Curator Dashboard

A software library for Apache Pig for the distributed analysis of large sequencing datasets on Hadoop clusters.

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• SciCrunch
• 13 years ago - by Anonymous

Founded on the principle that strong science would lead to important new medicines, Regeneron has become an integrated biopharmaceutical company that discovers, develops, and commercializes medicines for the treatment of serious medical conditions. Regeneron currently markets ARCALYST (rilonacept) Injection for Subcutaneous Use for the treatment of a rare, inherited, inflammatory condition. Regeneron has therapeutic candidates in Phase 3 clinical trials for the potential treatment of gout, age-related macular degeneration, central retinal vein occlusion, and certain cancers. Additional therapeutic candidates are in earlier stage development programs in rheumatoid arthritis and other inflammatory conditions, pain, cholesterol reduction, allergic conditions, and cancer. The Company''s ability to develop product candidates is enhanced by the application of several proprietary technologies that Regeneron has incorporated into a comprehensive drug discovery and development process. This process is designed to thoroughly understand the biology of specific diseases, discover potential therapeutic candidates, and evaluate these candidates in clinical trials. One specific area of Regeneron expertise is the rapid development of fully-human monoclonal antibodies. In November 2007, Regeneron and sanofi-aventis entered into a global, strategic collaboration to discover, develop, and commercialize fully-human therapeutic antibodies utilizing Regeneron''s proprietary VelociSuite of technologies, and we expanded the collaboration in November 2009. Five human antibodies developed under the sanofi-aventis collaboration are in clinical development today, with a goal of advancing an average of four to five new antibodies into clinical development each year through 2017. In addition to the Company''s corporate headquarters and research laboratories in Tarrytown, New York, Regeneron has a large-scale biologics manufacturing facility in Rensselaer, New York, where it produces commercial and investigational products for its clinical trials, and a satellite office in Bridgewater, New Jersey.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented on July 15, 2013. A database containing all genomic human and mouse binding sites of the Repressor Element 1 Silencing Transcription factor (REST), identified by PSSM. The RE1 silencing transcription factor (REST; also known as the neuron-restrictive silencer factor), is a nine zinc-finger transcription factor, related to the Gli-Kruppel family. REST binds to a conserved 21-nucleotide element, known as repressor element 1 (RE1; also known as the neuron-restrictive silencer element). REST was proposed to be a ''master'' silencer of neuron specific gene expression in non-neuronal tissues and undifferentiated neuroepithelium (precursor of neuronal cells), preventing the default expression of the neuronal phenotype during embryogenesis. It has been shown to function independently of orientation and distance from a gene promoter. REST has an important role during embryonic development, as homozygous gene knockout mice (Rest-/-) die by embryonic day 11.5. The constitutive expression of REST has also been shown to disrupt neuronal gene expression and cause axon path finding errors in chicken embryos (Paquette et al. 2000). RE1 sequences that are known to bind REST have also been found near to non-neuronal genes, including keratin and cytochrome P450 genes.

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• SciCrunch
• 17 years ago - by Anonymous

