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OMPC aims to enable reuse of the huge open and free code base of MATLAB on a free and faster growing Python platform. Running Python and MATLAB in a single interpreter avoids issues with running two separate applications. Python adds general purpose programming libraries to the convenient syntax of the language of technical computing. OMPC is not an interpreter, it lets Python to do the work. This means that if Python gets faster OMPC gets faster too. OMPC translates the m-files preserving the structure of the original programs as much as possible. Although OMPC comes with a library that emulates the features of numerical array of MATLAB there is nothing that will stop you from running the translated code the way you like it. This means that you could run the OMPC generated code on IronPython, Jython, PyPy or whatever else if you write your own numerical class. Sponsors: This resource is supported by RIKEN Brain Science Institute.
Proper citation: An Open-Source MATLAB-to-Python Compiler (RRID:SCR_008409) Copy
http://faculty.washington.edu/chudler/ehc.html
This web site focuses on neuroscience, the study of the nervous system. Links on this page are limited to those Dr. Chundler finds to be the most interesting and useful.
Proper citation: Eric H. Chundlers Links (RRID:SCR_008328) Copy
The project began as a pilot study to identify inherited genetic susceptibility to prostate and breast cancer. CGEMS has developed into a robust research program involving genome-wide association studies (GWASs) for a number of cancers to identify common genetic variants that affect a person''s risk of developing cancer. In collaboration with extramural scientists, NCI''s Division of Cancer Epidemiology and Genetics (DCEG) has carried out genome-wide scans for breast, prostate, pancreatic, and lung cancers, while a GWAS of bladder cancer is currently underway. By making the data available to both intramural and extramural research scientists, as well as those in the private sector through rapid posting, NIH can leverage its resources to ensure that the dramatic advances in genomics are incorporated into rigorous population-based studies. Ultimately, findings from these studies may yield new preventive, diagnostic, and therapeutic interventions for cancer. Sponsors: This resource is supported by the U.S. National Institues Of Health.
Proper citation: CGEMS (RRID:SCR_008445) Copy
Wheaton Industries Inc. is a leading marketer, manufacturer and re-packager of containers, laboratory ware, instrumentation and associated products and services sold principally to customers in the general laboratory, life sciences, and diagnostics and reagent / chemicals packaging markets. Our products and services are marketed and sold globally through two divisions. The laboratory research products are sold through Wheaton Science Products, and the packaging products are sold through Wheaton Science Packaging.
Proper citation: Wheaton Industry Inc (RRID:SCR_008565) Copy
This site is designed for researchers and students who want a quick way to generate random numbers or assign participants to experimental conditions. Research Randomizer can be used in a wide variety of situations, including psychology experiments, medical trials, and survey research. The program uses a JavaScript random number generator to produce customized sets of random numbers. Since its release in 1997, Research Randomizer has been used to generate number sets over 10.7 million times. This service is part of Social Psychology Network and is fast, free, and runs with any recent web browser as long as JavaScript isn''t disabled. Research Randomizer is a free service offered to students and researchers interested in conducting random assignment and random sampling. By using this service, you agree to abide by the SPN User Policy and to hold Research Randomizer and its staff harmless in the event that you experience a problem with the program or its results. Although every effort has been made to develop a useful means of generating random numbers, Research Randomizer and its staff do not guarantee the quality or randomness of numbers generated. Any use to which these numbers are put remains the sole responsibility of the user who generated them. What are the system requirements needed to run Research Randomizer? This program works best with Firefox and other recent web browsers. If you''re using a browser that came with America Online, or older browsers made prior to 2003, you may experience some difficulties with Research Randomizer. You may also not be able to use Research Randomizer with some limited-function browsers that do not fully support JavaScript, such as the Opera broswer used on certain game consoles. We would suggest that you update to a fairly recent, fully- functional stand-alone browser. How do I know what browser I am using? The easiest way to find this out is to click Help on the pulldown menu at the top of the screen. One of the options should be About Mozilla Firefox, About Internet Explorer, About Netscape, or something similar. Selecting this option will open a window that displays the name, version number, and copyright date of your browser. How does Research Randomizer generate its numbers? Research Randomizer uses the Math.random method within the JavaScript programming language to generate its random numbers for all modern web browsers. If you are using an older version of Microsoft Internet Explorer or Netscape Navigator (that is prior to version 4.0 of either), Research Randomizer uses an adaptation of the Central Randomizer by Paul Houle. Note that Research Randomizer no longer supports much-older browsers by other vendors (e.g., Mosaic). Who designed Research Randomizer? The original idea and programming for Research Randomizer came from Geoffrey C. Urbaniak in 1997. Research Randomizer was then jointly developed with Scott Plous, webmaster of Social Psychology Network, and online tutorials were added to the main program. In 1999 the site was redesigned with the assistance of Mike Lestik, in 2003 Mike Lestik added the download function, and in 2007 Mike Lestik and Scott Plous redesigned the site and added new content.
