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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
NASA NTRS1976

Applicability of ERTS-1 to Montana geology

The author has identified the following significant results. Late autumn imagery provides the advantages of topographic shadow enhancement and low cloud cover. Mapping of rock units was done locally with good results for alluvium, basin fill, volcanics, inclined Paleozoic and Mesozoic beds, and host strata of bentonite beds. Folds, intrusive domes, and even dip directions were mapped where differential erosion was significant. However, mapping was not possible for belt strata, was difficult for granite, and was hindered by conifers compared to grass cover. Expansion of local mapping required geologic control and encountered significant areas unmappable from ERTS imagery. Annotation of lineaments provided much new geologic data. By extrapolating test site comparisons, it is inferred that 27 percent of some 1200 lineaments mapped from western Montana represent unknown faults. The remainder appear to be localized mainly by undiscovered faults and sets of minor faults or joints.

Weidman, R. M.↗
NASA NTRS1992

A proposed research program in information processing

The goal of the Formalized Software Development (FSD) project was to demonstrate improvements productivity of software development and maintenance through the use of a new software lifecycle paradigm. The paradigm calls for the mechanical, but human-guided, derivation of software implementations from formal specifications of the desired software behavior. It relies on altering a system's specification and rederiving its implementation as the standard technology for software maintenance. A system definition for this paradigm is composed of a behavioral specification together with a body of annotations that control the derivation of executable code from the specification. Annotations generally achieve the selection of certain data representations and/or algorithms that are consistent with, but not mandated by, the behavioral specification. In doing this, they may yield systems which exhibit only certain behaviors among multiple alternatives permitted by the behavioral specification. The FSD project proposed to construct a testbed in which to explore the realization of this new paradigm. The testbed was to provide operational support environment for software design, implementation, and maintenance. The testbed was proposed to provide highly automated support for individual programmers ('programming in the small'), but not to address the additional needs of programming teams ('programming in the large'). The testbed proposed to focus on supporting rapid construction and evolution of useful prototypes of software systems, as opposed to focusing on the problems of achieving production quality performance of systems.

Schorr, Herbert↗
NASA NTRS2011

High-Performance 3D Articulated Robot Display

In the domain of telerobotic operations, the primary challenge facing the operator is to understand the state of the robotic platform. One key aspect of understanding the state is to visualize the physical location and configuration of the platform. As there is a wide variety of mobile robots, the requirements for visualizing their configurations vary diversely across different platforms. There can also be diversity in the mechanical mobility, such as wheeled, tracked, or legged mobility over surfaces. Adaptable 3D articulated robot visualization software can accommodate a wide variety of robotic platforms and environments. The visualization has been used for surface, aerial, space, and water robotic vehicle visualization during field testing. It has been used to enable operations of wheeled and legged surface vehicles, and can be readily adapted to facilitate other mechanical mobility solutions. The 3D visualization can render an articulated 3D model of a robotic platform for any environment. Given the model, the software receives real-time telemetry from the avionics system onboard the vehicle and animates the robot visualization to reflect the telemetered physical state. This is used to track the position and attitude in real time to monitor the progress of the vehicle as it traverses its environment. It is also used to monitor the state of any or all articulated elements of the vehicle, such as arms, legs, or control surfaces. The visualization can also render other sorts of telemetered states visually, such as stress or strains that are measured by the avionics. Such data can be used to color or annotate the virtual vehicle to indicate nominal or off-nominal states during operation. The visualization is also able to render the simulated environment where the vehicle is operating. For surface and aerial vehicles, it can render the terrain under the vehicle as the avionics sends it location information (GPS, odometry, or star tracking), and locate the vehicle over or on the terrain correctly. For long traverses over terrain, the visualization can stream in terrain piecewise in order to maintain the current area of interest for the operator without incurring unreasonable resource constraints on the computing platform. The visualization software is designed to run on laptops that can operate in field-testing environments without Internet access, which is a frequently encountered situation when testing in remote locations that simulate planetary environments such as Mars and other planetary bodies.

Powell, Mark W.↗
DOE OSTI2021

Learning from Crowds by Modeling Common Confusions

Crowdsourcing provides a practical way to obtain large amounts of labeled data at a low cost. However, the annotation quality of annotators varies considerably, which imposes new challenges in learning a high-quality model from the crowdsourced annotations. In this work, we provide a new perspective to decompose annotation noise into common noise and individual noise and differentiate the source of confusion based on instance difficulty and annotator expertise on a per-instance-annotator basis. We realize this new crowdsourcing model by an end-to-end learning solution with two types of noise adaptation layers: one is shared across annotators to capture their commonly shared confusions, and the other one is pertaining to each annotator to realize individual confusion. To recognize the source of noise in each annotation, we use an auxiliary network to choose from the two noise adaptation layers with respect to both instances and annotators. Extensive experiments on both synthesized and real-world benchmarks demonstrate the effectiveness of our proposed common noise adaptation solution.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