The retinoblastoma tumor suppressor gene RB plays a major role in cell cycle entry: RB sequesters a family of transcription factors, E2Fs, responsible for the transcription of many genes involved in the cell cycle regulation, DNA replication and in the activation of the apoptotic pathway. RB functions as a brake in the cell cycle which is released when external signals (growth factors, ) inform the cell that it can proceed to S phase. The target of the external signals is the G1 cyclin/Cdk complex. Once active, the complex phosphorylates pRB which can then free E2F. E2F can then participate in the synthesis of many genes, among them, cyclin E, which immediately binds to the Cdc2 kinase Cdc2. The complex then fires DNA replication. The understanding of the pathway regulating the tumor suppressor RB and the transcription factors E2F might give insight in the regulation of many cancers. Constructing the pathway Based on the literature, a quasi-exhaustive pathway has been built around RB to relate the regulation around the phosphorylation of the tumor suppressor protein. Once validated, the pathway can be exploited by computers to analyze deregulations observed in some cancers and used by biologists as a reference of the signalling pathways leading to RB phosphorylation. The diagram allowed to integrate an important amount of information. However, the goal would also be to exploit these data in order to understand the pathway and anticipate the behaviour of any kind of mutations in the cell. For that purpose, different tools are available to manipulate this kind of diagrams (Cytoscape, BiNoM, ...). Click here to find the page you are interested in Modeling the pathway The diagram was divided in different modules, each module representing a subpart of the diagram that describes the mechanism of modification (acetylation, phosphorylation) of a major protein in the cell cycle. The simplified diagram can be analyzed qualitatively (Boolean or discrete approaches) or quantitatively (ODEs) to provide a first understanding of the network. What for? The final purpose of the construction of this diagram is to provide a map of the RB pathway that can become a reference when studying different cancers and mutations. This project was partly funded by the EC contract ESBIC-D (LSHG-CT-2005-518192), the PIC Retinoblastome from Institut Curie, the PIC Bioinformatique et Biostatistiques from Institut Curie and the Research Networks Program in Bioinformatics from the High Council for Scientific and Technological Cooperation between France and Israel (Ministere des Affaires Etrangeres, Ministere de l''Education Nationale, de l''Enseignement Superieur et de la Recherche).

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• SciCrunch
• 17 years ago - by Anonymous

RANDOM.ORG is a true random number service that generates randomness via atmospheric noise. This page explains why it''s hard (and interesting) to get a computer to generate proper random numbers. Random numbers are useful for a variety of purposes, such as generating data encryption keys, simulating and modeling complex phenomena and for selecting random samples from larger data sets. They have also been used aesthetically, for example in literature and music, and are of course ever popular for games and gambling. When discussing single numbers, a random number is one that is drawn from a set of possible values, each of which is equally probable, i.e., a uniform distribution. When discussing a sequence of random numbers, each number drawn must be statistically independent of the others. With the advent of computers, programmers recognized the need for a means of introducing randomness into a computer program. However, surprising as it may seem, it is difficult to get a computer to do something by chance. A computer follows its instructions blindly and is therefore completely predictable. (A computer that doesn''t follow its instructions in this manner is broken.) There are two main approaches to generating random numbers using a computer: Pseudo-Random Number Generators (PRNGs) and True Random Number Generators (TRNGs). The approaches have quite different characteristics and each has its pros and cons.

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• SciCrunch
• 17 years ago - by Anonymous

The abbreviated name, mfold web server, describes a number of closely related software applications available on the World Wide Web (WWW) for the prediction of the secondary structure of single stranded nucleic acids. The objective of this web server is to provide easy access to RNA and DNA folding and hybridization software to the scientific community at large. By making use of universally available web GUIs (Graphical User Interfaces), the server circumvents the problem of portability of this software. Detailed output, in the form of structure plots with or without reliability information, single strand frequency plots and energy dot plots, are available for the folding of single sequences. A variety of bulk servers give less information, but in a shorter time and for up to hundreds of sequences at once. The portal for the mfold web server is http://www.bioinfo.rpi.edu/applications/mfold. This URL will be referred to as MFOLDROOT.

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• SciCrunch
• 17 years ago - by Anonymous

Complex systems are defined as systems with many interdependent parts which give rise to non-linear and emergent properties determining the high-level functioning and behavior of such systems. Due to the interdependence of their constituent elements and other characteristics of complex systems, it is difficult to predict system behavior based on the sum of their parts alone. Examples of complex systems include bee hives, bees themselves, human economies and societies, nervous systems, molecular interactions, cells and living things, ecosystems, as well as modern energy or telecommunication infrastructures. Arguably one of the most striking properties of complex systems is that conventional experimental and engineering approaches are inadequate to capture and predict the behavior of such systems. To complement the conventional experimental and engineering approaches, computer-based simulations of complex natural phenomena and complex man-made artifacts are increasingly employed across a wide range of sectors. Typically, such simulations require computing environments which meet very high specifications in terms of processing units, primary and secondary storage, and communication. Supercomputers constitute the de facto technology to deliver the required specifications. Acquiring, operating and maintaining supercomputers involve considerable costs, which many organizations cannot afford. The working assumption of the QosCosGrid project is that a grid could be enhanced by suitable middleware to provide features and performance characteristics that resemble those of a supercomputer., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