Proper citation: Research Randomizer (RRID:SCR_008563) Copy
Cambridge, Massachusetts-based biotechnology company focused on cancer. Focus areas are blood cancers and solid tumors. Compounds: ponatinib, AP26113, ridaforolimus and AP1903., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: ARIAD (RRID:SCR_008559) Copy
A commercial software provider designed for legal, risk management, corporate, government, law enforcement, accounting, and academic markets. Sponsors: This resource is Reed Elsevier, Inc. Keywords: Workflow, Professional, Legal, Risk, Management, Corporate, Government, Law, Enforcement, Accounting, Academic, Technology, Information,
Proper citation: LexisNexis (RRID:SCR_008433) Copy
http://www.ieee.org/portal/site/iportals?WT.mc_id=hplogo_upleft
IEEE is the worlds largest professional association advancing innovation and technological excellence for the benefit of humanity. IEEE and its members inspire a global community to innovate for a better tomorrow through its highly cited publications, conferences, technology standards, and professional and educational activities. IEEE is the trusted voice for engineering, computing and technology information around the globe. Through its global membership, IEEE is a leading authority on areas ranging from aerospace systems, computers and telecommunications to biomedical engineering, electric power and consumer electronics among others. Members rely on IEEE as a source of technical and professional information, resources and services. To foster an interest in the engineering profession, IEEE also serves student members in colleges and universities around the world. Other important constituencies include prospective members and organizations that purchase IEEE products and participate in conferences or other IEEE programs. IEEE has: -more than 375,000 members in more than 160 countries; 45 percent of whom are from outside the United States -more than 80,000 student members -329 sections in ten geographic regions worldwide -1,860 chapters that unite local members with similar technical interests -1,789 student branches in 80 countries -483 student branch chapters at colleges and universities -390 affinity groups -- IEEE Affinity Groups are non-technical sub-units of one or more Sections or a Council. The Affinity Group patent entities are Consultants'' Network, Graduates of the Last Decade (GOLD), Women in Engineering (WIE) and Life Members (LM) IEEE''s core purpose is to foster technological innovation and excellence for the benefit of humanity. It will be essential to the global technical community and to technical professionals everywhere, and be universally recognized for the contributions of technology and of technical professionals in improving global conditions., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.
Proper citation: IEEE (RRID:SCR_008314) Copy
TRACK-HD is a multi-centermulti-national prospective, observational biomarker study of premanifest and early stage HD with no experimental treatment. Objectives: - determine what combination of measures is the most sensitive for detecting change over the natural course of premanifest and early HD - to validate these as potential outcome measures for use in future therapeutic trials Design: - focused on intensive battery of novel assessments - extensive annual assessments - dynamic and fluid protocol - robust evidence-based measures TRACK-HD is a major new international study of Huntingtons disease. It aims to be the most comprehensive study of premanifest and early HD, and will define the best combination of assessments to be used in clinical trials of disease-modifying treatments in HD. TRACK-HD began in January 2008 and involves 360 subjects at 4 sites internationally. Sponsors: This resource is supported by The UK Medical Research Council (MRC), CHDI Foundation, Inc., The Euro-HD Network, The Wellcome Trust, The Department of Health, The Huntingtons Disease Association, and The Brain Research Trust. Keywords: Biomarker, Experimental, Treatment, Research, Therapeutic, Trail, Hunginton''s, Disease, Health,
Proper citation: Track-HD (RRID:SCR_008397) Copy
http://ipmb.sinica.edu.tw/affy/
Affymetrix Gene Expression Service Lab, AGESL was established by IPMB, IMB and IBS, Academia Sinica and opened for service in June 2004. The lab provides a full service from quality control of customer-provided RNA samples to raw data acquisition, including Affymetrix recommended QC procedures, cDNA synthesis, in vitro transcription, fragmentation, hybridization, washing, staining and scanning. Sponsors: This resource is supported by Affymetrix, Inc. Keywords: Gene, Expression, Service, Laboratory, RNA, Data, Synthesis, cDNA, In vitro, Transcription, Fragmentation, Hybrdization, Washing, Staining, Scanning,
Proper citation: Affymetrix Gene Expression Service Lab (RRID:SCR_008396) Copy
http://salilab.org/modeller/modeller.html
Software tool as Program for Comparative Protein Structure Modelling by Satisfaction of Spatial Restraints. Used for homology or comparative modeling of protein three dimensional structures. User provides alignment of sequence to be modeled with known related structures and MODELLER automatically calculates model containing all non hydrogen atoms.
