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At least 1,423 records · Page 79

All sources NASA NTRS DOE OSTI

DOE OSTI2022

merlin , an improved framework for the reconstruction of high-quality genome-scale metabolic models

Abstract Genome-scale metabolic models have been recognised as useful tools for better understanding living organisms’ metabolism. merlin (https://www.merlin-sysbio.org/) is an open-source and user-friendly resource that hastens the models’ reconstruction process, conjugating manual and automatic procedures, while leveraging the user's expertise with a curation-oriented graphical interface. An updated and redesigned version of merlin is herein presented. Since 2015, several features have been implemented in merlin, along with deep changes in the software architecture, operational flow, and graphical interface. The current version (4.0) includes the implementation of novel algorithms and third-party tools for genome functional annotation, draft assembly, model refinement, and curation. Such updates increased the user base, resulting in multiple published works, including genome metabolic (re-)annotations and model reconstructions of multiple (lower and higher) eukaryotes and prokaryotes. merlin version 4.0 is the only tool able to perform template based and de novo draft reconstructions, while achieving competitive performance compared to state-of-the art tools both for well and less-studied organisms.

Capela, João (ORCID:0000000212352922)↗

DOE OSTI2026

From 2D to 4D: a containerized workflow and browser to explore dynamic chromatin architecture

Background Characterizing the physical organization of the genome is essential for understanding long-range gene regulation, chromatin compartmentalization, and epigenetic accessibility. Hi-C experiments generate two-dimensional (2D) genome-wide contact maps of chromatin interactions by capturing the spatial proximity between genomic loci, which reveal interaction frequencies but lack the spatial resolution needed to interpret the three-dimensional (3D) genome structure(s). Emerging evidence suggests that epigenetic regulation is closely linked to 3D genome architecture, and that structural changes over time (4D) drive key biological processes in development, disease, and environmental response. Thus, integrating 3D structure with functional data is critical for a more complete understanding of genome regulation. Previous work, most notably the 4DHiC chromosome modeling framework, has shown that physical multi-dimensional modeling approaches rooted in polymer physics and molecular dynamics can resolve these structures at biologically meaningful resolutions by integrating temporal Hi-C data with physical constraints to uncover dynamic chromosome reorganization. Thus, molecular dynamics simulations, constrained by Hi-C contact matrices, can resolve fine-scale structural changes and reveal functionally significant transitions in chromatin conformation. Results Herein, we present the 4D Genome Browser Workflow (4DGBWorkflow) and the 4D Genome Browser (4DGB). The algorithm is based on the 4DHiC method, and the containerized tool is an end-to-end workflow that can transform, filter, and view 4D epigenomics and chromatin datasets, allowing non-specialists to apply three-dimensional modeling principles to diverse datasets and experimental conditions. The software executes on a laptop running macOS, Linux or Windows. From input Hi-C files (.hic), the 4DGBWorkflow produces 3D reconstructions of chromosomes, integrates the reconstruction with track data (e.g., epigenetic marks, transcriptome profiles), and provides comparative visualization of the results in a single workflow. Conclusions The 4DGBWorkflow and 4D Genome Browser are open-source tools for comparative analysis and visualization of 4D chromosome datasets, including chromatin architecture and epigenomic signals. Automatic integration of Hi-C data with molecular dynamics democratizes the construction of time resolved 3D genome structures, simplifying complex simulations and data integration schemes.

3D Genome Browser↗

DOE OSTI2011

JBluIce-EPICS control system for macromolecular crystallography.

The trio of macromolecular crystallography beamlines constructed by the General Medicine and Cancer Institutes Collaborative Access Team (GM/CA-CAT) in Sector 23 of the Advanced Photon Source (APS) have been in growing demand owing to their outstanding beam quality and capacity to measure data from crystals of only a few micrometres in size. To take full advantage of the state-of-the-art mechanical and optical design of these beamlines, a significant effort has been devoted to designing fast, convenient, intuitive and robust beamline controls that could easily accommodate new beamline developments. The GM/CA-CAT beamline controls are based on the power of EPICS for distributed hardware control, the rich Java graphical user interface of Eclipse RCP and the task-oriented philosophy as well as the look and feel of the successful SSRL BluIce graphical user interface for crystallography. These beamline controls feature a minimum number of software layers, the wide use of plug-ins that can be written in any language and unified motion controls that allow on-the-fly scanning and optimization of any beamline component. This paper describes the ways in which BluIce was combined with EPICS and converted into the Java-based JBluIce, discusses the solutions aimed at streamlining and speeding up operations and gives an overview of the tools that are provided by this new open-source control system for facilitating crystallographic experiments, especially in the field of microcrystallography.

