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http://code.google.com/

Developer tools, APIs and resources. Search developers.google.com and code.google.com.

Proper citation: Google Code (RRID:SCR_005786) Copy   

•   Source: SciCrunch Registry

http://ccr.coriell.org/Sections/Collections/HuREF/?SsId=78

The Human Reference Genetic Material Repository makes available DNA from a single individual, J. Craig Venter, whose genome has been sequenced and assembled. The DNA samples are prepared from a lymphoblastoid cell line established at Coriell Cell Repositories from a sample of peripheral blood. The DNA samples are available in 50 microgram aliquots. The lymphoblastoid cell line is not available for distribution. The human DNA sample provided is that of J. Craig Venter whose DNA from white blood cells and sperm was sequenced using Sanger chemistry (ABI Capillary Electrophoresis Platforms 3700 and 3730xl), assembled using the Celera Assembler and was published in PLoS Biology . J. Craig Venter, born on 14 October 1946, is a Caucasian male of self-reported European-American ancestry. The data available on this sample, whose genome assembly is referred to as HuRef, includes: * Whole Genome Shotgun Sequencing data * Sequence trace set deposited by JCVI in the NCBI trace archive * Human Genome Browser displaying sequence assembly, DNA variants and gene annotations Additional data sets from this study include: * Full set of Sanger reads used for genome assembly * SNP and insertion/deletion variant on the human genome sequence coordinates (NCBI version 36) * Affymetrix 500K GeneChip data * Illumina HumanHap650Y Genotyping BeadChip data Given the amount of data publicly available the genomic content of this sample, HuRef will be useful as a reference for many genetic studies.

Proper citation: Human Reference Genetic Material Repository (RRID:SCR_004693) 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.well.ox.ac.uk/platypus

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 16,2023. Software tool designed for efficient and accurate variant detection in high throughput sequencing data. Haplotype based variant caller for next generation sequence data.

Proper citation: Platypus (RRID:SCR_005389) Copy   

•   Source: SciCrunch Registry

http://www.uthouston.edu/uth-big/Projects/BioBank.htm

The University of Texas Health Science Center at Houston (UTHealth) Clinical and Translational Sciences (CCTS) BioBank employs a federated rather than a centralized model which encourages participation by sample owners who are concerned about guaranteeing their ownership of samples and sample information about patients, samples and related clinical data. In a federated model, individual sites agree on shared policies and procedures for data and sample sharing and oversight. Samples remain with and are governed by the contributing principal investigator at each site. The contributing investigator has final authority whether or not to collaborate or to release samples to qualified researchers. The goal of SLED (Sample Location and Enhanced Distribution) is to help researchers overcome two of the biggest obstacles preventing their research from beginning: 1) location of samples and related data, and 2) requesting of samples and related data. Prior to SLED''s inception the existing system was limited to providing links to samples and data and relying on phone calls to sample owners to facilitate sharing. Collaboration between the CTSA Biobank Consortium and the informatics team at the University of Texas School of Biomedical Informatics is ongoing during this effort. The initial design was constructed using best practices offered by NIH, NCI, and other biobank industry leaders to support and to improve synergy and interaction among various research efforts. Through SLED, researchers will be able to search for samples using a variety of criteria including availability, clinical data, consent criteria, patient demographics, patient diagnoses, study data, and sample type at local and national biobank sites.

Proper citation: UTHealth BioBank (RRID:SCR_004570) Copy   

•   Source: SciCrunch Registry

http://www.spaintechnology.com/biotech/news/hiv-biobank.html

THIS RESOURCE IS NO LONGER IN SERVICE, documented on September 15, 2011. The Spanish HIV BioBank was created with the objectives of processing, storing and providing distinct samples from HIV/AIDS patients, categorized according to strictly defined characteristics, free of charge to research projects. Strict compliance to ethical norms is always guaranteed. HIV BioBank possesses nearly 50,000 vials containing different prospective longitudinal study sample types. More than 1,700 of these samples are now used in 19 national and international research projects. (2009) The HIV BioBank represents a novel approach to HIV research that might be of general interest not only for basic and clinical research teams working on HIV, but also for those groups trying to establish large networks focused on research on specific clinical problems. It also represents a model to stimulate cooperative research among large numbers of research groups working as a network on specific clinical problems. The HIV BioBank is able to very efficiently release samples to different research project not only in Spain but also in other countries.

Proper citation: HIV Biobank (RRID:SCR_004691) Copy   

•   Source: SciCrunch Registry

http://www.uni-bonn.de/~umt70e/soft.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5th,2023. Software application that calculates the sample size required for obtaining a prescribed power against a specified alternative for TDT. (entry from Genetic Analysis Software)

Proper citation: TDTPOWER (RRID:SCR_005021) Copy   

•   Source: SciCrunch Registry

http://www.gotaxexplorer.de/

The Functional Similarity Search Tool (FSST) has been implemented for comparing user defined sets of annotated entities. FSST supports the computation of functional similarity scores based on an individual ontology and of combined scores. Its multi-threaded Java implementation takes advantage of symmetric multi-processing computers, decreasing runtime considerably. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: FSST - Functional Similarity Search Tool (RRID:SCR_005819) 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

http://ki.se/ki/jsp/polopoly.jsp?d=29354&a=31618&l=en

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The aim of the study is to estimate the importance of genetic (primary) and environmental factors for economic behavior by conducting a series of standard behavioral economics experiments on a sample of twins from the Swedish Twin Registry.

