A5101964384- Scientific Computing and Data Management
- Distributed and Parallel Computing Systems
- Advanced Data Storage Technologies
- Computational Drug Discovery Methods
- Big Data Technologies and Applications
- Research Data Management Practices
- Cloud Computing and Resource Management
- Protein Structure and Dynamics
- Cell Image Analysis Techniques
- Bioinformatics and Genomic Networks
- HER2/EGFR in Cancer Research
- Big Data and Business Intelligence
- Innovative Microfluidic and Catalytic Techniques Innovation
- vaccines and immunoinformatics approaches
- Monoclonal and Polyclonal Antibodies Research
- Gene Regulatory Network Analysis
- Software-Defined Networks and 5G
- Environmental Monitoring and Data Management
- Glycosylation and Glycoproteins Research
- Particle physics theoretical and experimental studies
- SARS-CoV-2 and COVID-19 Research
- Analog and Mixed-Signal Circuit Design
- Software System Performance and Reliability
- CAR-T cell therapy research
- Statistical and Computational Modeling
Institute of Bioorganic Chemistry
2025
Lomonosov Moscow State University
2019-2025
Brookhaven National Laboratory
2021-2024
Rutgers, The State University of New Jersey
2021
Rutgers Sexual and Reproductive Health and Rights
2021
NanoTechLabs (United States)
2021
Plekhanov Russian University of Economics
2020
Kurchatov Institute
2018-2019
The University of Texas at Arlington
2012
Despite the recent availability of vaccines against acute respiratory syndrome coronavirus 2 (SARS-CoV-2), search for inhibitory therapeutic agents has assumed importance especially in context emerging new viral variants. In this paper, we describe discovery a novel noncovalent small-molecule inhibitor, MCULE-5948770040, that binds to and inhibits SARS-Cov-2 main protease (Mpro) by employing scalable high-throughput virtual screening (HTVS) framework targeted compound library over 6.5...
Many extreme scale scientific applications have workloads comprised of a large number individual high-performance tasks. The Pilot abstraction decouples workload specification, resource management, and task execution via job placeholders late-binding. As such, suitable implementations the can support collective tasks on supercomputers. We introduce RADICAL-Pilot (RP) as portable, modular extensible pilot-enabled runtime system. describe RP's design, architecture implementation. characterize...
The race to meet the challenges of global pandemic has served as a reminder that existing drug discovery process is expensive, inefficient and slow. There major bottleneck screening vast number potential small molecules shortlist lead compounds for antiviral development. New opportunities accelerate lie at interface between machine learning methods, in this case, developed linear accelerators, physics-based methods. two
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 slow, especially emergencies like COVID-19 pandemic. In silico methodologies need be improved select better lead compounds, so as improve efficiency of later stages protocol, identify those compounds more quickly. No known methodological approach can this combination higher quality speed. Here, we describe an...
Despite the recent availability of vaccines against acute respiratory syndrome coronavirus 2 (SARS-CoV-2), search for inhibitory therapeutic agents has assumed importance especially in context emerging new viral variants. In this paper, we describe discovery a novel non-covalent small-molecule inhibitor, MCULE-5948770040, that binds to and inhibits SARS-Cov-2 main protease (M pro ) by employing scalable high throughput virtual screening (HTVS) framework targeted compound library over 6.5...
Exascale computers will offer transformative capabilities to combine data-driven and learning-based approaches with traditional simulation applications accelerate scientific discovery insight. These software combinations integrations, however, are difficult achieve due challenges of coordination deployment heterogeneous components on diverse massive platforms. We present the ExaWorks project, which can address many these challenges: is leading a co-design process create workflow Software...
COVID-19 has claimed more than 2.7 × 106 lives and resulted in over 124 infections. There is an urgent need to identify drugs that can inhibit SARS-CoV-2. We discuss innovations computational infrastructure methods are accelerating advancing drug design. Specifically, we describe several integrate artificial intelligence simulation-based approaches, the design of support these at scale. their implementation, characterize performance, highlight science advances capabilities have enabled.
Heterogeneous workflows represent a promising approach for overcoming traditional application performance limitations and to accelerate scientific insight on high-performance computing (HPC) platforms. As HPC platforms grow in size complexity, managing optimizing workflow resources while maximizing output assumes vital importance. Optimal resource allocation requires high-quality timely information about the state of hardware resources, status pending tasks, tasks that have already been...
Scientific workflows have become integral tools in broad scientific computing use cases. Science discovery is increasingly dependent on to orchestrate large and complex experiments that range from execution of a cloud-based data preprocessing pipeline multi-facility instrument-to-edge-to-HPC computational workflows. Given the changing landscape evolving needs emerging applications, it paramount development novel system functionalities seek increase efficiency, resilience, pervasiveness...
Metal additive manufacturing (AM) is a disruptive technology that opens the design space for parts outside those possible from traditional methods. In order to accelerate industry and R&D needs certify AM parts, Exascale Additive Manufacturing project (ExaAM) has developed suite of exascale-ready computational tools model process-to-structure-to-properties (PSP) relationship additively manufactured metal components. One such tool an uncertainty quantification (UQ) pipeline quantify effect in...
COVID-19 has claimed more 1 million lives and resulted in over 40 infections. There is an urgent need to identify drugs that can inhibit SARS-CoV-2. In response, the DOE recently established Medical Therapeutics project as part of National Virtual Biotechnology Laboratory, tasked it with creating computational infrastructure methods necessary advance therapeutics development. We discuss innovations are accelerating advancing drug design. Specifically, we describe several integrate artificial...
Big Data is supposed to be one of the main traits new coming digital era. Its technological aspects are usually widely discussed, whereas social peculiarities mostly neglected. We present approaches Data, and argue that despite seeming revolutionary technology, can treated as a tool produce knowledge. That means, it generates same risks challenges other breakthroughs we witnessed previously. To our viewpoint, cultural should counted issue in implementation. Since inability control big data...
One of the most important aspects in any computing distribution system is efficient data replication over storage or centers, that guarantees high availability and low cost for resource utilization. In this paper we propose a scheme production distributed analysis PanDA at ATLAS experiment. Our proposed based on investigation usage. Thus, focused main concepts popularity their Data represented as set parameters are used to predict future state terms levels.
Nowadays, many scientific workflows from different domains, such as Remote Sensing, Astronomy, and Bioinformatics, are executed on large computing infrastructures managed by resource managers. Scientific workflow management systems (SWMS) support the execution communicate with infrastructures' However, communication between SWMS managers is complicated a) inconsistent interfaces SMWS b) lack of for dependencies workflow-specific properties. To tackle these issues, we developed Common...