43 PARTICLE ACCELERATORS↗

DOE OSTI2022

DEIMoS: An Open-Source Tool for Processing High-Dimensional Mass Spectrometry Data

Not Available

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

WeightedAFL

WeightedAFL (WAFL) is an improvement to open source fuzzer, American Fuzzy Lop (AFL). Fuzzers modify input to target programs in order to produce crashes and other unintended output in those target programs. WAFL integrates directly with AFL to determine offsets within a buffer that will improve performance metrics. WAFL uses various machine learning techniques to learn these offsets. WAFL also provides a novel software engineering solution to integrate with AFL and allows contributors to quickly write and test algorithms in python. SAND2020-12546 O Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-NA0003525.

Kincher-Winoto, Kina↗

DOE OSTI2023

PVade (PV Aerodynamic Design Engineering) [SWR-23-49]

PV Aerodynamic Design Engineering (PVade) is an open-source fluid-structure interaction (FSI) solver which can accurately simulate wind loads and aerodynamic stability in solar-tracking PV arrays. PVade’s pressure profiles and inertial load time series can be used as inputs into mechanical module models to study degradation mechanisms including cracking of cells, weathering of cracked cells, and glass breakage. This software enables PV plant owners to predict optimal high-wind stow strategies under a variety of weather and site conditions.

Young, Ethan↗

DOE OSTI2015

Sandia Simple Particle Tracking (Sandia SPT) v. 1.0

Sandia SPT is designed as software to accompany a book chapter being published a methods chapter which provides an introduction on how to label and track individual proteins. The Sandia Simple Particle Tracking code uses techniques common to the image processing community, where its value is that it facilitates implementing the methods described in the book chapter by providing the necessary open-source code. The code performs single particle spot detection (or segmentation and localization) followed by tracking (or connecting the detected particles into trajectories). The book chapter, which along with the headers in each file, constitutes the documentation for the code is: Anthony, S.M.; Carroll-Portillo, A.; Timlon, J.A., Dynamics and Interactions of Individual Proteins in the Membrane of Living Cells. In Anup K. Singh (Ed.) Single Cell Protein Analysis Methods in Molecular Biology. Springer

Anthony, StephenM.↗

DOE OSTI2023

GridSweep Processing and Graphing Software v1.0

This software is used to process the raw data from the GridSweep instrument, a device developed under subcontract by McEachern Laboroatories for a DOE GMLC project. The software scrubbs, demodulates, and transforms point on wave voltage timeseries data into frequency/voltage amplitude/time data. It also has a GUI that allows for user selection of processed experimental data and graphing in heatmaps or 3-D plots. It was created alongside the GridSweep instrument as a part of the same project and is required to be open-source.

McEachern, Alex↗

DOE OSTI2015

Sandia Simple Particle Tracking (Sandia SPT) v. 1.0

Anthony, Stephen M.↗

DOE OSTI2022

Agile Acceleration of LLVM Flang Support for Fortran 2018 Parallel Programming

The LLVM Flang compiler ("Flang") is currently Fortran 95 compliant, and the frontend can parse Fortran 2018. However, Flang does not have a comprehensive 2018 test suite and does not fully implement the static semantics of the 2018 standard. We are investigating whether agile software development techniques, such as pair programming and test-driven development (TDD), can help Flang to rapidly progress to Fortran 2018 compliance. Because of the paramount importance of parallelism in high-performance computing, we are focusing on Fortran’s parallel features, commonly denoted “Coarray Fortran.” We are developing what we believe are the first exhaustive, open-source tests for the static semantics of Fortran 2018 parallel features, and contributing them to the LLVM project. A related effort involves writing runtime tests for parallel 2018 features and supporting those tests by developing a new parallel runtime library: the CoArray Fortran Framework of Efficient Interfaces to Network Environments (Caffeine).