KBase Silver Case Study: Determining Media Formulation Requirements for Isolation of Microbiome Constituents

KBase has powerful tools for extracting microbial genomes from metagenomes and performing phylogenomic analysis and metabolic modeling. These tools can be used to predict key media ingredients for isolating uncultured members of microbiomes. Essential to this process are high-quality genomes extracted from metagenomic assemblies, and Kbase has a tool for assessing the quality of genomes too. Below we identify growth factors for a myxobacteria ("slime bacteria") yet to be isolated from the rhizosphere of Miscanthus xgiganteus (hybrid of "Silvergrass"), cultivated at the Kellogg Biological Station in Michigan. Data was transferred with Globus from JGI-IMG. This narrative and the "KBase Gold Case Study: Can you find Delftia?" make up the Silver and Gold Narrative Set for teaching metagenomics concepts to students in the BIT 477/577 course at North Carolina State University. This tutorial will guide the user through the process of extracting and annotating high-quality genomes from a metagenomic data, performing phylogenomic analysis, building a metabolic model, and using these to predict nutrient requirments for growth and isolation of corresponding microbes.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1986

Multipolarization radar images for geologic mapping and vegetation discrimination

NASA has developed an airborne SAR that simultaneously yields image data in four linear polarizations in L-band with 10-m resolution over a swath of about 10 km. Signal data are recorded both optically and digitally and annotated in each of the channels to facilitate completely automated digital correlation. Comparison of the relative intensities of the different polarizations furnishes discriminatory mapping information. Local intensity variations in like-polarization images result from topographic effects, while strong cross polarization responses denote the effects of vegetation cover and, in some cases, possible scattering from the subsurface. In each of the areas studied, multiple polarization data led to the discrimination and mapping of unique surface unit features.

Evans, D. L.↗
DOE OSTI2019

MAGI: A Method for Metabolite Annotation and Gene Integration

Metabolomics is a widely used technology for obtaining direct measures of metabolic activities from diverse biological systems. However, ambiguous metabolite identifications are a common challenge and biochemical interpretation is often limited by incomplete and inaccurate genome-based predictions of enzyme activities (that is, gene annotations). Metabolite Annotation and Gene Integration (MAGI) generates a metabolite-gene association score using a biochemical reaction network. This is calculated by a method that emphasizes consensus between metabolites and genes via biochemical reactions. To demonstrate the potential of this method, we applied MAGI to integrate sequence data and metabolomics data collected from Streptomyces coelicolor A3(2), an extensively characterized bacterium that produces diverse secondary metabolites. Our findings suggest that coupling metabolomics and genomics data by scoring consensus between the two increases the quality of both metabolite identifications and gene annotations in this organism. MAGI also made biochemical predictions for poorly annotated genes that were consistent with the extensive literature on this important organism. Furthermore, this limited analysis suggests that using metabolomics data has the potential to improve annotations in sequenced organisms and also provides testable hypotheses for specific biochemical functions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2021-03)

This dataset contains layer-wise powder bed images from three different powder bed printing technologies – laser powder bed fusion, electron beam powder bed fusion, and binder jetting. This dataset was collected and annotated using the internally-developed Peregrine software tool and is designed primarily to facilitate research into anomaly defect detection using image segmentation or similar techniques. A total of 20 layers are provided for each printing technology, with each layer of data consisting of one or more calibrated images and an annotation file containing pixel-wise ground truth labels. The ground truths were labeled by domain experts, typically printer technicians. Data in this release were collected at Oak Ridge National Laboratory between 2016 and 2020 and were compiled in March 2021.

36 MATERIALS SCIENCE↗
DOE OSTI2021

MS2Planner: improved fragmentation spectra coverage in untargeted mass spectrometry by iterative optimized data acquisition

Motivation: Untargeted mass spectrometry experiments enable the profiling of metabolites in complex biological samples. The collected fragmentation spectra are the metabolite’s fingerprints that are used for molecule identification and discovery. Two main mass spectrometry strategies exist for the collection of fragmentation spectra: data-dependent acquisition (DDA) and data-independent acquisition (DIA). In the DIA strategy, all the metabolites ions in predefined mass-to-charge ratio ranges are co-isolated and co-fragmented, resulting in multiplexed fragmentation spectra that are challenging to annotate. In contrast, in the DDA strategy, fragmentation spectra are dynamically and specifically collected for the most abundant ions observed, causing redundancy and sub-optimal fragmentation spectra collection. Yet, DDA results in less multiplexed fragmentation spectra that can be readily annotated. Results: We introduce the MS2Planner workflow, an Iterative Optimized Data Acquisition strategy that optimizes the number of high-quality fragmentation spectra over multiple experimental acquisitions using topological sorting. Our results showed that MS2Planner increases the annotation rate by 38.6% and is 62.5% more sensitive and 9.4% more specific compared to DDA. Availability and implementation MS2Planner code is available at https://github.com/mohimanilab/MS2Planner. The generation of the inclusion list from MS2Planner was performed with python scripts available at https://github.com/lfnothias/IODA_MS.