Proper citation: MODELLER (RRID:SCR_008395) Copy
http://www.fa-petition.org/en/attivita/progetti2008.html
The aim of this resource is to facilitate and promote, even through fund-raising, the scientific research for the treatment of Friederich''s Ataxia. The mission of this portal is to: - To distribute information to the people affected by the disease and to make the general population aware. - Promote, fund and support the diagnosis, research, cure and potential treatments. - Promote the cooperation with other voluntary associations both national and international. Sponsors: This resource is supported by the RUDI Committee. Keywords: Research, Diagnosis, Cure, Treatment, Disease, Scientific, Friederich''s Ataxia,
Proper citation: ATASSIA DI FRIEDREICH - PROGETTI 2006 (RRID:SCR_008391) Copy
http://grey.colorado.edu/emergent
emergent is a comprehensive, full-featured neural network simulator that allows for the creation and analysis of complex, sophisticated models of the brain in the world. With an emphasis on qualitative analysis and teaching, it also supports the workflow of professional neural network researchers. Its high level drag-and-drop programming interface, built on top of a scripting language that has full introspective access to all aspects of networks and the software itself, allows one to write programs that seamlessly weave together the training of a network and evolution of its environment without ever typing out a line of code. Networks and all of their state variables are visually inspected in 3d, allowing for a quick visual regression of network dynamics and robot behavior. This same 3d world sports a highly accurate Newtonian physics simulation, allowing you to create rich robotics simulations (for example, a car). As a direct descendant of PDP (1986) and PDP (1999), emergent has been in development for decades. In the most recent versions available strive to distill it down to its essential elements. Those that take the time to learn the best practices will be rewarded with the ability to create and understand the most complicated neural models ever published.
Proper citation: Emergent (RRID:SCR_008500) Copy
Center for the study of non-human primates. Its mission is the study and use of non-human primates as models for studies of social and biological interactions and for the discovery of methods of prevention, diagnosis and treatment of diseases that afflict humans. Through the stewardship of three unique facilities—Cayo Santiago Field Station, Sabana Seca Field Station, and the Laboratory of Primate Morphology supports a diverse range of research programs that enhance understanding of primate biology and behavior, with direct applications in biomedical and translational research.
Proper citation: Caribbean Primate Research Center (RRID:SCR_008345) Copy
The Lausanne Genomics Technologies Facility (GTF) is a genomic technologies core laboratory serving the Lausanne and Lemanic region research community. It is housed in and administered by the Center for Integrative Genomics. The GTF offers a range of microarrays services, including : providing access to the instrumentation and the consumables that are required for the use of the pre-printed oligonucleotide microarrays available from Affymetrix and Illumina as well as miRNA gene microarrays from Agilent Technologies providing access to and supporting applications using the Illumina Genome Analyzer 2 ultra high throughput DNA sequencing platform providing access to the instrumentation and the consumables that are required for performing quantitative real-time PCR analyses using the Applied Biosystems 7900HT Sequence Detection System. providing bioinformatics support and consultation services at the stages of experimental design, data collection and storage, image analysis and data analysis acting as a center of experience, expertise and training in microarray and quantitative PCR technologies and methodologies. Laboratory space and computer workstations are available to users wanting to perform the experiments and/or analyses in the facility. The GTF also acts as an information clearing house for the user community by providing a forum for the sharing of methods, protocols and experience generated by the GTF and community scientists using microarray and quantitative PCR technology investigating and implementing, when appropriate, microarray-based methods for applications other than gene expression monitoring (e.g. SNP detection) participating in the evaluation of new RNA expression profiling and nucleic hybridization detection technologies as they develop and incorporate the appropriate technologies into the services offered by the facility
Proper citation: Lausanne Genomic Technologies Facility (RRID:SCR_008468) Copy
http://amser.org./index.php?P=AMSER--About
AMSER is a portal of educational resources and services built specifically for use by those in Community and Technical Colleges but free for anyone to use. AMSER provides links to resources for faculty, staff, librarians, students and others for use in both educational settings or in their pursuit of life long learning. Sponsors: AMSER is funded by the National Science Foundation (NSF) as part of the National Science Digital Library, and is being created by a team of project partners led by Internet Scout.