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• SciCrunch
• 17 years ago - by Anonymous

THIS RESOURCE IS NO LONGER IN SERVICE, documented August 23, 2016. The brain is made of billions of neurons, which together form the world''s most powerful information-processing machine. Despite decades of research, the fundamental principle by which these cells work together is still unknown. Many theories for brain function have been proposed over the last century. But only in the last few years has it become possible to record simultaneously from large enough numbers of neurons to put these theories to the test experimentally. This is an unprecedented opportunity, but it opens up a new question: how do we go from the gigabytes of experimental data that we now have, to concise conclusions about the function of the brain? The data processing methods traditionally used in neuroscience are not sophisticated enough to exploit this new flood of information. Fortunately, modern statistics and machine learning theory is making great strides in precisely the type of techniques needed to process these large multivariate databases. By applying these methods to neuronal data, we can now test long-standing hypotheses about brain function. The Cell Assembly The main focus of our research is an experimental search for cell assemblies. Before describing what a cell assembly is, it will be useful to describe what it is not. The brain is often thought of as a feed-forward system. In this scheme, sensory information is processed by successive levels of cortical analyzers, each of which transforms the results of previous levels, until sensory information is in a suitable form to guide the animals behavior. In support of this idea, the pattern of connections in the cortex does appear to respect a hierarchical organization, with the output of low-level areas corresponding to a single sensory modality being integrated into high-level multi-modal areas. Responses in higher-level sensory areas appear to have more complex responses to sensory stimuli, in agreement with increased abstraction as the hierarchy is traversed. However, there are several levels at which this feed-forward picture is incomplete. At the circuit diagram level, there more connections projecting across and down the hierarchy, than there are feed-forward projections. What''s more, if information were processed in a strictly feed-forward manner, one would expect a neuron to respond identically to repeated presentations of the same sensory stimulus. Although this is a fairly good approximation in primary sensory areas of cortex, in high-level structures responses are often more variable than expected from strict sensory control. Finally, although feed-forward processing can describe how an animal could perform simple stimulus-response behaviors, it cannot explain more complex top-down behaviors such as memory or thought. An alternative point of view, put forward over 50 years ago by Canadian psychologist Donald Hebb, holds that recurrent and feedback connections play an essential role in brain function. The principal actor in this view is the cell assembly, an anatomically distributed subset of neurons, amongst which mutually excitatory connections have been strengthened by repeated co-activation, allowing the assembly to later maintain its activity through reverberation without direct sensory stimulation. This theory allows for sensory-response behavior, and also behavior resulting purely from internally generated cognitive activity, by the sequential activation of a series of assemblies, leading in turn to the production of motion. In our research, we search for signatures of assembly activity in simultaneous recordings from multiple neurons, and aim to characterize the properties of assembly activity in ways not possible from theory alone. Software for Automatic Clustering KlustaKwik is a program developed in the lab for automatic cluster analysis, specifically designed to run fast on large data sets. In order facilitate open-source development, it is now located at klustakwik.sourceforge.net. This study was supported by NIH grants MH073245 and DC009947; NSF grant SBE-0542013 to the Temporal Dynamics of Learning Center, an NSF Science of Learning Center; a National Institute on Deafness and Other Communication Disorders, NIH, grant DC-005787-01A1; and a Spanish grant FIS 2006-09294. K.D.H. is an Alfred P. Sloan fellow. We would like to dedicate this work to the memory of D. J. Amit.

