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rick stevens, argonne

The power of the EMP is in the capability to turn these data in to descriptive and predictive models. Rick Stevens is on Facebook. There is an urgent need to identify drugs that can inhibit SARS-CoV-2. Plan your own trip or take one of Rick's value-packed European tours and vacations. Stevens has been at Argonne since 1982, and has served as director of the Mathematics and Computer Science Division and also as Acting Associate … He is also the PI for the Argonne Leadership Computing Facility. Rick Stevens is Argonne’s Associate Laboratory Director for Computing, Environment and Life Sciences. cecil_graf@yahoo.fr Tour HQ 33 650 603 800. “He will undoubtedly continue to contribute to the discipline at the highest level.” Rick Stevens professor of computer science at the University of Chicago and leader of Argonne's Exascale computing initiative. The SEED integrates many publicly available genome sequences into a single resource. (0.29 MB TIF), Accuracy of GAAS estimates for microbial metagenomes. No. 80 functional roles considered to be “always ON.”. Rick Stevens is Argonne’s Associate Laboratory Director for Computing, Environment and Life Sciences. Rick Stevens Associate Laboratory Director, Argonne National Laboratory, Professor, University of Chicago The SEED is a constantly updated integration of genomic data with a genome database, web front end, API and The simulated viromes were made of 100 bp sequences. Due to our privacy policy, only current members can send messages to people on ResearchGate. RMACC 2018 HPC Symposium has ended I am Rick Stevens, the Associate Laboratory Director responsible for Computing, Environment and Life Sciences research at Argonne National Laboratory and a Professor of Computer Science at the University of Chicago. Rick Steves is America's leading authority on European travel. View Rick Stevens's business profile as Associate Laboratory Director, Computing at Department of Energy - Argonne National Laboratory. Rick Stevens is a professor at the University of Chicago and the associate laboratory director for the Computing, Environment and Life Sciences Directorate at Argonne National Laboratory. HPCwire recently had a chance to talk with Stevens, one of the report’s authors and associate laboratory director at ANL, about the scope of the potential AI project and a few particulars regarding the AI opportunity and challenge. Rick L Stevens Rick will speak to experiences gained running the highly successful RAST and MG-RAST services for genome and metagenome sequence assembly and analysis. In addition to his research work, Stevens teaches courses on computer architecture, collaboration technology, virtual reality, parallel computing and computational science. This is both too expensive and too slow, especially in emergencies like the COVID-19 pandemic. Two decades later, Mr. Stevens, 34, oversees Argonne's joint research project with IBM Corp. to develop software for the next generation of supercomputers. Support for hierarchical clusters. (0.17 MB TIF), Biome averaged genome length estimated by GAAS for the metagenomes of each environment. Yet efforts to develop new models are failing to keep pace with genome sequencing. Rick Stevens, Director of Accelerated Pharma. Detail of the 169 metagenomes used for the meta-analysis and their average genome size estimated by GAAS. Rick Stevens . 80% of the species in the viral simulated metagenomes were treated as unknown. Two decades later, Mr. Stevens, 34, oversees Argonne's joint research project with IBM Corp. to develop software for the next generation of supercomputers. Biological datasets amenable to applied machine learning are more available today than ever before, yet they lack adequate representation in the Data-for-Good community. He is currently leader of Argonne’s Exascale Computing Initiative, and a Professor of Computer Science at the University of Chicago Physical Sciences Collegiate Division. However, the piecemeal approach that has defined efforts to study mi... High throughput sequencing has accelerated the determination of genome sequences for thousands of human infectious disease pathogens and dozens of their vectors. Sections of this page. Gujarat Biotechnology Research Centre, Gandhinagar, Fellowship for the Interpretation of Genomes, Mathematics and Computer Science Division, School of Information and Computer Science, Learning Curves for Drug Response Prediction in Cancer Cell Lines, Scalable HPC and AI Infrastructure for COVID-19 Therapeutics, IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads, Abstract 36: Virtual screening with deep learning using cancer cell line dose-response data, Regression Enrichment Surfaces: a Simple Analysis Technique for