Proper citation: Applied Math and Science Education Repository (RRID:SCR_008501) Copy
Griffin (G-protein-receptor interacting feature finding instrument) is a high-throughput system to predict GPCR - G-protein coupling selectively with the input of GPCR sequence and ligand molecular weight. This system consists of two parts: 1) HMM section using family specific multiple alignment of GPCRs, 2) SVM section using physico-chemical feature vectors in GPCR sequence. G-protein coupled receptors (GPCR), which is composed of seven transmembrane helices, play a role as interface of signal transduction. The external stimulation for GPCR, induce the coupling with G-protein (Gi/o, Gq/11, Gs, G12/13) followed by different kinds of signal transduction to inner cell. About half of distributed drugs are intending to control this GPCR - G-protein binding system, and therefore this system is important research target for the development of effective drug. For this purpose, it is necessary to monitor, effectively and comprehensively, of the activation of G-protein by identifying ligand combined with GPCR. Since, at present, it is difficult to construct such biochemical experiment system, if the answers for experimental results can be prepared beforehand by using bioinformatics techniques, large progress is brought to G-protein related drug design. Previous works for predicting GPCR-G protein coupling selectivity are using sequence pattern search, statistical models, and HMM representations showed high sensitivity of predictions. However, there are still no works that can predict with both high sensitivity and specificity. In this work we extracted comprehensively the physico-chemical parameters of each part of ligand, GPCR and G-protein, and choose the parameters which have strong correlation with the coupling selectivity of G-protein. These parameters were put as a feature vector, used for GPCR classification based on SVM.
Proper citation: G protein receptor interaction feature finding instrument (RRID:SCR_008343) Copy
http://www.cff.org/treatments/Pipeline/
The Cystic Fibrosis Foundation has built a dynamic pipeline for the development of more new potential cystic fibrosis (CF) therapies than ever before. To treat a complex disease like CF, therapies must target problems in the airways and the digestive system. In the CF drug development pipeline, there also are promising new therapies designed to rectify the cause of CF a faulty gene and/or its faulty protein product. Cystic fibrosis is an inherited chronic disease that affects the lungs and digestive system of about 30,000 children and adults in the United States (70,000 worldwide). A defective gene and its protein product cause the body to produce unusually thick, sticky mucus that: clogs the lungs and leads to life-threatening lung infections; and obstructs the pancreas and stops natural enzymes from helping the body break down and absorb food. In the 1950s, few children with cystic fibrosis lived to attend elementary school. Today, advances in research and medical treatments have further enhanced and extended life for children and adults with CF. Many people with the disease can now expect to live into their 30s, 40s and beyond.
Proper citation: Drug Development Pipeline (RRID:SCR_008464) Copy
http://www.xiphophorus.txstate.edu/
Supplier of xiphophorus (platyfish or swordtails) from pedigreed parental lines, representing variety of species. In addition to supplying strains and providing consultation on husbandry and genetic questions, the XGSC produces custom interspecies hybrids (both first generation F1, and backcross hybrid generation BC1) for a variety of projects.
Proper citation: Xiphophorus Genetic Stock Center (RRID:SCR_008340) Copy
The DeRisi Lab focuses on genomic approaches to the study of infectious disease. Specifically, we are studying Plasmodium falciparum, the causative agent of the most deadly form of human malaria. We are also involved in a major effort for the discovery of new viral pathogens associated with diseases of unknown etiology. Software tools developed in the lab include: HMMSplicer discovers splice sites in high throughput sequencing datasets without using gene models. HMMSplicer can also be used to find non-canonical junctions as well. HMMSplicer was benchmarked on publickly available A. thaliana, H. sapiens, and P. falciparum datasets and performs well on all genomes. Information about the datasets tested, including the exact command parameters and the final results, is provided. HMMSplicer is implemented in Python and is freely available for all. VersaCount is a simple application to assist with the counting of cells by microscopy. When used with a numeric keypad, it can significantly increase counting efficiency when compared with a traditional clicker. Although it was designed for malaria work, it can be customized for a wide variety of cell counting applications. VersaCount was written by Charlie Kim. ExpressionNet is a program written by Jingchun Zhu that uses Bayesian network learning algorithms to explore relationships among random variables to generate network models. The software has been used to study the transcriptional response to environmental perturbations in budding yeast. Details of the program and the study of yeast transcription using Bayesian Networks was published in PLoS ONE. DNA microarrays may be used to identify microbial species present in environmental and clinical samples. However, automated tools for reliable species identification based on observed microarray hybridization patterns are lacking. We present an algorithm, E-Predict, for microarray-based species identification. ArrayOligoSelector (AOS) is an open source program developed by Jingchun Zhu for the purpose of systematically designing gene-specific long oligonucleotide probes for entire genomes. For each open reading frame, the program optimizes oligo selection based upon several parameters, including uniqueness, complexity, secondary structure, GC content, and 3'' end proximity. AOS also is hosted at SourceForge. This site contains documentation and a user-friendly how-to. ArrayMaker 2 provides high performance robotic control of microarrayer robots with an incredibly intuitive, easy to use interface. ArrayMaker 2 is optimized for use with the new generation of ultra fast linear servo driven arrayers, yet it is backwards compatible with the original MGuide style of ball-screw driven arrayers.
Proper citation: DeRisi Lab (RRID:SCR_008581) Copy
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