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. Computer Science Professor and Argonne Lab Director Rick Stevens talks about how the new Aurora Exascale Supercomputer will provide unprecedented capability to integrate data analytics and simulation for advanced 3D modeling. © 2008-2020 ResearchGate GmbH. Overview of HPC and AI Computing for COVID-19 in the US. “He will undoubtedly continue to contribute to the discipline at the highest level.” He framed the project around three points: 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. Bacillus subtilis is an organism of interest because of its extensive industrial applications, its similarity to pathogenic organisms, and its role as the model organism for Gram-positive, sporulating bacteria. The last family member to visit his grave was my great grandmother in 1930. Method: Percentage of support for an AR is given by the percent of genes in the AR that have at least one high-scoring CLR edge that links to another gene in the same AR. The additional file contains example code in Perl, Python, and Java that demonstrates how to access the SEED using SOAP. The relative alignment length is defined as the ratio of the length of the alignment over the length of the query sequence length, expressed in percent. (0.22 MB PDF), Accuracy of the GAAS estimates when no species are unknown. Check out what Rick Stevens will be attending at RMACC 2018 HPC Symposium. Rick L. 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. Rick STEVENS of Argonne National Laboratory, Illinois (ANL) | Read 248 publications | Contact Rick STEVENS (0.39 MB TIF), The relative alignment length filtering parameter. This includes helping Rick Stevens is a professor of computer science at the University of Chicago and Argonne National Laboratory. Sections of this page. Although the “big data” revolution first came to public prominence (circa 2010) in online enterprises like Google, Amazon, and Facebook, it is now widely recognized as the initial phase of a watershed transformation that modern society generally—and scientific and engineering research in particular—are in the process of undergoing. 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. (0.17 MB TIF), Biome averaged genome length estimated by GAAS for the metagenomes of each environment. Title. Rick Stevens Mathematics and Computer Science Division Argonne National Laboratory Abstract The emergence of virtual reality technology has introduced an exciting new approach to scientific research and development. Rick Stevens. These molfiles reflect the structure of the predominant ionic form of the compounds at neutral pH as predicted using the MarvinBeans software [28]. 9 Password policy recommendations: Here's what you need to know. 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. Among β-lactams, carbapenems are considered the last line of defense against recalcitrant infections. Amazing goal. 1. The power of the EMP is in the capability to turn these data in to descriptive and predictive models. Error was calculated for the relative abundance (top) and average genome length (bottom) estimates. In this paper we train >35,000 neural network models, sweeping over common featurization techniques. BLAST-based comparisons have typically been used for such analyses; however, sampling biases, high percentages of unknown sequences, and the use of arbitrary thresholds to find significant similarities can decrease the accuracy and val... Genome-scale metabolic models have emerged as a crucial resource for translating detailed knowledge of thousands of distinct enzymatic processes into global predictions of organism behavior [1]. Rick Stevens professor of computer science at the University of Chicago and leader of Argonne's Exascale computing initiative. This is a much tougher support criterion to meet than the criterion used in CLR Supplementary Table CS-1. and developing de novo annotations. Associate Director, Argonne National Laboratory. (0.32 MB PDF), Effect of using all similarities for microbial strains. View Rick Stevens's business profile as Associate Laboratory Director, Computing at Department of Energy - Argonne National Laboratory. Microbes hold the key to life. If there's anyone more bullish than Rick Stevens on the potential of computer science and biology, it's Kurzweil Examples of programming using the SEED servers (coded in Perl). The RAST (Rapid Annotation using Subsystem Technology) annotation engine was built in 2008 to annotate bacterial and archaeal genomes. From 2000-2004, Stevens served as Director of the National Science Foundation’s TeraGrid Project and from 1997-2001 as Chief Architect for the National Computational Science Alliance. The numbers reported are: mean (median) ± standard deviation. The two surfaces of each graph correspond to the average error ± the standard deviation for the >1,200 simulated metagenomes. Rick Stevens Associate Laboratory Director Argonne National Laboratory Professor of Computer Science University of Chicago. Today's annotation pipelines result in inconsistent gene assignments that complicate comparative analyses and prevent efficient construction of metabolic models. In this paper, we present a scalable real-time solution to correct the spatial photometric variation in multi-projector displays. 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. Rick Stevens is Argonne’s Associate Laboratory Director for Computing, Environment and Life Sciences. In the "big data" era, research biologists are faced with analyzing new types that usually require some level of computational expertise. 