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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

NP-MRD: the Natural Products Magnetic Resonance Database

The Natural Products Magnetic Resonance Database (NP-MRD) is a comprehensive, freely available electronic resource for the deposition, distribution, searching and retrieval of nuclear magnetic resonance (NMR) data on natural products, metabolites and other biologically derived chemicals. NMR spectroscopy has long been viewed as the ‘gold standard’ for the structure determination of novel natural products and novel metabolites. NMR is also widely used in natural product dereplication and the characterization of biofluid mixtures (metabolomics). All of these NMR applications require large collections of high quality, well-annotated, referential NMR spectra of pure compounds. Unfortunately, referential NMR spectral collections for natural products are quite limited. It is because of the critical need for dedicated, open access natural product NMR resources that the NP-MRD was funded by the National Institute of Health (NIH). Since its launch in 2020, the NP-MRD has grown quickly to become the world's largest repository for NMR data on natural products and other biological substances. It currently contains both structural and NMR data for nearly 41,000 natural product compounds from >7400 different living species. All structural, spectroscopic and descriptive data in the NP-MRD is interactively viewable, searchable and fully downloadable in multiple formats. Extensive hyperlinks to other databases of relevance are also provided. The NP-MRD also supports community deposition of NMR assignments and NMR spectra (1D and 2D) of natural products and related meta-data. The deposition system performs extensive data enrichment, automated data format conversion and spectral/assignment evaluation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

NMPFamsDB: a database of novel protein families from microbial metagenomes and metatranscriptomes

Abstract The Novel Metagenome Protein Families Database (NMPFamsDB) is a database of metagenome- and metatranscriptome-derived protein families, whose members have no hits to proteins of reference genomes or Pfam domains. Each protein family is accompanied by multiple sequence alignments, Hidden Markov Models, taxonomic information, ecosystem and geolocation metadata, sequence and structure predictions, as well as 3D structure models predicted with AlphaFold2. In its current version, NMPFamsDB hosts over 100 000 protein families, each with at least 100 members. The reported protein families significantly expand (more than double) the number of known protein sequence clusters from reference genomes and reveal new insights into their habitat distribution, origins, functions and taxonomy. We expect NMPFamsDB to be a valuable resource for microbial proteome-wide analyses and for further discovery and characterization of novel functions. NMPFamsDB is publicly available in http://www.nmpfamsdb.org/ or https://bib.fleming.gr/NMPFamsDB.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Genomes OnLine Database (GOLD) v.10: new features and updates

The Genomes OnLine Database (GOLD; https://gold.jgi.doe.gov/) at the Department of Energy Joint Genome Institute is a comprehensive online metadata repository designed to catalog and manage information related to (meta)genomic sequence projects. GOLD provides a centralized platform where researchers can access a wide array of metadata from its four organization levels namely Study, Organism/Biosample, Sequencing Project and Analysis Project. GOLD continues to serve as a valuable resource and has seen significant growth and expansion since its inception in 1997. With its expanded role as a collaborative platform, it not only actively imports data from other primary repositories like National Center for Biotechnology Information but also supports contributions from researchers worldwide. This collaborative approach has enriched the database with diverse datasets, creating a more integrated resource to enhance scientific insights. As genomic research becomes increasingly integral to various scientific disciplines, more researchers and institutions are turning to GOLD for their metadata needs. To meet this growing demand, GOLD has expanded by adding diverse metadata fields, intuitive features, advanced search capabilities and enhanced data visualization tools, making it easier for users to find and interpret relevant information. This manuscript provides an update and highlights the new features introduced over the last 2 years.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

metagRoot: a comprehensive database of protein families associated with plant root microbiomes

The plant root microbiome is vital in plant health, nutrient uptake, and environmental resilience. To explore and harness this diversity, we present metagRoot, a specialized and enriched database focused on the protein families of the plant root microbiome. MetagRoot integrates metagenomic, metatranscriptomic, and reference genome-derived protein data to characterize 71 091 enriched protein families, each containing at least 100 sequences. These families are annotated with multiple sequence alignments, CRISPR elements, hidden Markov models, taxonomic and functional classifications, ecosystem and geolocation metadata, and predicted 3D structures using AlphaFold2. MetagRoot is a powerful tool for decoding the molecular landscape of root-associated microbial communities and advancing microbiome-informed agricultural practices by enriching protein family information with ecological and structural context. The database is available at https://pavlopoulos-lab.org/metagroot/ or https://www.metagroot.org.

