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https://reich.hms.harvard.edu/software

XP-CLR (Chen et al. 2010) uses allele frequency differentiation at linked loci to detect selective sweeps. Source code and documentation are available.

Proper citation: XP-CLR (RRID:SCR_004961) Copy   

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http://www4.wiwiss.fu-berlin.de/bizer/d2r-server/

D2R Server is a tool for publishing relational databases on the Semantic Web. It enables RDF and HTML browsers to navigate the content of the database, and allows applications to query the database using the SPARQL query language. Data on the Semantic Web is modeled and represented in RDF. D2R Server uses a customizable D2RQ mapping to map database content into this format, and allows the RDF data to be browsed and searched the two main access paradigms to the Semantic Web. D2R Server''s Linked Data interface makes RDF descriptions of individual resources available over the HTTP protocol. An RDF description can be retrieved simply by accessing the resource''s URI over the Web. Using a Semantic Web browser like Tabulator (slides) or Disco, you can follow links from one resource to the next, surfing the Web of Data. The SPARQL interface enables applications to search and query the database using the SPARQL query language over the SPARQL protocol. Requests from the Web are rewritten into SQL queries via the mapping. This on-the-fly translation allows publishing of RDF from large live databases and eliminates the need for replicating the data into a dedicated RDF triple store. The latest source code is available from the project''s CVS repository and can be browsed online.

Proper citation: D2R Server - Publishing Relational Databases on the Semantic Web (RRID:SCR_004963) Copy   

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http://www.icpsr.umich.edu/icpsrweb/NACDA/studies/02744/version/1

Data set of a follow-up study (one of four Established Populations for Epidemiologic Studies of the Elderly - EPESE) that obtains information on four primary outcome variables (cognitive status, depression, functional status, and mortality) and four primary independent variables (social support, social class, social location, and chronic illness); and examines the relationships between social factors and chronic disease on the one hand and health outcomes on the other. This data set complements the other three sites providing a population which is both urban and rural and contains approximately equal numbers of black and white participants across a broad socioeconomic base. The Duke site was originally funded by the NIA Epidemiology, Demography and Biometry Program (EDBP) to complete seven waves of data collection (three in-person and four telephone interviews) in order to examine the health of a sample of 4,162 persons aged 65+, and factors that influence their health and use of health services. The cohort was originally interviewed in 1986/87 and followed annually for 6 years thereafter. The study design consisted of a random stratified household sample with an over-sampling of blacks. Questionnaire topics include the following: Demographics, Alcohol Use, Independence, Health condition, Cognition, Personal mastery, Health Service Utilization, Activity of daily living, Social Support, Hearing and Vision, Incontinence, Social Interaction, Weight and Height, Smoking, Religion, Nutrition, Life Satisfaction, Self Esteem, Sleep, Medications, Economic Status, Depression, Life Changes, Blood pressure. National Death Index files have been searched and death certificates obtained for the members of this study. Sample members have been matched with Medicare Part A files to obtain information on hospitalizations, and will be matched on Medicare Part B (outpatient) files. Data from the first wave of the survey is in the public domain and can be obtained from NACDA or from the National Archives, Center for Electronic Records in Washington, DC. * Dates of Study: 1996-1997 * Study Features: Longitudinal, Oversampling * Sample Size: 1986-1988: 4,162 Links: * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/02744 * National Archives: http://www.archives.gov/research/electronic-records/

Proper citation: Piedmont Health Survey of the Elderly (RRID:SCR_006349) Copy   

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https://neuinfo.org/mynif/search.php?q=nlx_149462&t=indexable&list=cover&nif=nlx_144509-1

A virtual database that indexes both BioNOT for negation data, and the Resource Discovery Pipeline: an automated resource discovery and semi-automated type characterization with text-mining scripts that facilitate curation team efforts to discover, integrate and display new content. This virtual database currently indexes the following resources: * BioNOT, http://snake.ims.uwm.edu/bionot/index.php?searchterm=mecp2+autism&submit=Search * Resource Discovery Pipeline, http://lucene1.neuinfo.org/nif_resource/current/