47 OTHER INSTRUMENTATION↗
DOE OSTI2024

The secondary metabolism collaboratory: a database and web discussion portal for secondary metabolite biosynthetic gene clusters

Secondary metabolites are small molecules produced by all corners of life, often with specialized bioactive functions with clinical and environmental relevance. Secondary metabolite biosynthetic gene clusters (BGCs) can often be identified within DNA sequences by various sequence similarity tools, but determining the exact functions of genes in the pathway and predicting their chemical products can often only be done by careful, manual comparative analysis. To facilitate this, we report the first release of the secondary metabolism collaboratory (SMC), which aims to provide a comprehensive, tool-agnostic repository of BGC sequence data drawn from all publicly available and user-submitted bacterial and archaeal genome and contig sources. On the website, users are provided a searchable catalog of putative BGCs identified from each source, along with visualizations of gene and domain annotations derived from multiple sequence analysis tools. SMC’s data is also available through publicly-accessible application programming interface (API) endpoints to facilitate programmatic access. Users are encouraged to share their findings (and search for others’) through comment posts on BGC and source pages. At the time of writing, SMC is the largest repository of BGC information, holding 13.1M BGC regions from 1.3M source sequences and growing, and can be found at https://smc.jgi.doe.gov.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Full Integration of Lipidomics Data into Multi-OMIC Functional Enrichment

Lipids have numerous roles critical to living systems. Many of these vital functions are tightly linked or regulated by proteins. Even though the function of many lipid-related enzymes is known, direct links between most individual lipid species and the enzymes that metabolize them are severely lacking. This missing connection impedes biological progress. A resource that allows users to quickly identify protein-lipid relationships will advance our understanding of lipid homeostasis and metabolic perturbed systems. Databases are readily available for mapping small molecule metabolites (i.e., polar metabolites) and specific oxidized fatty acid lipids (e.g., arachidonic acid derivatives) to proteins/enzymes known to be directly involved in metabolism of these molecules (e.g. SMPDB, Reactome, HMDB, BioCyc). This enables the integration of metabolite and protein (as well as transcript) data when performing functional enrichment and metabolic modeling allowing researchers to rapidly examine metabolic pathways from multiple omics sources. Currently, linking lipidomics data with proteomics data is conducted using a time-intensive, user defined, manual process. Here we propose creating a tool that will link lipidomics and proteomics data and also conduct functional enrichment analysis and visualization allowing for full statistical integration. Using text-mining approaches, we will extract lipid references from uniprot and create a database linking lipid species to enzymes directly related to their metabolism. We will also extract directional annotation, which will allow even greater specificity when linking data types and will help eliminate false positives from functional associations.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning

Abstract The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), founding member of the Worldwide Protein Data Bank (wwPDB), is the US data center for the open-access PDB archive. As wwPDB-designated Archive Keeper, RCSB PDB is also responsible for PDB data security. Annually, RCSB PDB serves >10 000 depositors of three-dimensional (3D) biostructures working on all permanently inhabited continents. RCSB PDB delivers data from its research-focused RCSB.org web portal to many millions of PDB data consumers based in virtually every United Nations-recognized country, territory, etc. This Database Issue contribution describes upgrades to the research-focused RCSB.org web portal that created a one-stop-shop for open access to ∼200 000 experimentally-determined PDB structures of biological macromolecules alongside >1 000 000 incorporated Computed Structure Models (CSMs) predicted using artificial intelligence/machine learning methods. RCSB.org is a ‘living data resource.’ Every PDB structure and CSM is integrated weekly with related functional annotations from external biodata resources, providing up-to-date information for the entire corpus of 3D biostructure data freely available from RCSB.org with no usage limitations. Within RCSB.org, PDB structures and the CSMs are clearly identified as to their provenance and reliability. Both are fully searchable, and can be analyzed and visualized using the full complement of RCSB.org web portal capabilities.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes

Abstract For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical ‘Rosetta Stone’ to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org and KBase.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