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• SciCrunch
• 17 years ago - by Anonymous

QTL Cartographer is a suite of programs to map quantitative traits using a map of molecular markers. The programs are available via an anonymous ftp server. See the README for more information. You will also want a copy of Gnuplot to display plots made by QTL Cartographer. Gnuplot is freely available on the web. Do a search to find the latest version for your operating system. Windows QTL Cartographer Windows QTL Cartographer is a user friendly version of QTL Cartographer. It has a GUI interface and runs under Microsoft Windows. Manual The manual for QTL Cartographer is written in LaTeX2e. An Adobe Portable document format (pdf) version is available with the distribution of the programs. Look in the doc/pdf folder for the manual.pdf file. This file can be printed or viewed using Acrobat Reader, available through the Adobe website. The manual has also been translated into html. It is available through the following link. Please note that the translator is not perfect: The pdf form of the manual is much more accurate. Specifically, latex2html failed to translate figure 2.4 and simply printed 2.3 twice. Man Pages In the UNIX world, it is comman to have man pages for programs. We have written such a set of man pages, and these are available with the UNIX distribution. The man pages are also a part of the manual.pdf file. Here is a list of the man pages. 1. Emap 2. Rmap 3. Rqtl 4. Rcross 5. Qstats 6. LRmapqtl 7. SRmapqtl 8. Zmapqtl 9. JZmapqtl 10. MImapqtl 11. MultiRegress 12. Prune 13. Preplot 14. Eqtl 15. QTLcart Perl scripts QTL Cartographer comes with some perl scripts to automate repetitive tasks and reformat output files. They are available in the doc/scripts subdirectory of the distribution. Here are the man pages that explain what the scripts can do. 1. Bootstrap.pl is a script for running a bootstrap analysis. 2. CWTupdate.pl is used with Permute.pl for the comparison-wise thresholds. 3. EWThreshold.pl is used with Permute.pl for the experiment-wise thresholds. 4. GetMaxLR.pl is used with Permute.pl for the experiment-wise thresholds. 5. Model8.pl iterates Zmapqtl to find a stable set of cofactors for composite interval mapping. 6. Permute.pl is a script for running a permutation test. 7. Prepraw.pl allows you to reformat and check a Mapmaker data file. 8. SRcompare.pl will compare the set of cofactors in two SRmapqtl output files. 9. SSupdate.pl is used with Bootstrap.pl to update the sum and sum of squares for the likelihoods and parameter estimates. 10. Vert.pl converts text file line endings between Unix, Macintosh and Windows. 11. Ztrim.pl redisplays Zmapqtl output so that it fits in a terminal window. Data We are now posting published data sets to our web site. A list of links to the ftp subdirectories follows. Each directory contains a set of text files of data. Please read the Readme file in the directory for information on the data. 1. Zeng et al provide data for their paper Genetic architecture of a morphological shape difference between two Drosophila species. If you have any data that you would like to make available via our server, contact Chris Basten. Presentations From time to time, Chris Basten gives presentations on how to use QTL Cartographer. These presentations are created in Microsoft Powerpoint. The source file for the presentation is available with the distribution of the programs. Look in the doc subdirectory. Binary Traits See this for more information on the BTmapqtl module. This is an add-on written in LaurenMcIntyre''s lab. BTmapqtl is in the binary directory of the distribution (and is created with a make for the UNIX version).

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• SciCrunch
• 17 years ago - by Anonymous

A commercial organization which provides assay technologies to isolate DNA, RNA, and proteins from any biological sample. Assay technologies are then used to make specific target biomolecules, such as the DNA of a specific virus, visible for subsequent analysis.

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• SciCrunch
• 17 years ago - by Anonymous

Features: * This software takes a list of p-values resulting from the simultaneous testing of many hypotheses and estimates their q-values. A point-and-click interface is now available! * The q-value of a test measures the proportion of false positives incurred (called the false discovery rate) when that particular test is called significant. * A short tutorial on q-values and false discovery rates is provided with the manual. * Various plots are automatically generated, allowing one to make sensible significance cut-offs. * Several mathematical results have recently been shown on the conservative accuracy of the estimated q-values from this software. * The software can be applied to problems in genomics, brain imaging, astrophysics, and data mining. This research was supported in part by a National Science Foundation graduate research fellowship.