Proper citation: Integrated Auto-Extracted Annotation (RRID:SCR_005892) Copy   

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http://www.t1diabetes.nih.gov/T1D-PTP/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 22, 2016. Investigator access is provided to the established facilities and expertise needed to extend, enhance and validate preclinical studies of promising new therapeutics in cases where additional preclinical testing is needed to validate potential therapies under disease-specific conditions and in multiple animal models before therapeutics can enter the Type 1 Diabetes Rapid Access to Intervention Development (T1D-RAID) development pipeline. The T1D-RAID program provides resources for pre-clinical development of drugs, natural products, and biologics that will be tested as new therapeutics in type 1 diabetes clinical trials. The T1D-RAID program is not currently accepting applications. The T1D-PTP program currently supports two contracts, which are separate from each other and from the T1D-RAID NCI contract resources, to assist in preclinical development of therapeutics for T1D: * Agents to be tested for Preclinical Efficacy in Prevention or Reversal of Type 1 Diabetes in Rodent Models. Type 1 Diabetes Preclinical Testing Program (T1D-PTP) (NOT-DK-09-006) * Needs for Preclinical Efficacy Testing of Promising Agents to Prevent or Reverse Diabetic Complications (NOT-DK-09-009) The T1D-RAID and T1D-PTP are programs intended to remove the most common barriers to progress in identification and development of new therapies for Type 1 Diabetes. The common goal of these programs is to support and provide for the preclinical work necessary to obtain proof of principle establishing that a new molecule or novel approach will be a viable candidate for expanded clinical evaluation.

Proper citation: Type 1 Diabetes Preclinical Testing Program (RRID:SCR_006861) Copy   

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http://www.zv.uni-leipzig.de/en/

Proper citation: University of Leipzig; Saxony; Germany (RRID:SCR_004960) Copy   

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http://clip.med.yale.edu/SHM

A targeting model that defines where mutations occur (by specifying the relative rates at which DNA motifs in the Ig sequence are mutated), and a nucleotide substitution model that defines the resulting mutation (by specifying the probability of each base mutating to each of the other three possibilities as a function of the surrounding bases).

Proper citation: Models of SHM Targeting and Substitution (RRID:SCR_005250) Copy   

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http://www.cs.tau.ac.il/~shlomito/tissue-net/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. Network visualizations in which the expression and predicted flux data are projected over the global human network. These network visualizations are accessible through the supplemental website using the publicly available Cytoscape software (Cline, Smoot et al. 2007). Since many high degree nodes exist in the network, special layouts are required to produce network visualizations that are readily interpretable. To this end we produced network visualizations in which hub nodes are repeated multiple times and hence layouts with a small number of edge crossings can be generated. Contains entries for brain compartments and brain pathways.

Proper citation: Network-based Prediction of Human Tissue-specific Metabolism (RRID:SCR_007392) Copy   

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http://www.unipi.it/english/

Proper citation: University of Pisa; Pisa; Italy (RRID:SCR_006616) Copy   

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http://www.meduniwien.ac.at/homepage/1/

Proper citation: Medical University of Vienna; Vienna; Austria (RRID:SCR_005007) Copy   

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http://medicine.yale.edu/index.aspx

Proper citation: Yale School of Medicine; Connecticut; USA (RRID:SCR_006339) Copy   

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http://www.physionet.org/physiobank/database/sleep-edf/

Sleep EEG dataset from 8 subjects in European Data Format (EDF) including original recordings and their hypnograms as described in B Kemp, AH Zwinderman, B Tuk, HAC Kamphuisen, JJL Obery��. Analysis of a sleep-dependent neuronal feedback loop: the slow-wave microcontinuity of the EEG. IEEE-BME 47(9):1185-1194 (2000). The recordings were obtained from Caucasian males and females (21 - 35 years old) without any medication; they contain horizontal EOG, FpzCz and PzOz EEG, each sampled at 100 Hz. The sc* recordings also contain the submental-EMG envelope, oro-nasal airflow, rectal body temperature and an event marker, all sampled at 1 Hz. The st* recordings contain submental EMG sampled at 100 Hz and an event marker sampled at 1 Hz. The 4 sc* recordings were obtained in 1989 from ambulatory healthy volunteers during 24 hours in their normal daily life, using a modified cassette tape recorder. The 4 st* recordings were obtained in 1994 from subjects who had mild difficulty falling asleep but were otherwise healthy, during a night in the hospital, using a miniature telemetry system with very good signal quality.