Chasapi, Maria N↗
DOE OSTI2014

RNAcentral: an international database of ncRNA sequences

The field of non-coding RNA biology has been hampered by the lack of availability of a comprehensive, up-to-date collection of accessioned RNA sequences. Here we present the first release of RNAcentral, a database that collates and integrates information from an international consortium of established RNA sequence databases. The initial release contains over 8.1 million sequences, including representatives of all major functional classes. A web portal (http://rnacentral.org) provides free access to data, search functionality, cross-references, source code and an integrated genome browser for selected species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

RNAcentral: A comprehensive database of non-coding RNA sequences

RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. Furthermore, the website has been subject to continuous improvements focusing on text and sequence similarity searches as well as genome browsing functionality.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

SCOPe: classification of large macromolecular structures in the structural classification of proteins—extended database

The SCOPe (Structural Classification of Proteins—extended, https://scop.berkeley.edu) database hierarchically classifies domains from the majority of proteins of known structure according to their structural and evolutionary relationships. SCOPe also incorporates and updates the ASTRAL compendium, which provides multiple databases and tools to aid in the analysis of the sequences and structures of proteins classified in SCOPe. Protein structures are classified using a combination of manual curation and highly precise automated methods. In the current release of SCOPe, 2.07, we have focused our manual curation efforts on larger protein structures, including the spliceosome, proteasome and RNA polymerase I, as well as many other Pfam families that had not previously been classified. Domains from these large protein complexes are distinctive in several ways: novel non-globular folds are more common, and domains from previously observed protein families often have N- or C-terminal extensions that were disordered or not present in previous structures. The current monthly release update, SCOPe 2.07–2018-10–18, classifies 90 992 PDB entries (about two thirds of PDB entries).

Biochemistry & Molecular Biology↗
DOE OSTI2025

Expansion of the tmRNA sequence database and new tools for search and visualization

Abstract Transfer–messenger RNA (tmRNA) contributes essential tRNA-like and mRNA-like functions during the process of trans-translation, a mechanism of quality control for the translating bacterial ribosome. Proper tmRNA identification benefits the study of trans-translation and also the study of genomic islands, which frequently use the tmRNA gene as an integration site. Automated tmRNA gene identification tools are available, but manual inspection is still important for eliminating false positives. We have increased our database of precisely mapped tmRNA sequences over 50-fold to 97 179 unique sequences. Group I introns had previously been found integrated within a single subsite within the TψC-loop; they have now been identified at four distinct subsites, suggesting multiple founding events of invasion of tmRNA genes by group I introns, all in the same vicinity. tmRNA genes were found in metagenomic archaeal genomes, perhaps a result of misbinning of bacterial sequences during genome assembly. With the expanded database, we have produced new covariance models for improved tmRNA sequence search and new secondary structure visualization tools.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

First-principles equation of state database for warm dense matter computation

We put together a first-principles equation of state (FPEOS) database for matter at extreme conditions by combining results from path integral Monte Carlo and density functional molecular dynamics simulations of the elements H, He, B, C, N, O, Ne, Na, Mg, Al, and Si as well as the compounds LiF , B 4 C , BN , CH 4 , CH 2 , C 2 H 3 , CH , C 2 H , MgO , and MgSiO 3 . For all these materials, we provide the pressure and internal energy over a density-temperature range from ~ 0.5 to 50 g cm - 3 and from ~ 10 4 to 10 9 K, which are based on ~ 5000 different first-principles simulations. We compute isobars, adiabats, and shock Hugoniot curves in the regime of L - and K -shell ionization. Invoking the linear mixing approximation, we study the properties of mixtures at high density and temperature. Furthermore, we derive the Hugoniot curves for water and alumina as well as for carbon-oxygen, helium-neon, and CH-silicon mixtures. We predict the maximal shock compression ratios of H 2 O , H 2 O 2 , Al 2 O 3 , CO , and CO 2 to be 4.61, 4.64, 4.64, 4.89, and 4.83, respectively. Finally we use the FPEOS database to determine the points of maximum shock compression for all available binary mixtures. We identify mixtures that reach higher shock compression ratios than their end members. We discuss trends common to all mixtures in pressure-temperature and particle-shock velocity spaces. In the Supplemental Material, we provide all FPEOS tables as well as computer codes for interpolation, Hugoniot calculations, and plots of various thermodynamic functions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Statistics on magnetic properties of Co compounds: A database-driven method for discovering Co-based ferromagnets

