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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   

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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   

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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   

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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   

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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   

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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   

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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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http://www.nature.com/nature/supplements/collections/

This website provides summary collections written for a broad audience highlighting some of the significant advances in a particular field. These are not scientific articles although they may reference scientific work. Sponsors: This resource is supported by Nature.com

Proper citation: Nature Supplements: Collections archive (RRID:SCR_008337) Copy   

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http://www.ini.uzh.ch/

The mission of the Institute is to discover the key principles by which brains work and to implement these in artificial systems that interact intelligently with the real world. The Institute of Neuroinformatics is built of many people covering a wide range of disciplines and research areas. The major research projects and areas are listed below. - Behavior and Cognition: At the Institute of Neuroinformatics researchers investigate in Behavior and Cognition on various levels, ranging from neuronal circuit models of learning and adaptation over psychophysical experiments for color constancy up to modeling complex behavioral tasks such as exploration and goal-directed navigation. - Computation in Neural Circuits: By examining the brains of cats, rats and monkeys, and by making simulations of the cortex, INI hopes to learn how this circuit performs such widely different tasks. This knowledge might lead to advances in how computers are designed, and will certainly lead to advances in the subtlety and power of medical neuroscience. - Neurotechnologies: INI aims to harness the principles of biological computation, which can be expected to have a major impact on the technology market as autonomous intelligence pervades equipment, vehicles, buildings, utilities and clothing. Sponsors: INI is supported by European Union (EU), Gerbert Ruf Stiftung, Neuroscience Center (ZNZ), Swiss Confederation (KTI), Swiss Federal Institute of Technology Zurich (ETH), Swiss National Science Foundation (SNF), University of Zurich (UZH), and VW Stiftung

Proper citation: Institute of Neuroinformatics (RRID:SCR_008331) Copy   

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http://www.rulesbasedmedicine.com/

Rules-Based Medicine (RBM) uses proprietary Multi-Analyte Profiling (MAP) technology to make life science research and drug and diagnostic development programs more efficient and effective. Whether measuring hundreds of biomarkers or simply a few, our approach provides reproducible, quantitative immunoassay data from a small sample volume at a cost-effective price. RBM is CLIA certified and supports GLP studies. * Quality: All immunoassays are validated to clinical laboratory standards. This means complete validation for the clinic, not fit for purpose validation which at RBM means inferior validation. Learn More * Content: We have the most comprehensive menu of biomarker immunoassays available. * Small Sample Volumes: Multiplexing provides you with more data using a smaller sample volume. * Cost Effective: Multiplexing and automation combine to deliver high quality data at reasonable prices. * Ease of use: Ship us your samples and get results within 2 weeks. Rules-Based Medicine (RBM), the worlds leading multiplexed biomarker testing laboratory, provides comprehensive protein biomarker products and services based on its Multi-Analyte Profiling (MAP) technology platform. RBMs biomarker testing service provides pre-clinical and clinical researchers with reproducible, quantitative, multiplexed immunoassay data for hundreds of proteins in a cost-effective manner, from a small sample volume and from multiple species. Our biomarker testing laboratory is CLIA certified and supports GLP studies. Most diseases and drug effects manifest themselves in abnormal levels of specific biomarkers found in the peripheral blood. By providing multiplexed, quantitative, and reproducible tests for hundreds of biomarkers, RBM enables research that historically was not available due to sample volume requirements and associated costs. Use of our testing services can identify the sources of both the positive and negative effects of drugs during pre-clinical research and clinical trials. Biomarker testing results identify patients most likely to respond to a given therapy and the biochemical reason for that response, making clinical trials more successful and effective. Through its wholly owned subsidiary EDI GmbH, RBM provides Human Organo-Typic (HOT) cell culture systems. These co-culture systems consist of multiple primary cell types grown in a 3-D architecture that closely mimic particular human organs and are an ideal platform for ex vivo studies of drug safety and efficacy. RBM combines EDIs cell culture systems with its HumanMAP biomarker testing services to provide researchers with an unprecedented view of the physiological and biochemical impact of a new drug compound or consumer product prior to testing in a human subject. RBM also performs custom assay development, participates in co-sponsored research programs, and pursues in-licensing of novel high-value assays.