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. “Mike has made a significant positive impact on the field of computer science,” said Rick Stevens, Argonne associate laboratory director for Computing, Environment and Life Sciences. “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. The PathoSystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center funded by the National Institute of Allergy and Infectious Diseases (https://www.patricbrc.org). Learn more . Share . Sorry, you need to be a researcher to join ResearchGate. a comprehensive repertoire of the genome regions that are dispensable for growth of Bacillus subtilis in a variety of media conditions. The 2-day conference was held at the Kingkey Palace Hotel, Shenzhen, China, on the 14th-15th June 2011, and was hosted by BGI (formally the Beijing Genomics Institute). 80% of the species were treated as unknown. That’s how Rick Stevens, an associate director at Argonne National Laboratory in Lemont, Illinois, explains the unprecedented computational power of … Sessions from the most recent GTC in October are now available to … He is buried in the Meuse-Argonne American Cemetery. Rick STEVENS of Argonne National Laboratory, Illinois (ANL) | Read 247 publications | Contact Rick STEVENS Rick Stevens, Argonne National Laboratory: IBM Blue Gene Supercomputer Selected for DOE Advanced Research. Responding to th... β-lactams are the most widely used antibacterials. Rick Stevens, Associate Director of the Argonne National Laboratory (computing, environment, and life sciences) is also a professor at the University of Chicago, Department of Computer Science and holds senior fellow appointments in the University’s Computation Institute and the Institute for Genomics and Systems Biology. Consequently, there is a growing need for the development of data-driven and, in particular, deep learning methods for various tasks such as cancer diagnosis, detectio... Cancer is a complex disease, the understanding and treatment of which are being aided through increases in the volume of collected data and in the scale of deployed computing power. Managed by UChicago Argonne, LLC Since 1999, Rick Stevens has been a professor at the University of Chicago and since 2004, an Associate Laboratory Director at Argonne National Laboratory. Here, we establish 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. The work performed by Argonne will be in accordance with DOE’s contract with UChicago Argonne, LLC, for the operation of Argonne (Contract No. Nature Biotechnology 28, 969 (2010). Our limited understanding of the relationship between the behavior of individual neurons and large neuronal networks is an important limitation in current epilepsy research and may be one of the main causes of our inadequate ability to treat it. server scripts. 80% of the species in the viral simulated metagenomes were treated as unknown. In this paper, we apply transfer learning to the prediction of anti-cancer drug response. Rick Stevens is Argonne’s Associate Laboratory Director for Computing, Environment and Life Sciences. RICK L STEVENS of Argonne National Laboratory, Illinois (ANL) | Read 238 publications | Contact RICK L STEVENS Sequence length was 100 bp and no strains were treated as unknown. The text files may be copied into any spreadsheet program of choice to visualize the data for the iBsu1103 model. We didn't go to Reims, but enjoyed the Champagne Tour as a driving experience. The simulated viromes were made of 100 bp sequences. Watch the video . The increasing number of sequenced plant genomes is placing new demands on the methods applied to analyze, annotate, and model these genomes. David Geer: Today we’re talking with 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. Method: Percentage of support for an AR is given by the percent of all possible gene-to-gene connections in the same AR that have a corresponding high-scoring (above > SD4) CLR edge. 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. 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. Trish Damkroger (Intel) and Rick Stevens (Argonne) Discuss Exascale Computing with Aurora Junca, Stephanie November 5, 2020 November 6, 2020 Trish Damkroger, GM/VP Intel & Rick Stevens, Assoc Director at Argonne discuss how Exascale computing will speed discovery in cancer treatments, open new insights into astrophysics, and much more. There is an urgent need to identify drugs that can inhibit SARS-CoV-2. RMACC 2018 HPC Symposium has ended (0.27 MB TIF), Error surfaces for Figure S5. “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. 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. (PDF). 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 Stevens is a professor of computer science at the University of Chicago and Argonne National Laboratory. Cancer cell line (CCL) screening panels... We present a new method for understanding the performance of a model in virtual drug screening tasks. Yet efforts to develop new models are failing to keep pace with genome sequencing. The community has invested millions of dollars and years of effort to build key components. Suggest someone you think fits with our community of curiosity today. February 8, 2011. Abstract. See what Rick Stevens will be attending and learn more about the event taking place Aug 7 - 9, 2018 in Wolf Law Building, Kittredge Loop Drive, Boulder, CO, USA. Support for k-means clusters. A new method is introduced for comparing across computational models that may have very different forms. The ch... To enable the Life Science community to fully use TeraGrid resources for computing and data management, we developed an integrated cyber computational environment named the Open Life Science Gateway. 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. 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. Professor Rick Stevens is associate laboratory director of Argonne National Laboratory for Computing, Environment, and Life Sciences where he is responsible for research in computer science, mathematics, biology, ecology and the environment. 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