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http://www.ariad.com/

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   

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http://www.cns.caltech.edu/

The Computation and Neural Systems degree program is organized jointly by the Division of Biology, the Division of Engineering and Applied Science, and the Division of Physics, Mathematics and Astronomy. It is the program''s objective to provide a broad knowledge of this inherently multidisciplinary field, while at the same time requiring an appropriate depth of knowledge in the particular field of the thesis research. For example, a student working on cooperative circuits for early visual processing will also develop an in-depth knowledge of the anatomy and electrophysiology of early visual areas and a knowledge of visual psychophysics. A student working on olfactory cortex electrophysiology and its simulation would include the study of concurrent processing and the ethology of olfaction, and the relevant knowledge of dynamical and collective systems. A student working on the theory of complex systems could study collective and statistical properties of physics as well as the anatomical and algorithmic structure of biological and applied networks. Sponsors: The computational and neural systems is funded by the California Institute of Technology.

Proper citation: Computational and Neural Systems (RRID:SCR_008316) Copy   

•   Source: SciCrunch Registry
  

http://lagan.stanford.edu

About the LAGAN Toolkit The LAGAN Tookit consists of four components: CHAOS CHAOS is a pairwise local aligner optimized for non-coding, and other poorly conserved regions of the genome. It uses both exact matching and degenerate seeds, and is able to find homology in the presence of gaps. LAGAN LAGAN is our highly parametrizable pairwise global alignment program. It takes local alignments generated by CHAOS as anchors, and limits the search area of the Needleman-Wunsch algorithm around these anchors; Multi-LAGAN Multi-LAGAN is a generalization of the pairwise algorithm to multiple sequence alignment. M-LAGAN performs progressive pairwise alignments, guided by a user-specified phylogenetic tree. Alignments are aligned to other alignments using the sum-of-pairs metric. Shuffle-LAGAN Shuffle-LAGAN is a novel glocal alignment algorithm that is able to find rearrangements (inversions, transpositions and some duplications) in a global alignment framework. It uses CHAOS local alignments to build a map of the rearrangements between the sequences, and LAGAN to align the regions of conserved synteny. The website uses scripts written by Alex Poliakov. The website was designed by Marina Sirota.

Proper citation: LAGAN (RRID:SCR_008558) Copy   

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http://www.strout.net/conical/

CONICAL is a C++ class library for building simulations common in computational neuroscience. Currently its focus is on compartmental modeling, with capabilities similar to GENESIS and NEURON. Future classes may support reaction-diffusion kinetics and more. A key feature of CONICAL is its cross-platform compatibility; it has been fully co-developed and tested under Unix, DOS, and Mac OS. Any C++ compiler which adheres to the emerging ANSI standard should be able to compile the CONICAL classes without modification. It is intended to encourage the rapid development of simulator software, especially on non-Unix systems where such software is sorely lacking. The present focus of the CONICAL library of C++ classes is compartmental modeling. A model neuron is built out of compartments, usually with a cylindrical shape. When small enough, these open-ended cylinders can approximate nearly any geometry, just as the stack of cylinders approximates a cone in the logo above. While any compartment has passive electrical properties (like a simple resistor-capacitor circuit), more interesting properties require the use of active ion channels whose conductance varies as a function of the time or membrane voltage. A standard Hodgkin-Huxley ion channel is included as one of the built-in CONICAL object types. Most of the voltage-gated ion channels in the literature can be directly implemented merely by setting the parameters of this class. For extensibility, this class is derived from several layers of more general classes. Connections between neurons can be implemented in several ways. For a gap junction (i.e., simple electrical connection), a passive current (or pair of currents, one in each direction) can be used. Synapses are more complex objects, but used in a similar fashion. The Alpha-function synapse is a very popular model of synaptic transmission, and is a basic CONICAL class. More complex (and realistic) synapses can be built using the Markov-model synapse. (A Markov model can be used on its own for other purposes as well.) In addition to classes directly related to neural modeling, CONICAL contains several other useful object types. These include a current injector, and a column-oriented output stream for storing data in table form.

Proper citation: Conical: The Computational Neuroscience Class Library (RRID:SCR_008318) Copy   

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http://www.lexisnexis.com

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   

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http://safcsupplysolutions.com

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. A business division of Sigma-Aldrich Corporation, focusing on providing custom manufactured products and specialized services used in the industrial development and manufacturing, including processes, that bring new drugs and new electronic products to market., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: SAFC (RRID:SCR_008554) Copy   

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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   

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http://molbiocore.ucsd.edu/

THIS RESOURCE IS NO LONGER IN SERVICE, documented on January 31, 2022. The UCSD CFAR/VMRF Molecular Biology Core (MBC) is a service core designed to facilitate and support HIV/AIDS research at the University of California San Diego (UCSD), the VA San Diego Healthcare System (VASDHCS), the Veterans Medical Research Foundation (VMRF), the UCSD Antiviral Research Center (AVRC), the Scripps Research Institute, and others in the San Diego HIV/AIDS research community. The MBC provides a variety of services, including DNA sequencing, viral DNA and RNA quantification, cDNA microarray analysis of herpesvirus expression, lentiviral vectors, RNAi design and synthesis, custom vector and plasmid design and construction, plasmids and other reagents of interest to HIV/AIDS research, shared access to computational biology software, and a variety of other services. The core is operated in association with the VMRF, the UCSD AIDS Research Institute (ARI), the VASDHCS, and the VA Research Center for AIDS and HIV Infection (RACHI). The VMRF/CFAR MBC is open to all UCSD, VA, and VMRF investigators as well as those from outside institutions. Keywords: Biology, Research, Medical, Molecular, DNA, Sequencing, Healthcare, RNA, DNA, cDNA, Microarray, Analysis, Herpesvirus, Expression, Lentiviral,