Proper citation: Rules Based Medicine (RRID:SCR_008575) Copy   

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http://www.nimblegen.com

Roche NimbleGen, Inc. is a leading innovator, manufacturer and supplier of a proprietary suite of DNA microarrays, consumables, instruments and services. Roche NimbleGen uniquely produces high-density arrays of long oligo probes that provide greater information content and higher data quality necessary for studying the full diversity of genomic and epigenomic variation. Roche NimbleGen is enabling a new era of High-Definition Genomics by providing scientists with cost-effective, high-throughput tools for extracting and integrating complex data on important forms of genomic and epigenomic variation not previously accessible on a genome-wide scale. Scientists can thus obtain a clearer understanding of genomic and epigenomic structure and function and how they impact biology and medicine. This improved performance is made possible by Roche NimbleGen''s proprietary Maskless Array Synthesis (MAS) technology, which uses digital light processing and rapid, high-yield photochemistry to synthesize long oligo, high-density DNA microarrays with extreme flexibility. NimbleGen Systems was established in 1999. The MAS technology is the result of research collaborations between the departments of biotechnology, genetics, physics, and semiconductor engineering at the University of Wisconsin - Madison. Roche NimbleGen has the exclusive worldwide license to the MAS technology from the Wisconsin Alumni Research Foundation (WARF).

Proper citation: Roche NimbleGen (RRID:SCR_008571) Copy   

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https://bitbucket.org/johanneskoester/snakemake/wiki/

A Python based language and execution environment for make-like workflows. The system supports the use of automatically inferred multiple named wildcards (or variables) in input and output filenames.

Proper citation: Snakemake (RRID:SCR_003475) Copy   

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http://bbid.irp.nia.nih.gov/

Database of images of putative biological pathways, macromolecular structures, gene families, and cellular relationships. It is of use to those who are working with large sets of genes or proteins using cDNA arrays, functional genomics, or proteomics. The rationale for this collection is that: # Except in a few cases, information on most biological pathways in higher eukaryotes is non-existent, incomplete, or conflicting. # Similar biological pathways differ by tissue context, developmental stages, stimulatory events, or for other complex reasons. This database allows comparisons of different variations of pathways that can be tested empirically. # The goal of this database is to use images created directly by biomedical scientists who are specialists in a particular biological system. It is specifically designed to NOT use average, idealized or redrawn pathways. It does NOT use pathways defined by computer algorithm or information search approaches. # Information on biological pathways in higher eukaryotes generally resides in the images and text of review papers. Much of this information is not easily accessible by current medical reference search engines. # All images are attributable to the original authors. All pathways or other biological systems described are graphic representations of natural systems. Each pathway is to be considered a work in progress. Each carries some degree of error or incompleteness. The end user has the ultimate responsibility to determine the scientific correctness and validity in their particular biological system. Image/pathway submissions are welcome.

Proper citation: Biological Biochemical Image Database (RRID:SCR_003474) Copy   

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http://pir.georgetown.edu/pirwww/dbinfo/pirsf.shtml

A SuperFamily classification system, with rules for functional site and protein name, to facilitate the sensible propagation and standardization of protein annotation and the systematic detection of annotation errors. The PIRSF concept is being used as a guiding principle to provide comprehensive and non-overlapping clustering of UniProtKB sequences into a hierarchical order to reflect their evolutionary relationships. The PIRSF classification system is based on whole proteins rather than on the component domains; therefore, it allows annotation of generic biochemical and specific biological functions, as well as classification of proteins without well-defined domains. There are different PIRSF classification levels. The primary level is the homeomorphic family, whose members are both homologous (evolved from a common ancestor) and homeomorphic (sharing full-length sequence similarity and a common domain architecture). At a lower level are the subfamilies which are clusters representing functional specialization and/or domain architecture variation within the family. Above the homeomorphic level there may be parent superfamilies that connect distantly related families and orphan proteins based on common domains. Because proteins can belong to more than one domain superfamily, the PIRSF structure is formally a network. The FTP site provides free download for PIRSF.

Proper citation: PIRSF (RRID:SCR_003352) Copy   

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http://biomed.emory.edu/PROGRAM_SITES/MSP/

The Molecular and Systems Pharmacology graduate program at Emory University offers broad training in the biomedical sciences for students interested in learning how the drugs of today work and how the novel therapeutics of tomorrow can be developed. The Program offers a specialization in toxicology. Emory University was recently rated by The Scientist magazine as the number 1 university in the world in terms of impact in pharmacology and toxicology research. Particular strengths within the MSP graduate school program at Emory include neuropharmacology, cancer biology, AIDS research, cardiovascular pharmacology, toxicology, and chemical biology. Ph.D. training in the Emory MSP program provides students with an ideal preparation for successful careers in the biotechnology and pharmaceutical industries as well as in academic research, teaching, government research, patent law and other disciplines that depend upon knowledge of fundamental pharmacological principles.

Proper citation: Emory University, Molecular and Systems Pharmacology (RRID:SCR_003351) Copy   

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