Proper citation: KI Biobank - Economical Behavior (RRID:SCR_005934) Copy   

•   Source: SciCrunch Registry

http://od1n.sourceforge.net

A C++ software framework to develop, simulate and run magnetic resonance sequences on different platforms.

Proper citation: Object-Oriented Development Interface for NMR (RRID:SCR_005974) 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://www.biological-networks.org/p/outliers/

Software that performs a morphology-based approach for the automatic identification of outlier neurons based on neuronal tree structures. This tool was used by Zawadzki et al. (2012), who reported on and its application to the NeuroMorpho database. For the analysis, each neuron is represented by a feature vector composed of 20 measurements, which are projected into lower dimensional space with PCA. Bivariate kernel density estimation is then used to obtain a probability distribution for cells. Cells with high probabilities are understood as archetypes, while those with the small probabilities are classified as outliers. Further details about the method and its application in other domains can be found in Costa et al. (2009) and Echtermeyer et al. (2011). This version requires Matlab (Mathworks Inc, Natick, USA) and allows the user to apply the workflow using a graphical user interface.

Proper citation: DONE: Detection of Outlier NEurons (RRID:SCR_005299) Copy   

•   Source: SciCrunch Registry

http://www.rand.org/labor/FLS/IFLS.html

A dataset of an on-going multi-level longitudinal survey in Indonesia that collects extensive information on socio-economic and demographic characteristics of respondents, as well as extremely comprehensive interviews with local leaders about community services and facilities. The survey is ideally suited for research on topics related to important dynamic aging processes such as the transition from self-sufficiency to dependency, the decline from robust health to frailty, labor force and earning dynamics, wealth accumulation and decumulation, living arrangements and intergenerational transfers. The first wave of IFLS was fielded in 1993 and collected information on over 30,000 individuals living in 7,200 households. The sample covers 321 communities in 13 provinces in Indonesia and is representative of about 83% of the population. These households were revisited in 1997 (IFLS2), 2000 (IFLS3), and 2007-8 (IFLS4). A 25% sub-sample of households was re-interviewed in 1998 (IFLS2+). Special attention is paid to the measurement of health, including the measurement of anthropometry, blood pressure, lung capacity, a mobility test and collection of dry blood spots by a nurse or doctor. In addition to comprehensive life history data on education, work, migration, marriage and child bearing, the survey collects very detailed information on economic status of individuals and households. Links with non co-resident family members are spelled out in conjunction with information on borrowing and transfers. Information is gathered on participation in community activities and in public assistance programs. Measurement of health is a major focus of the survey. In addition to detailed information about use of private and public health services along with insurance status, respondents provide a self-reported assessment of health status. Detailed information on the local economy and prices of goods and services are also collected. These data may be matched with the individual and household-level data. Considerable attention has been placed on minimizing attrition in IFLS. In each re-survey, about 95% of households have been re-contacted. Around 10-15% of respondents have moved from the location in which they were interviewed in the previous wave. In addition, individuals who split-off from the original households have been followed. They have added around 1,000 households to the sample in 1997 and about 3,000 households in 2000. Data Availability: IFLS1 data are available through ICPSR as study number 6706. Data from subsequent waves of the IFLS can be accessed from the RAND project Website. * Dates of Study: 1993-2008 * Study Features: Longitudinal, International, Anthropometric Measures, Biomarkers * Sample Size: ** 1993: 22,000 (IFLS1) ** 1997: 33,000 (IFLS2) ** 1998: 10,000 (IFLS2+) ** 2000: 37,000 (IFLS3) ** 2008: 44,103 (IFLS4) Links: * IFLS1 ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/06706 * IFLS ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00184

Proper citation: Indonesia Family Life Survey (RRID:SCR_005695) Copy   

•   Source: SciCrunch Registry

http://ccr.coriell.org/Sections/Collections/NINDS/?SsId=10

Open resource of biological samples (DNA, cell lines, and other biospecimens) and corresponding phenotypic data to promote neurological research. Samples from more than 34,000 unique individuals with cerebrovascular disease, dystonia, epilepsy, Huntington's Disease, motor neuron disease, Parkinsonism, and Tourette Syndrome, as well as controls (population control and unaffected relatives) have been collected. The mission of the NINDS Repository is to provide 1) genetics support for scientists investigating pathogenesis in the central and peripheral nervous systems through submissions and distribution; 2) information support for patients, families, and advocates concerned with the living-side of neurological disease and stroke.