WormBase in 2022—data, processes, and tools for analyzing Caenorhabditis elegans

WormBase (www.wormbase.org) is the central repository for the genetics and genomics of the nematode Caenorhabditis elegans. We provide the research community with data and tools to facilitate the use of C. elegans and related nematodes as model organisms for studying human health, development, and many aspects of fundamental biology. Throughout our 22-year history, we have continued to evolve to reflect progress and innovation in the science and technologies involved in the study of C. elegans. We strive to incorporate new data types and richer data sets, and to provide integrated displays and services that avail the knowledge generated by the published nematode genetics literature. Here, we provide a broad overview of the current state of WormBase in terms of data type, curation workflows, analysis, and tools, including exciting new advances for analysis of single-cell data, text mining and visualization, and the new community collaboration forum. Concurrently, we continue the integration and harmonization of infrastructure, processes, and tools with the Alliance of Genome Resources, of which WormBase is a founding member.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Multi-genome Phage Annotation Toolkit and Evaluator

Summary: To address the need for improved tools for annotation and comparative genomics of bacteriophage genomes, we developed multiPhATE2. As an extension of the multiPhATE code, multiPhATE2 includes comparative genomics codes for gene matching among sets of input bacteriophage genomes, and scales well to large input data sets due to incorporation of multiprocessing in the functional annotation and comparative genomics subsystems. Furthermore, additional search algorithms and databases have been added to the functional annotation subsystem. MultiPhATE2 was implemented in Python 3.7, and runs as a command-line code under Linux or MAC-OS.

Kimbrel, JeffreyA.↗
DOE OSTI2020

Leveraging computational genomics to understand the molecular basis of metal homeostasis

Genome-based data is helping to reveal the diverse strategies plants and algae use to maintain metal homeostasis. In addition to acquisition, distribution and storage of metals, acclimating to feast or famine can involve a wealth of genes that we are just now starting to understand. The fast-paced acquisition of genome-based data, however, is far outpacing our ability to experimentally characterize protein function. Computational genomic approaches are needed to fill the gap between what is known and unknown. To avoid misconstruing bioinformatically derived data, which is the root cause of the inaccurate functional annotations that plague databases, functional inferences from diverse sources and contextualization of that evidence with a robust understanding of protein family evolution is needed. Phylogenomic- and comparative-genomic-based studies can aid in the interpretation of experimental data or provide a spark for the discovery of a new function. These analyses not only lead to novel insight into a target protein's function but can generate thought-provoking insights across protein families.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

A Model Integration Pipeline for the Improvement of Human Genome-Scale Metabolic Reconstructions

Abstract Metabolism has been a major field of study in the last years, mainly due to its importance in understanding cell physiology and certain disease phenotypes due to its deregulation. Genome-scale metabolic models (GSMMs) have been established as important tools to help achieve a better understanding of human metabolism. Towards this aim, advances in systems biology and bioinformatics have allowed the reconstruction of several human GSMMs, although some limitations and challenges remain, such as the lack of external identifiers for both metabolites and reactions. A pipeline was developed to integrate multiple GSMMs, starting by retrieving information from the main human GSMMs and evaluating the presence of external database identifiers and annotations for both metabolites and reactions. Information from metabolites was included into a graph database with omics data repositories, allowing clustering of metabolites through their similarity regarding database cross-referencing. Metabolite annotation of several older GSMMs was enriched, allowing the identification and integration of common entities. Using this information, as well as other metrics, we successfully integrated reactions from these models. These methods can be leveraged towards the creation of a unified consensus model of human metabolism.

Vieira, Vítor↗
DOE OSTI2024

VIBES: a workflow for annotating and visualizing viral sequences integrated into bacterial genomes

Abstract Bacteriophages are viruses that infect bacteria. Many bacteriophages integrate their genomes into the bacterial chromosome and become prophages. Prophages may substantially burden or benefit host bacteria fitness, acting in some cases as parasites and in others as mutualists. Some prophages have been demonstrated to increase host virulence. The increasing ease of bacterial genome sequencing provides an opportunity to deeply explore prophage prevalence and insertion sites. Here we present VIBES (Viral Integrations in Bacterial genomES), a workflow intended to automate prophage annotation in complete bacterial genome sequences. VIBES provides additional context to prophage annotations by annotating bacterial genes and viral proteins in user-provided bacterial and viral genomes. The VIBES pipeline is implemented as a Nextflow-driven workflow, providing a simple, unified interface for execution on local, cluster and cloud computing environments. For each step of the pipeline, a container including all necessary software dependencies is provided. VIBES produces results in simple tab-separated format and generates intuitive and interactive visualizations for data exploration. Despite VIBES’s primary emphasis on prophage annotation, its generic alignment-based design allows it to be deployed as a general-purpose sequence similarity search manager. We demonstrate the utility of the VIBES prophage annotation workflow by searching for 178 Pf phage genomes across 1072 Pseudomonas spp. genomes.

59 BASIC BIOLOGICAL SCIENCES↗