The search for new ferromagnetic compounds is often targeted at known structure families, particularly those containing iron, cobalt, and manganese. Here, we propose a method to expand this search to lesser-known structure types, using a database of experimental Curie and Néel temperatures. This study, in particular, illustrates the case of compounds containing the element cobalt, and we demonstrate how the use of such a database can lead to the discovery of ferromagnetic materials that had previously been overlooked. We report statistics from a literature survey of the magnetic properties of Co-based compounds with more than 33 at. % Co. We classify more than 13 000 compounds by structure type, cobalt content, and magnetic ground state. From these data, compounds TaCo 2 Ga, La 6 Co 13 Bi, and Nd 2 Co 3 were identified as potential ferromagnets, and we confirm their ferromagnetic ordering theoretically via first-principles calculations and experimentally via synthesis and characterization measurements. In addition, the analysis is focused on the collection of data trends and discovery of ferromagnetic materials with easy-axis magnetic anisotropy. Both known ferromagnetic materials with unknown magnetic anisotropy, and unstudied compounds were considered. From the subset of known ferromagnets with unknown anisotropy, the compound Co 2 Mg was synthesized, characterized, and determined to have easy-axis magnetic anisotropy at room temperature.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Nonparametric Bayesian Modeling for Automated Database Schema Matching

The problem of merging databases arises in many government and commercial applications. Schema matching, a common first step, identifies equivalent fields between databases. We introduce a schema matching framework that builds nonparametric Bayesian models for each field and compares them by computing the probability that a single model could have generated both fields. Our experiments show that our method is more accurate and faster than the existing instance-based matching algorithms in part because of the use of nonparametric Bayesian models.

Bayesian↗
DOE OSTI2024

Resources, Training, and Education Under the Heliostat Consortium: Industry Gap Analysis and Building a Resource Database

Concentrating solar power is not a widely deployed or known technology area, and the heliostat workforce community in the United States is currently small, with knowledge and expertise not widely available. The resource, training, and education (RTE) topic within the Heliostat Consortium (HelioCon) was established to address this. RTE encompasses resources, practices, and programs to ensure that (1) newcomers to the heliostat development community have an adequate knowledge base and training to conduct R&D efforts, (2) outsiders to the field are provided with resources and opportunities to join the workforce, and (3) the workforce community is a productive, healthy, and fulfilling environment for all workers. In the first year of the project, a roadmap study was conducted, in which the major gaps in RTE were identified by consulting experts in the industry, with the top gap being the lack of public accessibility to concentrating solar-thermal power (CSP) knowledge. Here, to address this, the HelioCon team has been developing a centralized web-based resource database, containing a reference library, educational videos, lists of components suppliers and software/metrology tools, a power tower plant database, and information on existing standards/guidelines.