Proper citation: NINDS Repository (RRID:SCR_004520) Copy   

•   Source: SciCrunch Registry

http://ki.se/ki/jsp/polopoly.jsp?d=29358&a=31596&l=en

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 29, 2016. So far there is only limited knowledge about possible genetic influences in acute spinal cord injuries (SCI). In this project DNA is collected prospectively from persons with SCI admitted to the acute SCI rehabilitation unit of the Karolinska University Hospital. Trauma is the cause of injury in a majority of the patients. Other causes of injury are spinal abscesses, tumors or spinal infarctions. The aim of the project is to create a sufficiently large DNA biobank with samples from 200-400 individuals from clinically well characterized patients to allow for studies of association between candidate genes and clinical outcome parameters.

Proper citation: KI Biobank - SCI (RRID:SCR_005849) Copy   

•   Source: SciCrunch Registry

http://www.harzing.com/pop.htm

Software program that allows researchers to perform citation analysis and calculate various impact metrics. It uses Google Scholar to obtain the raw citations, then analyzes these and presents the following statistics: * Total number of papers * Total number of citations * Average number of citations per paper * Average number of citations per author * Average number of papers per author * Average number of citations per year * Hirsch''s h-index and related parameters * Egghe''s g-index * The contemporary h-index * The age-weighted citation rate * Two variations of individual h-indices * An analysis of the number of authors per paper. The results are available on-screen and can also be copied to the Windows clipboard (for pasting into other applications) or saved to a variety of output formats (for future reference or further analysis). The Publish or Perish software is a Microsoft Windows application that can also be installed and used on Apple Mac OS X and GNU/Linux computers, with the aid of a suitable emulator such as Wine or CrossOver Mac.

Proper citation: Publish or perish (RRID:SCR_005968) Copy   

•   Source: SciCrunch Registry

http://epi.helmholtz-muenchen.de/kora-gen/index_e.php

KORA-gen is infrastructure to provide phenotypes, genotypes and biosamples for collaborative genetic epidemiological research. From all four surveys that have been conducted so far, the following biological material is on hand: genomic DNA, blood serum, blood plasma and EBV immortalized cell lines (form KORA S4 only). These have been extracted from blood samples and are stored in nitrogen tanks and -80 degrees C refrigerators. Genomic DNA from more than 18.000 adult subjects from Augsburg and the surrounding counties is available at present. So far, EBV immortalized cell lines from 1.600 participants are cultivated. To meet the manifold demands of researchers with genetic and molecular questions KORA-gen fulfills the following prerequisites for successful genetic-epidemiological research: * representative samples from the general population, * well characterized disease phenotypes and intermediate phenotypes, * information on environmental factors, * availability of genomic DNA, serum, plasma and urine, as well as EBV immortalized cell lines. In total, four population based health surveys have been conducted between 1984 and 2000 with 18000 participants in the age range of 25 to 74 years, and a biological specimen bank was established in order to enable scientists to perform epidemiologic research with respect to molecular and genetic questions. The KORA study center conducts regular follow-up investigations and has collected a wealth of information on sociodemography, general medical history, environmental factors, smoking, nutrition, alcohol consumption, and various laboratory parameters. This unique resource will be increased further by follow-up studies of the cohort. The assessment of statistical questions covers the definition of the study design and the calculation of statistical power. Furthermore, we offer assistance in data analysis. Kora-gen can be used by external partners. Interested parties can inform themselves interactively via internet about the available data and rules of access. The genotypic data base is a common resource to all partners.

Proper citation: KORA-gen (RRID:SCR_004510) Copy   

•   Source: SciCrunch Registry

http://dbmi.mc.vanderbilt.edu/research/dnadatabank.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. BioVU is a research resource providing a View into biology at the level of DNA and other important macromolecules. BioVU has two major components. The first is a repository of DNA samples (extracted from discarded blood samples) that are coded solely by a Research Unique Identifier (RUI) derived from the Medical Record Number (MRN) using a one-way hash function. This is a computer algorithm that creates a transformation of each MRN such that the resulting RUI (which is in this instance is a 512 byte identifier) is unique, and has the property that it is not possible to infer or compute the MRN that generated it. As of early 2009, over 50,000 DNA samples were in the biobank, with new samples being added at the rate of approximately 700 per week. The second component of the resource is the creation of a database known as the Synthetic Derivative which is a collection of de-identified information extracted from VUMC''s electronic clinical information systems, indexed by the same one-way RUI used to track samples, and with content changed by deletion or permutation of all identifiers contained within each record. The Synthetic Derivative search interface is available to Vanderbilt researchers via the StarBRITE research portal created and maintained by the Vanderbilt Institute for Clinical and Translational Research. This user interface enables investigators meeting protocol approval criteria and other user agreement requirements to receive protocol-specific sets of data derived from DNA samples and from the Synthetic Derivative., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Vanderbilt BioVU (RRID:SCR_004632) Copy   

•   Source: SciCrunch Registry

http://genetics.agrsci.dk/~bg/popgen/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on January 11, 2023. Software application that calculates a number of different genetic identities, phylogeny reconstructing measures, and distance reconstructing measures (entry from Genetic Analysis Software)

Proper citation: POPDIST (RRID:SCR_004904) Copy   

•   Source: SciCrunch Registry