Proper citation: Sleep-EDF Database (RRID:SCR_006976) Copy   

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http://alchemy.sourceforge.net/

ALCHEMY is a genotype calling algorithm for Affymetrix and Illumina products which is not based on clustering methods. Features include explicit handling of reduced heterozygosity due to inbreeding and accurate results with small sample sizes. ALCHEMY is a method for automated calling of diploid genotypes from raw intensity data produced by various high-throughput multiplexed SNP genotyping methods. It has been developed for and tested on Affymetrix GeneChip Arrays, Illumina GoldenGate, and Illumina Infinium based assays. Primary motivations for ALCHEMY''s development was the lack of available genotype calling methods which can perform well in the absence of heterozygous samples (due to panels of inbred lines being genotyped) or provide accurate calls with small sample batches. ALCHEMY differs from other genotype calling methods in that genotype inference is based on a parametric Bayesian model of the raw intensity data rather than a generalized clustering approach and the model incorporates population genetic principles such as Hardy-Weinberg equilibrium adjusted for inbreeding levels. ALCHEMY can simultaneously estimate individual sample inbreeding coefficients from the data and use them to improve statistical inference of diploid genotypes at individual SNPs. The main documentation for ALCHEMY is maintained on the sourceforge-hosted MediaWiki system. Features * Population genetic model based SNP genotype calling * Simultaneous estimation of per-sample inbreeding coefficients, allele frequencies, and genotypes * Bayesian model provides posterior probabilities of genotype correctness as quality measures * Growing number of scripts and supporting programs for validation of genotypes against control data and output reformating needs * Multithreaded program for parallel execution on multi-CPU/core systems * Non-clustering based methods can handle small sample sets for empirical optimization of sample preparation techniques and accurate calling of SNPs missing genotype classes ALCHEMY is written in C and developed on the GNU/Linux platform. It should compile on any current GNU/Linux distribution with the development packages for the GNU Scientific Library (gsl) and other development packages for standard system libraries. It may also compile and run on Mac OS X if gsl is installed.

Proper citation: ALCHEMY (RRID:SCR_005761) Copy   

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http://clinicaltrials.gov/ct2/show/NCT00248651

Multi-center, randomized, placebo-controlled trial evaluating the tricyclic antidepressant, amitriptyline and the selective serotonin reuptake inhibitor (SSRI), escitalopram to placebo in patients with functional dyspepsia. The purpose of this study is to determine whether amitriptyline and escitalopram are more efficacious than placebo in relief of the symptoms of functional dyspepsia, adjusting for psychological and psychiatric co-morbidities.

Proper citation: Functional Dyspepsia Treatment Trial (RRID:SCR_006691) Copy   

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http://www.ifs.org.uk/ELSA

An interdisciplinary data resource on health, economic position and quality of life as people age. Longitudinal multidisciplinary data from a representative sample of the English population aged 50 and older have been collected. Both objective and subjective data are collected relating to health and disability, biological markers of disease, economic circumstance, social participation, networks and well-being. Participants are surveyed every two years to see how people''s health, economic and social circumstances may change over time. One of the study''s aims is to determine the relationships between functioning and health, social networks, resources and economic position as people plan for, move into and progress beyond retirement. It is patterned after the Health and Retirement Study, a similar study based in the United States. ELSA''s method of data collection includes face-to-face interview with respondents aged 50+; self-completion; and clinical, physical, and performance measurements (e.g., timed walk). Wave 2 added questions about quality of health care, literacy, and household consumption, and a visit by a nurse to obtain anthropometric, blood pressure, and lung function measurements, as well as saliva and blood samples, and to record results from tests of balance and muscle strength. Another new aspect of Wave 2 is the ''Exit Interview'' carried out with proxy informants to collect data about respondents who have died since Wave 1. This interview includes questions about the respondents'' physical and psychological health, the care and support they received, their memory and mood in the last year of their life, and details of what has happened to their finances after their death. Wave 3 data added questions related to mortgages and pensions. The intention is to conduct interviews every 2 years, and to have a nurse visit every 4 years. It also is envisioned that the ELSA data will ultimately be linked to available administrative data, such as death registry data, a cancer register, NHS hospital episodes data, National Insurance contributions, benefits, and tax credit records. The survey data are designed to be used for the investigation of a broad set of topics relevant to understanding the aging process. These include: * health trajectories, disability and healthy life expectancy; * the determinants of economic position in older age; * the links between economic position, physical health, cognition and mental health; * the nature and timing of retirement and post-retirement labour market activity; * household and family structure, social networks and social supports; * patterns, determinants and consequences of social, civic and cultural participation; * predictors of well-being. Current funding for ELSA will extend the panel to 12 years of study, giving significant potential for longitudinal analyses to examine causal processes. * Dates of Study: 2002-2007 * Study Features: Longitudinal, International, Anthropometric Measures * Sample Size: ** 2000-2003 (Wave 1): 12,100 ** 2004-2005 (Wave 2): 9,433 ** 2006-2007 (Wave 3): 9,771 ** 2008-2009 (Wave 4): underway Links * Economic and Social Data Service (ESDS): http://www.esds.ac.uk/longitudinal/about/overview.asp * ICPSR: http://www.icpsr.umich.edu/icpsrweb/ICPSR/studies/00139#scope-of-study

