Rick Stevens
University of Chicago
Deep learningMachine learningDistributed computingComputer graphics (images)GenomeArtificial intelligenceParallel computingVirtual realityData scienceSoftwareVisualizationComputer scienceMultimediaArtificial neural networkGeneticsComputational biologySupercomputerBiology
221Publications
56H-index
25.3kCitations
Publications 216
Newest
#1Romain Egele (École Polytechnique)H-Index: 3
#2Prasanna Balaprakash (Argonne National Laboratory)H-Index: 22
Last. Zhengying LiuH-Index: 4
view all 7 authors...
Developing high-performing predictive models for large tabular data sets is a challenging task. Neural architecture search (NAS) is an AutoML approach that generates and evaluates multiple neural networks with different architectures concurrently to automatically discover an high performing model. A key issue in NAS, particularly for large data sets, is the large computation time required to evaluate each generated architecture. While data-parallel training has the potential to address this issu...
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#1Margo VanOeffelenH-Index: 3
#2Marcus Nguyen (U of C: University of Chicago)H-Index: 8
Last. Gordon D. PuschH-Index: 25
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Antimicrobial resistance (AMR) is a major global health threat that affects millions of people each year. Funding agencies worldwide and the global research community have expended considerable capital and effort tracking the evolution and spread of AMR by isolating and sequencing bacterial strains and performing antimicrobial susceptibility testing (AST). For the last several years, we have been capturing these efforts by curating data from the literature and data resources and building a set o...
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#1Pedro J BallesterH-Index: 1
#2Rick Stevens (U of C: University of Chicago)H-Index: 56
Last. Tero Aittokallio (University of Oslo)H-Index: 56
view all 5 authors...
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#5Mathis Bode (RWTH Aachen University)H-Index: 1
#7Mikhail Titov (RU: Rutgers University)H-Index: 2
Last. Matteo Turilli (RU: Rutgers University)H-Index: 10
view all 29 authors...
The race to meet the challenges of the global pandemic has served as a reminder that the existing drug discovery process is expensive, inefficient and slow. There is a major bottleneck screening th...
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#1Anda Trifan (UIUC: University of Illinois at Urbana–Champaign)H-Index: 7
#2Defne Gorgun (UIUC: University of Illinois at Urbana–Champaign)H-Index: 1
Last. Arvind Ramanathan (Argonne National Laboratory)H-Index: 8
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The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) replication transcription complex (RTC) is a multi-domain protein responsible for replicating and transcribing the viral mRNA inside a human cell. Attacking RTC function with pharmaceutical compounds is a pathway to treating COVID-19. Conventional tools, e.g., cryo-electron microscopy and all-atom molecular dynamics (AAMD), do not provide sufficiently high resolution or timescale to capture important dynamics of this molecular mach...
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#1James J. Davis (Argonne National Laboratory)H-Index: 23
#2Long Sw (Houston Methodist Hospital)H-Index: 6
Last. James M. Musser (Houston Methodist Hospital)H-Index: 125
view all 9 authors...
ABSTRACT null The ARTIC Network provides a common resource of PCR primer sequences and recommendations for amplifying SARS-CoV-2 genomes. The initial tiling strategy was developed with the reference genome Wuhan-01, and subsequent iterations have addressed areas of low amplification and sequence drop out. Recently, a new version (V4) was released, based on new variant genome sequences, in response to the realization that some V3 primers were located in regions with key mutations. Herein, we comp...
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#1Austin ClydeH-Index: 5
#2Ashka ShahH-Index: 2
Last. Rick StevensH-Index: 56
view all 5 authors...
Scaffold based drug discovery (SBDD) is a technique for drug discovery which pins chemical scaffolds as the framework of design. Scaffolds, or molecular frameworks, organize the design of compounds into local neighborhoods. We formalize scaffold based drug discovery into a network design. Utilizing docking data from SARS-CoV-2 virtual screening studies and JAK2 kinase assay data, we showcase how a scaffold based conception of chemical space is intuitive for design. Lastly, we highlight the utili...
#1Aymen Al Saadi (RU: Rutgers University)H-Index: 2
#2Dario Alfè (University of Naples Federico II)H-Index: 70
Last. Austin Clyde (U of C: University of Chicago)H-Index: 5
view all 36 authors...
The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2–3 billion to deliver one new drug. This is both too expensive and too slow, especially in emergencies like the COVID-19 pandemic. In silico methodologies need to be improved both to select better lead compounds, so as to improve the efficiency of later stages in the drug discovery protocol, and to identify those lead compounds more quickly. No known methodological approach can de...
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#1Hyungro Lee (RU: Rutgers University)H-Index: 11
#2Andre Merzky (RU: Rutgers University)H-Index: 21
Last. Peter V. Coveney (UCL: University College London)H-Index: 75
view all 0 authors...
COVID-19 has claimed more than 2.7 × 106 lives and resulted in over 124 × 106 infections. There is an urgent need to identify drugs that can inhibit SARS-CoV-2. We discuss innovations in computational infrastructure and methods that are accelerating and advancing drug design. Specifically, we describe several methods that integrate artificial intelligence and simulation-based approaches, and the design of computational infrastructure to support these methods at scale. We discuss their implementa...
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#1Yitan Zhu (Argonne National Laboratory)H-Index: 3
#2Thomas Brettin (Argonne National Laboratory)H-Index: 55
Last. Rick Stevens (U of C: University of Chicago)H-Index: 56
view all 9 authors...
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