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• SciCrunch
• 17 years ago - by Anonymous

A tool to examine relationships between genes in different disease associated loci. Given several genomic regions or SNPs associated with a particular phenotype or disease, GRAIL looks for similarities in the published scientific text among the associated genes. As input, users can upload either (1) SNPs that have emerged from a genome-wide association study or (2) genomic regions that have emerged from a linkage scan or are associated common or rare copy number variants. SNPs should be listed according to their rs#''s and must be listed in HapMap. Genomic Regions are specified by a user-defined identifier, the chromosome that it is located on, and the start and end base-pair positions for the region. Grail can take two sets of inputs - Query regions and Seed regions. Seed regions are definitely associated SNPs or genomic regions, and Query regions are those regions that the user is attempting to evaluate agains them. In many applications the two sets are identical. Based on textual relationships between genes, GRAIL assigns a p-value to each region suggesting its degree of functional connectivity, and picks the best candidate gene. GRAIL is developed by Soumya Raychaudhuri in the labs of David Altshuler and Mark Daly at the Center for Human Genetic Research of Massachusetts General Hospital and Harvard Medical School, and the Broad Institute. GRAIL is described in manuscript, currently in preparation.

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• SciCrunch
• 17 years ago - by Anonymous

Software tool for detecting epistatic interactions in genome-wide association studies (entry from Genetic Analysis Software)

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• SciCrunch
• 14 years ago - by Anonymous

GOstat is a tool that allows you to find statistically overrepresented Gene Ontologies within a group of genes. The Gene-Ontology database (GO: http://www.geneontology.org) provides a useful tool to annotate and analyze the function of large numbers of genes. Modern experimental techniques, as e.g. DNA microarrays, often result in long lists of genes. To learn about the biology in this kind of data it is desirable to find functional annotation or Gene-Ontology groups which are highly represented in the data. This program (GOstat) should help in the analysis of such lists and will provide statistics about the GO terms contained in the data and sort the GO annotations giving the most representative GO terms first. Run GOstat: * Go to search form - Computes GO statistics of a list of genes selected from a microarray. * GOstat Display - You can store results from a previously run and view them here, either by uploading them as a file or putting them on a selected URL. * Upload Custom GO Annotations - This allows you to upload your own GO annotation database and use it with GOstat. Variants of GOstat: * Rank GOstat - Takes input from all genes on microarray instead of using a fixed cutoff and uses ranks using a Wilcoxon test or either ranks or pvalues to score GOs using Kolmogorov-Smirnov statistics. * Gene Abundance GOstats - Takes input from all genes on microarray and sums up the gene abundances for each GO to compute statistics. * Two list GOstat - Compares GO statistics in two independent lists of genes, not necessarily one of them being the complete list the other list is sampled from. Platform: Online tool, THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

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• SciCrunch
• 17 years ago - by Anonymous

The Gregor Mendel Institute of Molecular Plant Biology (GMI) was founded by the Austrian Academy of Sciences in 2000 in the form of a company to promote research excellence within the field of plant molecular biology. It is the only international centre for basic plant research in Austria. The GMI is located at the Vienna Biocenter Campus within the purpose-built Austrian Academy of Sciences Life Sciences Center Vienna, completed in January 2006. The Vienna Biocenter Campus, which encompasses both independent and academic research institutes as well as biotechnology companies, provides an ideal environment for the GMI. Neighbouring institutes include the Research Institute of Molecular Pathology (IMP), the Institute of Molecular Biotechnology (IMBA), as well as the Max F. Perutz Laboratories of the University of Vienna and of the Medical University of Vienna. Research at the GMI is curiosity driven and covers many aspects of molecular genetics, from basic mechanisms of epigenetics to population genetics. Arabidopsis thaliana is used as the primary model organism, and research groups are evaluated annually by an international external Scientific Advisory Board. The working language of the GMI is English. Research at the GMI is carried out by independent research groups, led either by senior group leaders with contracts of unlimited duration, or junior group leaders with temporary (5 3 years) appointments. GMI''s research activities are supported by its administration and a platform consisting of the GMI''s own services, including state-of-the-art plant growth facilities, as well as joint services with the Research Institute of Molecular Pathology and the Institute of Molecular Biotechnology Funding Our employees are expected to apply for grants and additional financial support from various external national and international funding bodies. The list below provides an overview of the funding opportunities that could be relevant for GMI members. The Frderassistent of the FFG (in German) or the Frderkompass of the Federal Ministry of Transport, Innovation and Technology (in German) can also be used to find appropriate funding.