Buckner_GPU-R_BOSC2009
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This document discusses enabling GPU computing capabilities in the R statistical environment. It motivates using GPUs for R due to their low cost and ability to improve performance over single-threaded CPU execution. It introduces several GPU-accelerated R packages for tasks like Granger causality testing, clustering, SVM training and prediction, and mutual information calculation. It describes how the packages utilize CUDA to produce shared objects callable from R and notes opportunities for additional GPU-enabled functions. In conclusion, it provides references and information for obtaining the GPU computing capabilities for R.
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Schbath Rmes Bosc2009
The document describes the R'MES software for identifying exceptional motifs in DNA sequences. R'MES uses statistical methods to determine if the number of occurrences of a motif is significantly higher or skewed than expected by chance. It can compare the exceptionality of a motif between sequences and identify motifs that are over-represented or orientation-dependent in a genome. As examples, it discusses how R'MES was used to identify the Chi motif in Staphylococcus aureus and investigate the organization of DNA in Escherichia coli.
Kallio Chipster Bosc2009
The document discusses two software patterns used in developing Chipster, a bioinformatics application: graceful GUI blocking, which places an opaque layer over the GUI to indicate loading and prevent user interaction; and self-service distributed state management, which distributes application state management to clients to avoid single points of failure in a distributed system. The patterns were found useful for Chipster, which provides bioinformatics analysis tools through a graphical interface and supports distributed computing.
Welch Wordifier Bosc2009
This document discusses the discovery that DNA previously thought to have no value ("junk DNA") may actually play important roles in gene expression regulation. Scientists investigated junk DNA in the model plant Arabidopsis thaliana and found short, linked patterns of DNA called pyknons. This suggests a universal genetic mechanism is at play across biology that is not yet fully understood. The discovery illustrates the connection between coding and non-coding DNA and that the term "junk DNA" may need reevaluation.
Rice Emboss Bosc2009
EMBOSS is an open source software suite for sequence analysis. It contains over 200 applications and supports over 100 file formats. It is funded by the UK BBSRC and developed by researchers at the EBI, Sanger Institute, and other institutions. EMBOSS faced an uncertain future in 2004 when its original developers were relocated, but continued funding has allowed ongoing development and support for a worldwide user base conducting research on all continents.
Prlic Bio Java Bosc2009
BioJava is an open source Java framework for processing biological data. It provides tools for analyzing and manipulating sequences, structures, and other biological data. The latest version, BioJava 1.7, includes improved support for 3D structures and modularization into separate modules. The project aims to facilitate rapid bioinformatics application development and is supported by an active developer community.
Senger Soaplab Bosc2009
Soaplab is a generator of web services for accessing command-line programs and other tools. It wraps hundreds of EMBOSS programs and other plugins as SOAP web services. A new release, Soaplab 2.2.0, adds support for "typed services" which define inputs and outputs using WSDL and XSD for better integration with third party tools. Developers can add new command line tools or plugins and Soaplab will generate the corresponding web services.
Cock Biopython Bosc2009
This document provides an update on the Biopython project. It discusses recent releases including support for new file formats like FASTQ and new modules. It outlines current and future projects including work on parsing new file types and switching from CVS to git version control. Development involves an international team through an open source model and is supported by various organizations.
Hanmer Software Patterns Bosc2009
The document discusses software patterns for reusable design, outlining what a software pattern is, how patterns are used within communities, and how to apply patterns to documentation, design, and development. It provides an overview of pattern concepts including what constitutes a pattern, pattern languages, and pattern communities while cautioning that patterns should not be viewed as a "turn the crank" approach to software development.
Snell Psoda Bosc2009
PSODA is an open-source phylogenetic search and DNA analysis package that is compatible with PAUP* and adds a scripting language to PAUP blocks to allow for advanced meta-searches. It began development in 2005 as an alternative to PAUP* that could be used for phylogenetic search, multiple alignment, and detecting natural selection. PSODA's scripting language, PSODAscript, adds functionality like decision statements, loops, and functions to PAUP blocks and allows for easy scripting of meta-searches.
Procter Vamsas Bosc2009
This document summarizes an approach called VAMSAS that enables sharing of data like sequences, alignments, and annotations between different bioinformatics tools. It describes how VAMSAS uses a shared XML document and client library to allow tools to access and update shared data, view events in other tools, and better integrate workflows. Examples of tools like TOPALI and Jalview that could benefit from this approach are discussed.
Drablos Composite Motifs Bosc2009
This document describes a method for discovering composite motifs in DNA sequences. The method searches for overrepresented patterns representing transcription factor binding sites. It improves on previous methods by modeling motifs as modules that occur together, rather than as isolated patterns. The algorithm ranks predicted modules based on support, specificity and significance. It was shown to outperform other tools, particularly at realistic noise levels, due to its use of real DNA backgrounds and support-based scoring. Future work includes exploring the full Pareto front of optimal solutions and parameter interactions to improve predictions.
Fauteux Seeder Bosc2009
3) The algorithm works by first discovering short motif seeds, then extending these seeds into full length position weight matrices, and iteratively refining the matrices to discover overrepresented motifs.
Moeller Debian Bosc2009
Debian-Med is a Debian Linux distribution community focused on adapting and disseminating open source bioinformatics software. It maintains over 160 bioinformatics packages through a collaborative development process, providing quality assurance and compatibility across multiple architectures. The community aims to improve access to packages for high-performance and cloud computing as well as ease of data management and distribution of bioinformatics libraries and software.