Virtual Drug Screening Models, Targeting SARS-CoV-2 with AI- and HPC-enabled Lead Generation: A First Data Release, Ensemble Transfer Learning for the Prediction of Anti-Cancer Drug Response, Deep Medical Image Analysis with Representation Learning and Neuromorphic Computing, A Systematic Approach to Featurization for Cancer Drug Sensitivity Predictions with Deep Learning, The PATRIC Bioinformatics Resource Center: expanding data and analysis capabilities, AI Meets Exascale Computing: Advancing Cancer Research With Large-Scale High Performance Computing, Scalable Reinforcement-Learning-Based Neural Architecture Search for Cancer Deep Learning Research, Performance, Energy, and Scalability Analysis and Improvement of Parallel Cancer Deep Learning CANDLE Benchmarks, CANDLE/Supervisor: A workflow framework for machine learning applied to cancer research, Scaling Deep Learning for Cancer with Advanced Workflow Storage Integration, Portable and Reusable Deep Learning Infrastructure with Containers to Accelerate Cancer Studies, Big data and extreme-scale computing: Pathways to Convergence-Toward a shaping strategy for a future software and data ecosystem for scientific inquiry, Developing an in silico minimum inhibitory concentration panel test for Klebsiella pneumonia, Assembly, Annotation, and Comparative Genomics in PATRIC, the All Bacterial Bioinformatics Resource Center, BIG DATA AND EXTREME-SCALE COMPUTING: PATHWAYS TO CONVERGENCE Toward a Shaping Strategy for a Future Software and Data Ecosystem for Scientific Inquiry, Mutation in an Unannotated Protein Confers Carbapenem Resistance in Mycobacterium tuberculosis, Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center, Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation, Modeling central metabolism and energy biosynthesis across microbial life, Machine Learning for Antimicrobial Resistance, Antimicrobial Resistance Prediction in PATRIC and RAST, REMap: Operon map of M. tuberculosis based on RNA sequence data, RASTtk: A modular and extensible implementation of the RAST algorithm for building custom annotation pipelines and annotating batches of genomes, Genomic Encyclopedia of Bacteria and Archaea: Sequencing a Myriad of Type Strains, Standardized Metadata for Human Pathogen/Vector Genomic Sequences, High-throughput comparison, functional annotation, and metabolic modeling of plant genomes using the PlantSEED resource, Accelerating Bacterial Genomics and Metagenomics via Science Services, Large-Scale Modeling of Epileptic Seizures: Scaling Properties of Two Parallel Neuronal Network Simulation Algorithms, The SEED and the Rapid Annotation of microbial genomes using Subsystems Technology (RAST), PATRIC, the bacterial bioinformatics database and analysis resource, Comparison of the Genome Sequences of "Candidatus Portiera aleyrodidarum" Primary Endosymbionts of the Whitefly Bemisia tabaci B and Q Biotypes, Genome Sequences of the Primary Endosymbiont "Candidatus Portiera aleyrodidarum" in the Whitefly Bemisia tabaci B and Q Biotypes, Building the repertoire of dispensable chromosome regions in Bacillus subtilis entails major refinement of cognate large-scale metabolic model, SEED Servers: High-Performance Access to the SEED Genomes, Annotations, and Metabolic Models, Real Time Metagenomics: Using k-mers to annotate metagenomes, Unlocking the potential of metagenomics through replicated experimental design, Modeling the Microbial Maelstrom: Mathematical Abstractions of Biological Complexity, The Earth Microbiome Project: The Meeting Report for the 1st International Earth Microbiome Project Conference, Shenzhen, China, June 13th-15th 2011, Insights From High-Throughput Reconstruction and Analysis of 3500 Genome-Scale Metabolic Models, HPCS 2011 keynotes: Tuesday keynote I: High-performance computing and biology: The quest for a predictive biological theory, Connecting genotype to phenotype in the era of high-throughput sequencing, The International Exascale Software Project Roadmap 1, Meeting Report: The Terabase Metagenomics Workshop and the Vision of an Earth Microbiome Project, The Earth Microbiome Project: Meeting report of the "1 EMP meeting on sample selection and acquisition" at Argonne National Laboratory October 6 2010, Model-Driven Minimization of the B. Subtilis Genome, Systematic Comparison of the Behaviors Produced by Computational Models of Epileptic Neocortex, High-throughput generation, optimization and analysis of genome-scale metabolic models, Accessing the SEED Genome Databases via Web Services API: Tools for Programmers, Oscillation in a Network Model of Neocortex, Analysis of the Effect of Reversibility Constraints on the Predictions of Genome-Scale Metabolic Models, The GAAS Metagenomic Tool and Its Estimations of Viral and Microbial Average Genome