Proper citation: English Longitudinal Study of Ageing (RRID:SCR_006727) Copy   

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http://www.unisa.it/english/index

Proper citation: University of Salerno; Salerno; Italy (RRID:SCR_007853) Copy   

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http://www.neuro.fsu.edu/

The Program in Neuroscience is an independent research and graduate training program at Florida State University, which is a Carnegie Research I university. The Program includes faculty from the departments of Biological Science, Biomedical Science, Mathematics, and Psychology. Its objective is to promote interdisciplinary basic research into neural processes, including the biological mechanisms underlying behavior, and to provide advanced graduate training leading to the Ph.D. degree in Neuroscience. The program maintains specialized research support services and personnel, and provides special courses and symposia on contemporary neuroscience issues. Each semester the program brings to Florida State prominent neuroscientists who give colloquia and hold informal discussions with graduate students and faculty. Neuroscience, the study of brain and nervous system function, encompasses many of the unanswered questions about the nature of humans and other species. It stakes out a territory along the frontier of human knowledge where research can make a real difference to understanding. Traditionally, the primary emphasis of the FSU program has been on sensory processes. This focus is now supplemented by research and instruction in the biophysics and electrophysiology of excitable cells, neurotransmitter and hormone action, neural development and plasticity, circadian rhythms, feeding and regulatory processes, and the genetic bases of neurobiology and behavior. Broad interdisciplinary training is emphasized in the early years so that students develop skills in approaching research problems with multiple levels of analysis, from molecular to behavioral.

Proper citation: Florida State University Program in Neuroscience (RRID:SCR_007451) Copy   

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http://omicsoft.com/osa/

A fast and accurate alignment tool for RNA-Seq data.

Proper citation: Omicsoft Sequence Aligner (RRID:SCR_005270) Copy   

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http://www.hunter.cuny.edu/

Proper citation: Hunter College; New York; USA (RRID:SCR_005707) Copy   

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http://bc02.iis.sinica.edu.tw/gobu/manual/index.html

Gene Ontology Browsing Utility (GOBU) (GOBU) is a Java-based software program for integrating biological annotation catalogs under an extendable software architecture. Users may interact with the Gene Ontology and user-defined hierarchy data of genes, and then use its plugins to (and not limited to) (1) browse the GO hierarchy with user defined data, (2) browse GO-oriented expression levels in the user data, (3) compute GO enrichment, and/or (4) customize data reporting. A set of classes and utility functions has been established so that a customized program can be made as a plugin or a command-line tool that programmically manipulate the Gene Ontology and specified user data. See the source code repository for examples. Reference Lin WD, Chen YC, Ho JM, Hsiao CD. GOBU: Toward an Integration Interface for Biological Objects. Journal of Information Science and Engineering. 2006 22(1):19-29. Platform: Windows compatible, Mac OS X compatible, Linux compatible, Unix compatible

Proper citation: Gene Ontology Browsing Utility (GOBU) (RRID:SCR_005662) Copy   

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