses a maximum likelihood model to extract information on genetic linkage and association from samples of unrelated individuals, sib pairs, trios and larger pedigrees (Li et al, 2005; Li et al, 2006). It provides estimates of genetic model parameters and powerful tests of association in settings where population stratification is not a concern.

Proper citation: LAMP (RRID:SCR_001740) Copy   

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http://www.utsouthwestern.edu/labs/acute-liver/

Clinical research network for gathering prospective data and bio-samples on acute liver failure in adults since 1998. Clinical histories and laboratory and outcome data are available. Sample types include serum, plasma, urine, DNA, and liver tissue.

Proper citation: Acute Liver Failure Study Group (RRID:SCR_001463) Copy   

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http://www.broadinstitute.org/software/syzygy/

A targeted sequencing post processing analysis software tool that allows: 1. SNP and indel detection; 2. Allele frequency estimation; 3. Single-marker association test; 4. Group-wise marker test association; 5. Experimental QC summary (%dbSNP, Ts/Tv, Ns/S); 6. Power to detect variant. (entry from Genetic Analysis Software)

Proper citation: SYZYGY (RRID:SCR_002157) Copy   

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http://www.ncbcs.org/biositemaps/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on April 27,2023. Biositemaps represent a mechanism for computational biologists and bio-informaticians to openly broadcast and retrieve meta-data about biomedical data, tools and services (i.e., biomedical resources) over the Internet. All Institutions with an interest in biomedical research can publish a biositemap.rdf file on their Internet site. The technology, developed by the Biositemaps Working Group of the NIH Roadmap National Centers of Biomedical Computing (NCBC), addresses (i) locating, (ii) querying, (iii) composing or combining, and (iv) mining biomedical resources. Each site which intends to contribute to the inventory instantiates a file on its Internet site biositemap.rdf which conforms to a defined RDF schema and uses concepts from the Biomedical Resource Ontology to describe the resources. Each biositemap.rdf file is simply a list of controlled metadata about resources (software tools, databases, material resources) that your organization uses or believes are important to biomedical research. The key enabling technologies are the Information Model (IM) which is the list of metadata fields about each resource (resource_name, description, contact_person, resource_type,...) and the Biomedical Resource Ontology (BRO) which is a controlled terminology for the resource_typeand which is used to improve the sensitivity and specificity of web searches. Biositemaps blend the features of Sitemaps (enabling efficient web-content exploration) and RSS Feeds (a mechanism for wide and effective news dissemination). As a hybrid between Sitemaps and RSS feeds, the Biositemap infrastructure facilitates a decentralized, portable, extensible and computationally tractable generation and consumption of meta-data about existent, revised and new resources for biomedical computation. Web browsers, crawlers and robots can discover, accumulate, process, integrate and deliver Biositemaps content to (human or machine) users in a variety of graphical, tabular, computational formats. Biositemaps content allows such web browsers to pool resource-associated metadata from disparate and diverse sites and present it to the user in an integrated fashion. The Biositemaps protocol provides clues, information and directives for all Biositemap web harvesters that point to the existence and content of such biomedical resources at different sites.

Proper citation: Biositemaps (RRID:SCR_001976) Copy   

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https://wfcc.info/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Collects, authenticates, maintains and distributes cultures of microorganisms and cultured cells. Its aim is to promote and support the establishment of culture collections and related services, to provide liaison and set up an information network between the collections and their users, to organize workshops and conferences, publications and newsletters and work to ensure the long term perpetuation of important collections. The WFCC (through the activities of Professor Skerman, University of Queensland, Australia, and his colleagues in the 1960's) pioneered the development of an international database on culture resources worldwide. The result is the WFCC World Data Center for Microorganisms (WDCM). This data resource is now maintained at National Institute of Genetics (NIG), Japan and has records of nearly 476 culture collections from 62 countries. The records contain data on the organization, management, services and scientific interests of the collections. Each of these records is linked to a second record containing the list of species held. The WDCM database forms an important information resource for all microbiological activity and also acts as a focus for data activities among WFCC members.