Size in Four Major Biomes, High-Throughput Reconstruction and Optimization of 130 New Genome-Scale Metabolic Models, The International Exascale Software Project: a Call To Cooperative Action By the Global High-Performance Community, Using a camera to capture and correct spatial photometric variation in multi-projector displays, Application of high-performance computing to the reconstruction, analysis, and optimization of genome-scale metabolic models, i Bsu1103: a new genome-scale metabolic model of Bacillus subtilis based on SEED annotations. Co-founded by alumnus Kunle Olukotun, the company has announced product and system-as-a-service solutions for AI-intensive applications. Rick Stevens, associate laboratory director for computing, environment and life sciences at the Argonne National Lab-oratory in Lemont, Ill., says that SARS-CoV-2 is a member of the SARS coronavirus family and is, at 100 nanometers, one-thousandth the width of a human hair. The emergence and spread of antimicrobial resistance (AMR) mechanisms in bacterial pathogens, coupled with the dwindling number of effective antibiotics, has created a global health crisis. With recent breakthroughs in experimental microbiology making it possible to synthesize and implant an entire genome to create a living cell, the challenge of constructing a working blueprint for the first truly minimal synthetic organism is more important than ever. Between July 18(th) and 24(th) 2010, 26 leading microbial ecology, computation, bioinformatics and statistics researchers came together in Snowbird, Utah (USA) to discuss the challenge of how to best characterize the microbial world using next-generation sequencing technologies. “At Argonne National Laboratory we’re working on important research efforts including those focused on cancer, Covid-19, and many others, and using AI to automate parts of the development process is key to our success,” said Rick Stevens, associate laboratory director, Argonne National Laboratory, in a statement. In this paper, we analyze the performance characteristics of the benchmarks from the exploratory research project CANDLE (Cancer Distributed Learning Environment) with a focus on the hyperparameters epochs, batch sizes, and learnin... Background (0.39 MB TIF), The relative alignment length filtering parameter. Rick L. Stevens Title: Professor of Computer Science; Associate Laboratory Director, Computing, Environment and Life Sciences, Argonne National Laboratory Expertise: Exascale computing, Artificial intelligence, Performance modeling, Collaborative visualization environments, High-performance computer architecture Rick Stevens is Argonne’s Associate Laboratory Director for Computing, Environment and Life Sciences. Differences in the two genome sequences may add insights into the complex differences in the biology of both biotypes. Here we present a novel approach to annotate metagenomes using unique k-mer oligope... Metagenomics holds enormous promise for discovering novel enzymes and organisms that are biomarkers or drivers of processes relevant to disease, industry and the environment. "SambaNova is designed in some ways to bracket the performance that people typically see from GPUs," said Rick Stevens, associate laboratory director at Argonne… Nature Biotechnology 28, 969 (2010). © 2008-2020 ResearchGate GmbH. “Candidatus Portiera aleyrodidarum” is the obligate primary endosymbiotic bacterium of whiteflies, including the sweet potato whitefly Complexity, uniqueness, and periodic change have long been the top best practices for passwords, but new recommendations have led to changes around password policies. Yet without access to advanced computing resources in the US, China and Europe, these data would be just another survey. Rick Stevens is the Associate Laboratory Director of the Computing, Environment and Life Sciences Directorate at Argonne National Laboratory, and a Professor of Computer Science at the University of Chicago, with significant responsibility in delivering on the U.S. national initiative for Exascale computing and developing the DOE initiative in Artificial Intelligence (AI) for Science. The community has invested millions of dollars and years of effort to build key components. Argonne National Laboratory Describing microbial... Join ResearchGate to find the people and research you need to help your work. NVIDIA's GPU Technology Conference (GTC) is the must attend digital event for developers, researchers, engineers, and innovators looking to enhance their skills, exchange ideas, and gain a deeper understanding of how AI will transform their work. Rick Stevens . Being able to identify the genetic mechanisms of AMR and predict the resistance phenotypes of bacterial pathogens prior to culturing could inform clinical decis... A map