14 SOLAR ENERGY↗
DOE OSTI2014

SU-E-T-413: Experience-Based VMAT Plan Quality Database

Purpose: To quantify VMAT plan quality using a retrospective study of over 200 clinical treated VMAT plans created using the Eclipse Treatment Planning System to create benchmarks of plan quality for a few categories of treatment sites. Methods: Using a controlled phantom geometry, various dosimetric indices were investigated to quantify dosimetric plan quality as a function of isocenter displacement from center of mass, average path length, number of arcs and PTV proximity to critical structures. Beginning with published dosimetry indices from SRS and SBRT evaluations, UDI (Unified Dosimetry Index) and modified UDI were tested before creating a new factor VMAT-DI. VMAT-DI was developed within boundaries of this project and it includes renormalized factors of conformity index, coverage index, modified gradient index and homogeneity index as well as indices based on routine clinical practice such as absolute dose max index. The plans were then evaluated using the VMAT-DI such that benchmarks for planning could be created. Results: The majority of the plans evaluated could be assigned VMAT-DI values within a range for each treatment site. However, the outliers were results of difficult planning parameters such as very irregular targets, inhomogeneities or difficult to achieve critical structure constraints. To effectively use VMAT-DI for guidance, especially for prediction of the plan quality for body sites new to the practice, VMATDI database needs to be subdivided by target complexity and by body site index/average path length factor. Conclusion: An experienced-based VMAT-DI database can be used to help analyze plans before evaluation by the physician to show that it adheres to the clinical standards of previously treated VMAT plans which will make a guideline for concluding the optimization. The introduction of institution-wide clinical planning protocols, standardizing OAR naming and constraints will make it possible to incorporate a cumulative critical structure dosimetry index such as NTCP.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2014

SU-E-QI-16: Reproducibility of Computed Tomography Quantitative Structural Features Using the FDA Thoracic Phantom Image Database

Purpose: To assess the reproducibility of quantitative structural features using images from the computed tomography thoracic FDA phantom database under different scanning conditions. Methods: Development of quantitative image features to describe lesion shape and size, beyond conventional RECIST measures, is an evolving area of research in need of benchmarking standards. Gavrielides et al. (2010) scanned a FDA-developed thoracic phantom with nodules of various Hounsfield units (HU) values, shapes and sizes close to vascular structures using several scanners and varying scanning conditions/parameters; these images are in the public domain. We tested six structural features, namely, Convexity, Perimeter, Major Axis, Minor Axis, Extent Mean and Eccentricity, to characterize lung nodules. Convexity measures lesion irregularity referenced to a convex surface. Previously, we showed it to have prognostic value in lung adenocarcinoma. The above metrics and RECIST measures were evaluated on three spiculated (8mm/-300HU, 12mm/+30HU and 15mm/+30HU) and two non-spiculated (8mm/+100HU and 10mm/+100HU) nodules (from layout 2) imaged at three different mAs values: 25, 100 and 200 mAs; on a Phillips scanner (16-slice Mx8000-IDT; 3mm slice thickness). The nodules were segmented semi-automatically using a commercial software tool; the same HU range was used for all nodules. Results: Analysis showed convexity having the lowest maximum coefficient of variation (MCV): 1.1% and 0.6% for spiculated and non-spiculated nodules, respectively, much lower compared to RECIST Major and Minor axes whose MCV were 10.1% and 13.4% for spiculated, and 1.9% and 2.3% for non-spiculated nodules, respectively, across the various mAs. MCVs were consistently larger for speculated nodules. In general, the dependence of structural features on mAs (noise) was low. Conclusion: The FDA phantom CT database may be used for benchmarking of structural features for various scanners and scanning conditions; we used only a small fraction of available data. Our feature convexity outperformed other structural features including RECIST measures.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

TU-A-12A-04: Quantitative Texture Features Calculated in Lung Tissue From CT Scans Demonstrate Consistency Between Two Databases From Different Institutions