Proper citation: UCSD Center for AIDS Research Molecular Biology Core (RRID:SCR_008435) Copy   

•   Source: SciCrunch Registry
  

http://rocr.bioinf.mpi-sb.mpg.de/

ROCR is a package for evaluating and visualizing the performance of scoring classifiers in the statistical language R. It features over 25 performance measures that can be freely combined to create two-dimensional performance curves. Standard methods for investigating trade-offs between specific performance measures are available within a uniform framework, including receiver operating characteristic (ROC) graphs, precision/recall plots, lift charts and cost curves. ROCR integrates tightly with R''s powerful graphics capabilities, thus allowing for highly adjustable plots. Being equipped with only three commands and reasonable default values for optional parameters, ROCR combines flexibility with ease of usage. Performance measures that ROCR knows: Accuracy, error rate, true positive rate, false positive rate, true negative rate, false negative rate, sensitivity, specificity, recall, positive predictive value, negative predictive value, precision, fallout, miss, phi correlation coefficient, Matthews correlation coefficient, mutual information, chi square statistic, odds ratio, lift value, precision/recall F measure, ROC convex hull, area under the ROC curve, precision/recall break-even point, calibration error, mean cross-entropy, root mean squared error, SAR measure, expected cost, explicit cost. ROCR features: ROC curves, precision/recall plots, lift charts, cost curves, custom curves by freely selecting one performance measure for the x axis and one for the y axis, handling of data from cross-validation or bootstrapping, curve averaging (vertically, horizontally, or by threshold), standard error bars, box plots, curves that are color-coded by cutoff, printing threshold values on the curve, tight integration with Rs plotting facilities (making it easy to adjust plots or to combine multiple plots), fully customizable, easy to use (only 3 commands). ROCR can be used under the terms of the GNU General Public License. Running within R, it is platform-independent.

Proper citation: Classifier Visualization in R (RRID:SCR_008551) Copy   

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http://www.youtube.com/education?b=400

This resource is geared towards providing educational video in various fields. All the videos are compiled from various sources and are freely accessible. Some of the topics covered are: - Business - Education - Engineering - Fine Arts & Design - Health & Medicine - History - Humanities - Journalism & Media - Law - Literature - Mathematics - Science - Social Science Sponsors: This resource is supported by YouTube, LLC.

Proper citation: YouTube Educational Portal (RRID:SCR_008310) Copy   

•   Source: SciCrunch Registry
  

http://dove.embl-heidelberg.de/Blast2/

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. This portal let you search BLAST through the WU-BLAST2 Search Service provided by the Bork Group at EMBL. Sponsors: This resource is supported by EMBL., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: Bork Group's WU-BLAST2 Search Service at EMBL (RRID:SCR_008431) Copy   

•   Source: SciCrunch Registry
  

http://cprc.rcm.upr.edu/

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   

•   Source: SciCrunch Registry
  

http://cython.org/

Cython is a language that makes writing C extensions for the Python language as easy as Python itself. Cython is based on the well-known Pyrex, but supports more cutting edge functionality and optimizations. The Cython language is very close to the Python language, but Cython additionally supports calling C functions and declaring C types on variables and class attributes. This allows the compiler to generate very efficient C code from Cython code. This makes Cython the ideal language for wrapping external C libraries, and for fast C modules that speed up the execution of Python code. Sponsor. Google and Enthought funded Dag Seljebotn to greatly improve Cython integration with NumPy. Kurt Smith and Danilo Freitas were funded through the Google Summer of Code program to work on improved Fortran and C support respectively.

Proper citation: Cython C-Extensions for Python (RRID:SCR_008466) Copy   

•   Source: SciCrunch Registry
  

http://www.unil.ch/dafl

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   

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http://www.broadinstitute.org/scientific-community/science/programs/cancer/ultrasome

An efficient methodology for detecting and delineating gains and losses of chromosomal material in DNA copy-number data.

Proper citation: Ultrasome (RRID:SCR_008465) Copy   

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http://griffin.cbrc.jp/

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   

•   Source: SciCrunch Registry
  

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   

•   Source: SciCrunch Registry
  

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   

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http://www.sanger.ac.uk/cgi-bin/blast/submitblast/d_rerio

This Blast server offers searches against all D. rerio finished and unfinished clones in the Sanger sequencing pipeline. You can now also search the de novo assemblies generated from sequencing of one doubled haploid homozygous individual of each the AB and Tuebingen strain. Both fish were sequenced to ~40x coverage using Illumina GA sequencing technology and the sequences were assembled using Phusion2, resulting in a 1,33 Gb AB and a 1.48 Gb Tuebingen assembly. Due to the short reads and short inserts and no integration of physical or genetic map data, both assemblies are highly fragmented - with an N50 contig size of about 5kb. Mis-assembly errors may also be present in the contigs. Please note these assemblies are independent additions to the assemblies released by the zebrafish genome project and are intended to aid identification of polymorphisms between these two strains. Charity. Genome Research Limited is a charity registered in England with number 1021457

Proper citation: D. rerio Blast Server (RRID:SCR_008461) Copy   

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http://derisilab.ucsf.edu/

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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