Proper citation: World Federation for Culture Collections (RRID:SCR_001974) Copy   

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http://cgsc.biology.yale.edu/index.php

The CGSC Collection contains only non-pathogenic BSL-1 laboratory strains, primarily genetic derivatives of Escherichia coli K-12, the laboratory strain widely used in genetic and molecular studies, but a few B strains. The CGSC Database of E. coli genetic information includes genotypes and reference information for the strains in the CGSC collection, the names, synonyms, properties, and map position for genes, gene product information, and information on specific mutations and references to primary literature. The public version of the database includes this information and can be queried directly via this CGSC DB WebServer. The collection includes cultures of wild-type contributed from a number of laboratories and a few thousand derivatives carrying one or up to 29 mutations from among 3500 mutations in (or included in deletions spanning) more than 1300 different loci. Some combinations were constructed particularly for mapping purposes and are still used for teaching and for rapid localization, some for manifestation of a particular phenotype, some strains for transferring a particular region or for complementation analysis. Some plasmids, e.g., the Clarke and Carbon collection, F-primes, a number of toolkit plasmids, and a few classic plasmids are included, but it is not a comprehensive collection of plasmids. Additionally, we have recently acquired most of the strains from the Keio Collection of systematic individual gene knockout (deletion/kan insertion) strains.

Proper citation: CGSC (RRID:SCR_002303) Copy   

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http://sccn.ucsd.edu/wiki/MPT

This toolbox is an EEGLAB plugin for performing Measure Projection Analysis. Measure Projection Analysis (MPA) is a novel probabilistic multi-subject inference method that overcomes EEG Independent Component (IC) clustering issues by abandoning the notion of distinct IC clusters. Instead, it searches voxel by voxel for brain regions having event-related IC process dynamics that exhibit statistically significant consistency across subjects and/or sessions as quantified by the values of various EEG measures. Local-mean EEG measure values are then assigned to all such locations based on a probabilistic model of IC localization error and inter-subject anatomical and functional differences.

Proper citation: Measure Projection Toolbox (RRID:SCR_002429) Copy   

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http://www.w3.org/wiki/images/5/51/HCLSIG$$SWANSIOC$$Actions$$RhetoricalStructure$$models$$abcde$abcde_example.htm

Proposed format for papers to be machine-readable for computers and wikis. The goal is to make mining, integration, and consumption of published information by semantic browsers and wikis easier.

Proper citation: ABCDE Format (RRID:SCR_002428) Copy   

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https://sites.google.com/a/brain.org.au/ctp/

Software package with functions that will help researchers plan how many subjects per group need to be included in an MRI-based cortical thickness study to ensure a thickness difference is detected. The package requires cortical thickness mapping and co-registration to be carried out using Freesurfer. The power analyses are implemented in the R software package., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: cortex (RRID:SCR_002467) Copy   

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http://www.nitrc.org/projects/ukftractography/

Software framework which uses an unscented Kalman filter for performing tractography. At each point on the fiber the most consistent direction is found as a mixture of previous estimates and of the local model. It is very easy to expand the framework and to implement new fiber representations for it. Currently it is possible to tract fibers using two different 1-, 2-, or 3-tensor methods. Both methods use a mixture of Gaussian tensors. One limits the diffusion ellipsoids to a cylindrical shape (the second and third eigenvalue are assumed to be identical) and the other one uses a full tensor representation. The project is written in C++. It could be used both as a Slicer3 module and as a standalone commandline application.

Proper citation: Diffusion Tractography with Kalman Filter (RRID:SCR_002585) Copy   

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http://jena.sourceforge.net/

Java framework for building Semantic Web applications, it provides a collection of tools and Java libraries to help you to develop semantic web and linked-data apps, tools and servers. It provides extensive Java libraries for helping developers develop code that handles RDF, RDFS, RDFa, OWL and SPARQL in line with published W3C recommendations. Jena includes a rule-based inference engine to perform reasoning based on OWL and RDFS ontologies, and a variety of storage strategies to store RDF triples in memory or on disk. The Jena Framework includes: * an API for reading, processing and writing RDF data in XML, N-triples and Turtle formats; * an ontology API for handling OWL and RDFS ontologies; * a rule-based inference engine for reasoning with RDF and OWL data sources; * stores to allow large numbers of RDF triples to be efficiently stored on disk; * a query engine compliant with the latest SPARQL specification * servers to allow RDF data to be published to other applications using a variety of protocols, including SPARQL In April 2012, Jena graduated from the Apache incubator process and was approved as a top-level Apache project.