of the transcriptional organization of genes of an organism is a basic tool that is necessary to understand and facilitate a more accurate genetic manipulation of the organism. (0.64 MB TIF). Responding to th... β-lactams are the most widely used antibacterials. Only verified researchers can join ResearchGate and send messages to other members. Stevens has been at Argonne since 1982, and has served as director of the Mathematics and Computer Science Division and also as Acting Associate Laboratory Director for Physical, Biological and Computing Sciences. (0.24 MB PDF), Sampling bias toward larger genomes in metagenomic libraries. We report two complete genome sequences of this bacterium GAAS relative abundance error (top), average genome size error (middle) and number of similarities (bottom) for the JGI simulated microbial metagenomes (∼1,200 bp/read). Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic models. Argonne National Laboratory's Rick Stevens talks about 'the biggest, baddest' computer in the world. Join Facebook to connect with Rick Stevens and others you may know. The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2-3 billion to deliver one new drug. Yet many aspects of B. subtilis are still poorly un... Two existing models of brain dynamics in epilepsy, one detailed (i.e., realistic) and one abstract (i.e., simplified) are compared in terms of behavioral range and match to in vitro mouse recordings. Accession numbers: CA, CAMERA Accession; GB, NCBI GenBank; GP, NCBI Genome Project; GSS, NCBI Genome Survey Sequence; MG: MG-RAST Accession; SRA, NCBI Short Read Archive. While most virtual screening problems present as a mix between ranking and classification, the models are typically trained as regression models presenting a problem requiring either a choice of a cutoff or ranking measure. Motivated by the size of cell line drug sensitivity data, researchers have been developing machine learning (ML) models for predicting drug response to advance cancer treatment. Facebook gives people the power to share and makes the... Jump to. The numbers reported are: mean (median) ± standard deviation. With the availability of hundreds and soon thousands of complete genomes, the construction of genome-scale metabolic models for these organisms has attracted much attention. Rick Stevens is a professor of computer science at the University of Chicago and Argonne National Laboratory. Rick STEVENS of Argonne National Laboratory, Illinois (ANL) | Read 248 publications | Contact Rick STEVENS Stevens will deliver the keynote at PEARC19, outlining the AI for Science initiative from Argonne. The backend is used as the foundation for many genome annot... A basic understanding of the relationship between activity of individual neurons and macroscopic electrical activity of local field potentials, or electroencephalogram {(EEG)}, may provide guidance for experimental design in neuroscience, improve development of therapeutic approaches in neurology, and offer opportunities for computer-aided design o... Reversibility constraints are one aspect of genome-scale metabolic models that has received significant attention recently. The Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center (https://www.patricbrc.org). server scripts. Examples of programming using the SEED servers (coded in Perl). In this paper, we apply transfer learning to the prediction of anti-cancer drug response. Method: Percentage of support for an AR (hierarchical cluster) is given by the percent of all possible gene-to-gene connections in the same cluster that have a corresponding high-scoring (above > SD4) CLR edge. The EMP has provided an unparrelled opportunity to explore the microbial diversity of planet earth. University students and faculty, institute members, and independent researchers, Technology or product developers, R&D specialists, and government or NGO employees in scientific roles, Health care professionals, including clinical researchers, Journalists, citizen scientists, or anyone interested in reading and discovering research. Collaborators. Although the investments in these separate software elements have been trem... Photometric variation in multi-projector displays is ar-guably the most vexing problem that needs to be addressed to achieve seamless tiled multi-projector displays. Rick Stevens is on Facebook. My research focuses on finding new ways to advance science and health outcomes using computation. Amazing goal. Background Stevens started programming at the age of 14 with IBM computer. To overcome these problems, we have developed... Rick will speak to experiences gained running the highly successful RAST and MG-RAST services for genome and metagenome sequence assembly and analysis. “At Argonne National Laboratory, we’re working on