Prins Bio Lib Bosc 2009
The document summarizes the BioLib project, which aims to create C/C++ libraries for common biological functionality that can be accessed from multiple bioinformatics programming languages to avoid duplication of efforts. It has created bindings for several existing libraries, including Affyio, Staden IO, GSL, Rlib, and others. The project uses Git for version control, CMake for building, and SWIG for generating language bindings in an effort to maximize code reuse across languages.
Wilczynski_BNFinder_BOSC2009
This document introduces BNFinder, a Python software for reconstructing Bayesian networks and dynamic Bayesian networks from data. It uses a fast, exact algorithm to find the optimal network topology, unlike traditional Markov chain Monte Carlo methods. The software supports discrete and continuous data, different scoring functions, and datasets with perturbations. It is open source and runs efficiently on large real-world genomic and neural network examples. Future plans include parallelization and improvements to continuous variable and classification models.
Welsh_BioHDF_BOSC2009
The document discusses the BioHDF project which aims to develop scalable data infrastructure for bioinformatics using HDF5. It notes that next generation DNA sequencing is producing vast amounts of complex data that is challenging to analyze and compare across samples due to lack of consistent data models and structured storage. The BioHDF project seeks to address this by developing HDF5 domain extensions and tools to organize, index, annotate and access sequencing data in a way that enables more efficient analysis, visualization and exploration of results within and between samples.
Varre_Biomanycores_BOSC2009
The document describes the biomanycores.org project, which aims to create a repository of open-source GPU-accelerated bioinformatics algorithms. It provides interfaces to popular bioinformatics tools like BioJava, BioPerl, and Biopython to easily integrate the GPU implementations. The project currently includes tools like Smith-Waterman alignment and PWM scanning. The challenges include differing APIs, object representations, real-world pipelines, and licensing. The goals are to share more OpenCL code, integrate and benchmark new algorithms, and improve usability for bioinformaticians.
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GNSS spoofing via SDR (Criptored Talks 2024)
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Must Know Postgres Extension for DBA and Developer during Migration
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
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Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
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Mutation Testing for Task-Oriented Chatbots
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
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Astute Business Solutions | Oracle Cloud Partner |
Your goto partner for Oracle Cloud, PeopleSoft, E-Business Suite, and Ellucian Banner. We are a firm specialized in managed services and consulting.
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Leveraging the Graph for Clinical Trials and Standards
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Astute Business Solutions | Oracle Cloud Partner |
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Buckner_GPU-R_BOSC2009
- 1. Enabling GPU Computing in the R Statistical Environment Josh Buckner bucknerj@umich.edu Molecular & Behavioral Neuroscience Institute University of Michigan Ann Arbor, MI 48109
- 2. Josh Buckner, Manhong Dai, Brian Athey, Stanley Watson and Fan Meng Support from: Pritzker Neuropsychiatric Disorders Consortium National Center for Integrative Biomedical Informatics Center for Computational Biology and Medicine
- 3. Motivation ● Default R install – Desktop – Single thread of execution ● Cost of traditional cluster
- 4. nVidia CUDA ● Free toolkit ● Inexpensive readily available desktop hardware ● Simple extension of C ● Lots of documentation
- 5. gpuGranger ● Granger-causality test ● statistic measuring whether sequence a predicts the values of seqence b better than b alone
- 6. gpuCor ● Pearson ● pairwise complete Pearson ● Kendall
- 7. gpuClust ● hierarchical cluster w/ variety of methods ● gpuDistClust
- 8. gpuSvmTrain and gpuSvmPredict ● R front end for Austin Carpenter's cuSVM
- 9. gpuMi ● B-spline based mutual information calculation
- 10. Other Functions ● gpuDist ● gpuMatMult ● gpuLr ● gpuQr ● gpuSolve
- 11. Future Functions ● From our new collaborator: Rapid Biologics ● gpuGlm – generalized linear model fit ● gpuLm – linear model fit ● gpuLsFit – least squares fit lsfit respectively
- 12. Results (single thread of execution)
- 13. How? ● Use nvcc to produce shared object with C calling convention
- 14. rinterface.h extern “C” void rSetDevice(const int * device);
- 15. rinterface.c #include<rinterface.h> #include<cuda.h> void rSetDevice(const int * device) { cudaSetDevice(*device); }
- 16. gpuSetDevice.R gpuSetDevice ← function(deviceId) { .C(“rSetDevice”, as.integer(deviceId)) }
- 17. Contributors ● Molecular & Behavioral Neuroscience Institute at University of Michigan ● Rapid Biologics, Seattle, Washington ● You!
- 18. Availability ● http://brainarray.mbni.med.umich.edu/brainarray/Rgpgpu ● http://cran.r-project.org/web/packages/gputools/index.htm ● bucknerj@umich.edu
- 19. References Carpenter,A. (2009) http://patternsonascreen.net/cuSVM.html. Daub,C. et al. (2004) Estimating mutual information using B-spline functions – an improved similarity measure for analysing gene expression data, BMC Bioinformatics, 5:118 Kaminski,M. et al. (2001) Evaluating causal relations in neural systems: granger causality, directed transfer function and statistical assessment of significance, Biol Cybern, Vol. 85, No. 2, 145—157.