Proper citation: JENA: A Semantic Web Framework for Java (RRID:SCR_001766) Copy   

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http://www.nitrc.org/projects/shape_mancova/

shapeAnalysisMANCOVA offers statistical shape analysis based on a parametric boundary description (SPHARM) as the point-based model computing method. The point-based models will be analyzed with the methods here proposed using multivariate analysis of covariance (MANCOVA). Here, the number of variates being tested is the dimensionality of our observations. Each point of these observations is a three dimensional displacement vector from the mean. The number of contrasts is the number of equations involved in the null-hypothesis. In order to encompass varying numbers of variates and contrasts, and to account for independent variables, a matrix computation is performed. This matrix represents the multidimensional aspects of the correlation significance and it can be transformed into a scalar measure by manipulation of its eigenvalues. Details of the methods can be found in its Insight Journal publication: http://hdl.handle.net/10380/3124

Proper citation: shapeAnalysisMANCOVA - SPHARM tools (RRID:SCR_002578) Copy   

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https://pydicom.github.io/

Software Python package for working with DICOM files, made for inspecting and modifying DICOM data in an easy pythonic way. The modifications can be written again to a new file. As a pure python package, it should run anywhere python runs without any other requirements.

Proper citation: pydicom (RRID:SCR_002573) Copy   

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http://www.egi.com/research-division-geodesic-system-components/eeg-software

A complete software package for working with electroencephalography (EEG) and event-related potential (ERP) data. You can acquire, review, analyze, and now ?see? your participant with synchronized video. Net Station also offers specialized tools and workflow options for both clinical and research applications, allows you to save different combinations of view settings (called workspaces) and helps with your reporting requirements by letting you set up and print custom cover pages. For more specialized work, Net Station also provides an optional electrical source estimation module (GeoSource) and an optional sensor location digitizer (Geodesic Photogrammetry System).

Proper citation: Net Station EEG Software (RRID:SCR_002453) Copy   

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http://www.biobank.unisi.it/Elencorett.asp

Data and biospecimen from Rett Syndrome patients shared with the scientific community with the ability to visualize the list of available samples and select those with specific clinical and molecular features. It also contains information on biospecimen samples from x-linked retardation, microdeletion, duplication syndromes, autosomal MR, and retinoblastoma. The bank is active since 1998 and it is located in the Medical Genetics Unit, at the University Hospital of Siena. The bank is divided in three distinct sections: # Rett Syndrome. This section contains samples from patients affected by Rett syndrome, a neurodegenerative disease affecting almost exclusively girls with an estimated frequency of 1:10000-15000 live born. By accessing the section users can see a list of all patients available with their phenotype, the specific MECP2 or CDKL5 mutation if known and the kind of biological samples available for each patient. The availability of this large panel of patients is potentially important for the clarification of the molecular bases of Rett syndrome. In fact, a 20-30 of Rett cases do not have MECP2 or CDKL5 mutations. These patients might bear intronic/promoter MECP2 or CDKL5 mutations or they might have alterations in one or more genes different from MECP2 or CDKL5, as suggested by the identification of various chromosomal rearrangements. To confirm a causative role of these rearrangements, and to identify the relevant gene/s, it is important to collect a great number of patients in which to search for overlapping rearrangements or point mutations in candidate genes. # X-Linked Mental Retardation. This section contains samples collected by the centers belonging to the Italian network on X-linked mental retardation, which includes the laboratory of bank curators (for specific information on the network goals and organization, go to the section page). Mental retardation (MR) is the most frequent cause of serious handicap in humans with an estimated prevalence of 0,3-0,5 for moderate to severe MR (IQ<50) which increases to 1-1,5 when mild MR (IQ 50-70) is included. It is calculated that about 20-25 of mentally retarded males have a mutation in a gene on the X chromosome (X-linked mental retardation). X-linked mental retardation is a genetically heterogeneous condition. This is particularly true for the non-syndromic form (MRX), where MR is the only consistent clinical finding and no distinctive features between patients exist. In this situation the only possibility to group patients from different families is represented by linkage analysis, which needs the availability of large families. However, families linked to the same region demonstrate different causative genes. In these conditions, the number of patients available for analysis is a discriminating factor since a large number of patients need to be tested in order to fully confirm or exclude the involvement of a gene in MRX. # Other. This section of the bank contains biological materials and clinical data of patients with other genetic disorders (different from Rett and X-linked mental retardation). Part of this section is dedicated to Alport syndrome. Services: * Isolation of leukocytes from human peripheral blood samples * Establishment of EBV transformed lymphoblastoid cell lines from human peripheral blood leukocytes. * DNA extraction. * Plasma isolation. * Storage: ** Cryo-preservation of transformed cell lines and primary leukocytes at 135��C ** Storage of DNA at 20 degrees C ** Storage of plasma at 20 degrees C * Distribution of the stored biological samples.