important research efforts including those focused on cancer, COVID-19, and many others, and using AI to automate parts of the development process is key to our success,” said Rick Stevens, associate laboratory director, Argonne National Laboratory. NVIDIA's GPU Technology Conference (GTC) is the must attend digital event for developers, researchers, engineers, and innovators looking to enhance their skills, exchange ideas, and gain a deeper understanding of how AI will transform their work. Rick Stevens, Associate Laboratory Director for Argonne’s Computing, Environment and Life Sciences (CELS) Directorate, will take part in a panel discussion that highlights how the scientific computing community is using HPC to advance COVID-19 research. Find out how . Scientists have Rick Stevens, Computing and Life Sciences Directorate Lead at the Argonne National Laboratory and an internationally recognized expert who helps drive the national agenda on computing was interviewed by David Geer, ITworld.com. Here we report two complete genome sequences of this bacterium from the B Stevens has been at Argonne since 1982, and has served as director of the Mathematics and Computer Science Division and also as Acting Associate Laboratory Director for Physical, Biological and Computing Sciences. Previous transfer learning studies for drug response prediction focused on bui... We explore three representative lines of research and demonstrate the utility of our methods on a classification benchmark of brain cancer MRI data. The database contains accurate and up-to-date annotations based on the subsystems concept that leverages clustering between genomes and other clues to accurately and efficiently annotate microbial genomes. (0.62 MB TIF), Effect of metagenomic sequence length on the accuracy of GAAS estimates. The additional file contains example code in Perl, Python, and Java that demonstrates how to access the SEED using SOAP. Stevens has been at Argonne since 1982, and has served as director of the Mathematics and Computer Science Division and also as Acting Associate Laboratory Director for … Title. “We weren’t even sure it was possible to build machines this fast,” said Rick Stevens, Argonne’s associate lab director for computing, environment and life sciences. In this talk we will discuss the role that high-performance computing and advanced data systems play in accelerating the transition of biology from a science primarily focused on description and explanation to a new science focused on systems level understanding and data driven predictive theories. Suggest someone you think fits with our community of curiosity today. (0.22 MB PDF), Accuracy of the GAAS estimates when no species are unknown. Rick Stevens is Associate Director for Computing, Environment and Life Sciences at Argonne’s National Laboratory. The remarkable advance in sequencing technology and the rising interest in medical and environmental microbiology, biotechnology, and synthetic biology resulted in a deluge of published microbial genomes. Microbes hold the key to life. Rick Stevens, Argonne National Laboratory. As drug sensitivity studies continue generating data, a common question is whether the proposed predictors can further improve the generalization performance with more trai... COVID-19 has claimed more 1 million lives and resulted in over 40 million infections. The last family member to visit his grave was my great grandmother in 1930. Rick Stevens Associate Laboratory Director Argonne National Laboratory Professor of Computer Science University of Chicago. Sched.com Conference Mobile Apps. First, high-level metrics were extracted from... Genome-scale metabolic models have proven to be valuable for predicting organism phenotypes from genotypes. Sequence length was 100 bp and no strains were treated as unknown. Rick Stevens Associate Laboratory Director, Argonne National Laboratory, Professor, University of Chicago Naperville, Illinois 500+ connections In this paper we train >35,000 neural network models, sweeping over common featurization techniques. Specifically, his research focuses on three principal areas: advanced collaboration and visualization environments, high-performance computer architectures (including Grids) and computational problems in the life sciences. Join Facebook to connect with Rick Stevens and others you may know. Transfer learning has been shown to be effective in many applications in which training data for the target problem are limited but data for a related (source) problem are abundant. Stevens is interested in the development of innovative tools and techniques that enable computational scientists to solve important large-scale problems effectively on advanced scientific computers.

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