Rasmussen, Katherine↗

DOE OSTI2023

PeleLMeX: an AMR Low Mach Number Reactive Flow Simulation Code without level sub-cycling

PeleLMeX simulates chemically reacting low Mach number flows with block-structured adaptive mesh refinement (AMR). The code is built upon the AMReX library, which provides the underlying data structures and tools to manage and operate on them across massively parallel computing architectures. PeleLMeX algorithmic features are inherited from its predecessor PeleLM but key improvements allow representation of more complex physical processes. Together with its compressible flow counterpart PeleC, the thermo-chemistry library PelePhysics and the multi-physics library PeleMP, it forms the Pele suite of open-source reactive flow simulation codes.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

The 4D Camera: An 87 kHz Direct Electron Detector for Scanning/Transmission Electron Microscopy

We describe the development, operation, and application of the 4D Camera—a 576 by 576 pixel active pixel sensor for scanning/transmission electron microscopy which operates at 87,000 Hz. The detector generates data at ~480 Gbit/s which is captured by dedicated receiver computers with a parallelized software infrastructure that has been implemented to process the resulting 10–700 Gigabyte-sized raw datasets. The back illuminated detector provides the ability to detect single electron events at accelerating voltages from 30 to 300 kV. Through electron counting, the resulting sparse data sets are reduced in size by 10--300× compared to the raw data, and open-source sparsity-based processing algorithms offer rapid data analysis. The high frame rate allows for large and complex scanning diffraction experiments to be accomplished with typical scanning transmission electron microscopy scanning parameters.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Control And Optimization Modular Modeling Application For Nuclear Deployment

The purpose of the COMMAND code is to provide a flexible, scalable tool for use in developing, integrating, and testing the technologies necessary for achieving autonomous operations of advanced nuclear reactors. The code enables users to efficiently implement custom simulations and experiments by combining key methods from different software modules. These modules are focused on: modeling and simulation tools, such as nuclear simulation tools used for high-fidelity modeling (e.g., Reactor Excursion and Leak Analysis Program [RELAP5-3D] and Monte Carlo N-Particle [MCNP]); machine learning and optimization tools (e.g., anomaly detection and data-driven modeling techniques); advanced control in its digital, high-performance, and supervisory control forms (e.g., proportional integral derivative (PID) control and model predictive control (MPC); and integration with hardware through industrial communication protocols. To ensure flexibility and scalability, COMMAND was designed to be both modular—the software “pieces” all inherit from generic building blocks and can be combined and connected to create complicated simulations—and high performing—designed for parallel processing, enabling simulations and experiments to take advantage of multi-core computers, servers, and nodes. The code is written in the Python programming language due to the language's popularity, active community, and open-source and cross-platform nature. Maintaining consistency with other simulation tools used within the nuclear energy community, users implement simulations and experiments through text input files, which define components, parameters, connections, etc., through lines of text. Given that COMMAND is written in Python, these input files are native Python scripts, and so use the standard Python structure and formatting. This also enables users to take advantage of Python's extensive package library to develop custom capabilities for their specific use cases.

Faber, Jacob [Idaho National Laboratory (INL), Ida↗

DOE OSTI2017

Domain Specific Language Support for Exascale

Domain-Specific Languages (DSLs) offer an attractive path to Exascale software since they provide expressive power through appropriate abstractions and enable domain-specific optimizations. But the advantages of a DSL compete with the difficulties of implementing a DSL, even for a narrowly defined domain. The DTEC project addresses how a variety of DSLs can be easily implemented to leverage existing compiler analysis and transformation capabilities within the ROSE open source compiler as part of a research program focusing on Exascale challenges. The OSU contributions to the DTEC project are in the area of code generation from high-level DSL descriptions, as well as verification of the automatically-generated code.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

High-Performance First-Principles Molecular Dynamics for Predictive Theory and Modeling