Proper citation: Italian Rett Syndrome database (RRID:SCR_002000) Copy   

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http://www.speedbiosystems.com/

Commercial antibody supplier based in Maryland.

Proper citation: Speed BioSystems (RRID:SCR_001673) Copy   

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http://www.nitrc.org/projects/segadapter/

An open source learning-based software that automatically learns how to transfer the output of a host segmentation tool closer to the user's manual segmentation using the image data and manual segmentation provided by the user. The motivation of this project is to bridge the gap between the segmentation tool developer and the tool users such that the existing segmentation tools can more effectively serve the community. More and more automatic segmentation tools are publicly available to today's researchers. However, when applied by their end-users, these segmentation tools usually can not achieve the performance that the tool developer reported. Discrepancies between the tool developer and its users in manual segmentation protocols and imaging modalities are the main reasons for such inconsistency.

Proper citation: Automatic Segmentation Tool Adapter (RRID:SCR_002481) Copy   

•   Source: SciCrunch Registry

http://bmsr.usc.edu/software/targetgene/

MATLAB tool to effectively identify potential therapeutic targets and drugs in cancer using genetic network-based approaches. It can rapidly extract genetic interactions from a precompiled database stored as a MATLAB MAT-file without the need to interrogate remote SQL databases. Millions of interactions involving thousands of candidate genes can be mapped to the genetic network within minutes. While TARGETgene is currently based on the gene network reported in (Wu et al.,Bioinformatics 26:807-813, 2010), it can be easily extended to allow the optional use of other developed gene networks. The simple graphical user interface also enables rapid, intuitive mapping and analysis of therapeutic targets at the systems level. By mapping predictions to drug-target information, TARGETgene may be used as an initial drug screening tool that identifies compounds for further evaluation. In addition, TARGETgene is expected to be applicable to identify potential therapeutic targets for any type or subtype of cancers, even those rare cancers that are not genetically recognized. Identification of Potential Therapeutic Targets * Prioritize potential therapeutic targets from thousands of candidate genes generated from high-throughput experiments using network-based metrics * Validate predictions (prioritization) using user-defined benchmark genes and curated cancer genes * Explore biologic information of selected targets through external databases (e.g., NCBI Entrez Gene) and gene function enrichment analysis Initial Drug Screening * Identify for further evaluation existing drugs and compounds that may act on the potential therapeutic targets identified by TARGETgene * Explore general information on identified drugs of interest through several external links Operating System: Windows XP / Vista / 7

Proper citation: TARGETgene (RRID:SCR_001392) Copy   

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http://faculty.washington.edu/browning/beagle/beagle.html

Software package for analysis of large-scale genetic data sets with hundreds of thousands of markers genotyped on thousands of samples. BEAGLE can * phase genotype data (i.e. infer haplotypes) for unrelated individuals, parent-offspring pairs, and parent-offspring trios. * infer sporadic missing genotype data. * impute ungenotyped markers that have been genotyped in a reference panel. * perform single marker and haplotypic association analysis. * detect genetic regions that are homozygous-by-descent in an individual or identical-by-descent in pairs of individuals. Beagle can also be used in conjunction with PRESTO, a program for fast and flexible permutation testing. PRESTO can compute empirical distributions of order statistics, analyze stratified data, and determine significance levels for one-stage and two-stage genetic association studies. BEAGLE is written in Java and runs on any computing platform with a Java version 1.6 interpreter (e.g. Windows, Unix, Linux, Solaris, Mac).

Proper citation: BEAGLE (RRID:SCR_001789) Copy   

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http://www.nitrc.org/projects/pestica/

Software tool to detect physiologic signals from the data itself as well as an adaptive physiologic noise removal tool (Impulse Response Function or IRF-RETROICOR) that zooms in on noise with only 6 regressors, getting all the noise that 5th order RETROICOR gets. These tools will allow you to correct your data for physiologic noise with what you currently have. These signals are equivalent to a parallel monitored pulse signal and a respiratory chest-bellows signal. Do you have 3D+time EPI data (BOLD or perfusion) but no usable physio signals for pulse and respiration? Are you concerned about the effect of physio noise on your data but don't know what to do but regress data-derived signals that mix unknown functional signal with possible physio noise signal? Are you concerned about the number of regressors you're incorporating once you add 5th order RETROICOR (20 more regressors!)? This is for you.

Proper citation: PESTICA fMRI Physio Detection/Correction (RRID:SCR_002513) Copy   

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