This project focused on developing high-performance software tools for First-Principles Molecular Dynamics (FPMD) simulations, and applying them in investigations of materials relevant to energy conversion processes. FPMD is an atomistic simulation method that combines a quantum-mechanical description of electronic structure with the statistical description provided by molecular dynamics (MD) simulations. This reliance on fundamental principles allows FPMD simulations to provide a consistent description of structural, dynamical and electronic properties of a material. This is particularly useful in systems for which reliable empirical models are lacking. FPMD simulations are increasingly used as a predictive tool for applications such as batteries, solar energy conversion, light-emitting devices, electro-chemical energy conversion devices and other materials. During the course of the project, several new features were developed and added to the open-source Qbox FPMD code. The code was further optimized for scalable operation of large-scale, Leadership-Class DOE computers. When combined with Many-Body Perturbation Theory (MBPT) calculations, this infrastructure was used to investigate structural and electronic properties of liquid water, ice, aqueous solutions, nanoparticles and solid-liquid interfaces. Computing both ionic trajectories and electronic structure in a consistent manner enabled the simulation of several spectroscopic properties, such as Raman spectra, infrared spectra, and sum-frequency generation spectra. The accuracy of the approximations used allowed for direct comparisons of results with experimental data such as optical spectra, X-ray and neutron diffraction spectra. The software infrastructure developed in this project, as applied to various investigations of solids, liquids and interfaces, demonstrates that FPMD simulations can provide a detailed, atomic-scale picture of structural, vibrational and electronic properties of complex systems relevant to energy conversion devices.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2019

MBMS1.0: An Open-Source Code for Modeling and Simulation of Membrane-Based Dehumidification and Energy Recovery

Air dehumidification processes are important and significantly impact both the performance of building ventilation and air conditioning systems, and the health of occupants. In a membrane-based dehumidifier, a permselective membrane is adopted to separate the two flow streams at feed and permeate sides. The feed side is continuously supplied with humid air at atmospheric pressure, while the permeate side is connected to a vacuum pump to produce vacuum or a low permeate vapor pressure as a driving force for water vapor permeation. The software MBMS 1.0 enables modeling and simulation of the design and configuration optimization of a membrane-based air-to-air (A2A) or air-to-vapor (A2V) device. A first-order physical-constant model was developed to reasonably account for the fundamental heat and mass transfer processes involved.

Gao, Zhiming↗

DOE OSTI2014

BioenergyKDF: Enabling Spatiotemporal Data Synthesis and Research Collaboration

The Bioenergy Knowledge Discovery Framework (BioenergyKDF) is a scalable, web-based collaborative environment for scientists working on bioenergy related research in which the connections between data, literature, and models can be explored and more clearly understood. The fully-operational and deployed system, built on multiple open source libraries and architectures, stores contributions from the community of practice and makes them easy to find, but that is just its base functionality. The BioenergyKDF provides a national spatiotemporal decision support capability that enables data sharing, analysis, modeling, and visualization as well as fosters the development and management of the U.S. bioenergy infrastructure, which is an essential component of the national energy infrastructure. The BioenergyKDF is built on a flexible, customizable platform that can be extended to support the requirements of any user community especially those that work with spatiotemporal data. While there are several community data-sharing software platforms available, some developed and distributed by national governments, none of them have the full suite of capabilities available in BioenergyKDF. For example, this component-based platform and database independent architecture allows it to be quickly deployed to existing infrastructure and to connect to existing data repositories (spatial or otherwise). As new data, analysis, and features are added; the BioenergyKDF will help lead research and support decisions concerning bioenergy into the future, but will also enable the development and growth of additional communities of practice both inside and outside of the Department of Energy. These communities will be able to leverage the substantial investment the agency has made in the KDF platform to quickly stand up systems that are customized to their data and research needs.

Bioenergy.↗

DOE OSTI2023

Catalyst: Fast and flexible modeling of reaction networks

We introduce Catalyst.jl, a flexible and feature-filled Julia library for modeling and high-performance simulation of chemical reaction networks (CRNs). Catalyst supports simulating stochastic chemical kinetics (jump process), chemical Langevin equation (stochastic differential equation), and reaction rate equation (ordinary differential equation) representations for CRNs. Through comprehensive benchmarks, we demonstrate that Catalyst simulation runtimes are often one to two orders of magnitude faster than other popular tools. More broadly, Catalyst acts as both a domain-specific language and an intermediate representation for symbolically encoding CRN models as Julia-native objects. This enables a pipeline of symbolically specifying, analyzing, and modifying CRNs; converting Catalyst models to symbolic representations of concrete mathematical models; and generating compiled code for numerical solvers. Leveraging ModelingToolkit.jl and Symbolics.jl, Catalyst models can be analyzed, simplified, and compiled into optimized representations for use in numerical solvers. Finally, we demonstrate Catalyst’s broad extensibility and composability by highlighting how it can compose with a variety of Julia libraries, and how existing open-source biological modeling projects have extended its intermediate representation.

59 BASIC BIOLOGICAL SCIENCES↗