Purpose: To evaluate the consistency of computed tomography (CT) scan texture features, previously identified as stable in a healthy patient cohort, in esophageal cancer patient CT scans. Methods: 116 patients receiving radiation therapy (median dose: 50.4Gy) for esophageal cancer were retrospectively identified. For each patient, diagnostic-quality pre-therapy (0-183 days) and post-therapy (5-120 days) scans (mean voxel size: 0.8mm×0.8mm×2.5mm) and a treatment planning scan and associated dose map were collected. An average of 501 32x32-pixel ROIs were placed randomly in the lungs of each pre-therapy scan. ROI centers were mapped to corresponding locations in post-therapy and planning scans using the displacement vector field output by demons deformable registration. Only ROIs with mean dose <5Gy were analyzed, as these were expected to contain minimal post-treatment damage. 140 texture features were calculated in pre-therapy and post-therapy scan ROIs and compared using Bland-Altman analysis. For each feature, the mean feature value change and the distance spanned by the 95% limits of agreement were normalized to the mean feature value, yielding normalized range of agreement (nRoA) and normalized bias (nBias). Using Wilcoxon signed rank tests, nRoA and nBias were compared with values computed previously in 27 healthy patient scans (mean voxel size: 0.67mm×0.67mm×1mm) acquired at a different institution. Results: nRoA was significantly (p<0.001) larger in cancer patients than healthy patients. Differences in nBias were not significant (p=0.23). The 20 features identified previously as having nRoA<20% for healthy patients had the lowest nRoA values in the current database, with an average increase of 5.6%. Conclusion: Despite differences in CT scanner type, scan resolution, and patient health status, the same 20 features remained stable (i.e., low variability and bias) in the absence of disease changes for databases from two institutions. Identification of these features is the first step towards quantifying radiation-induced changes between preand post-therapy scans. Supported, in part, by NIH Grant Nos. S10 RR021039, and P30 CA14599, the Virginia and D. K. Ludwig Fund for Cancer Research, Imaging Research Institute, Biological Sciences Division, The University of Chicago, and The Institute for Translational Medicine Pilot Award, The University of Chicago.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-P-10: A Web-Based Radiation Safety Relational Database Module for Regulatory Compliance

Purpose: Maintaining compliance with Radioactive Materials Licenses is inherently a time-consuming task requiring focus and attention to detail. Staff tasked with these responsibilities, such as the Radiation Safety Officer and associated personnel must retain disparate records for eventual placement into one or more annual reports. Entering results and records in a relational database using a web browser as the interface, and storing that data in a cloud-based storage site, removes procedural barriers. The data becomes more adaptable for mining and sharing. Methods: Web-based code was written utilizing the web framework Django, written in Python. Additionally, the application utilizes JavaScript for front-end interaction, SQL, HTML and CSS. Quality assurance code testing is performed in a sequential style, and new code is only added after the successful testing of the previous goals. Separate sections of the module include data entry and analysis for audits, surveys, quality management, and continuous quality improvement. Data elements can be adapted for quarterly and annual reporting, and for immediate notification of user determined alarm settings. Results: Current advances are focusing on user interface issues, and determining the simplest manner by which to teach the user to build query forms. One solution has been to prepare library documents that a user can select or edit in place of creation a new document. Forms are being developed based upon Nuclear Regulatory Commission federal code, and will be expanded to include State Regulations. Conclusion: Establishing a secure website to act as the portal for data entry, storage and manipulation can lead to added efficiencies for a Radiation Safety Program. Access to multiple databases can lead to mining for big data programs, and for determining safety issues before they occur. Overcoming web programming challenges, a category that includes mathematical handling, is providing challenges that are being overcome.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2019

Description of Emission Processes in Molecular Gases Based with the HITRAN Database

Methods for calculating the emission characteristics of a molecular gas in vibrational–rotational transitions involving information collected in the HITRAN database have been discussed. It has been shown that a series of vibrational–rotational transitions induced by the absorption of photons by CO{sub 2} molecules lead to the formation of unstable autoionizing states. Algorithms for calculating the partial absorption coefficients and radiation fluxes from the bulk of the molecular gas have been developed involving the HITRAN database. Advantages and disadvantages of this approach for calculating the emission characteristics of molecular gas layers have been discussed. The results have been demonstrated in application to carbon dioxide and methane in the Earth’s atmosphere.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

The tundra phenology database: more than two decades of tundra phenology responses to climate change

Observations of changes in phenology have provided some of the strongest signals of the effects of climate change on terrestrial ecosystems. The International Tundra Experiment (ITEX), initiated in the early 1990s, established a common protocol to measure plant phenology in tundra study areas across the globe. Today, this valuable collection of phenology measurements depicts the responses of plants at the colder extremes of our planet to experimental and ambient changes in temperature over the past decades. The database contains 150 434 phenology observations of 278 plant species taken at 28 study areas for periods of 1–26 years. Here we describe the full data set to increase the visibility and use of these data in global analyses and to invite phenology data contributions from underrepresented tundra locations. Portions of this tundra phenology database have been used in three recent syntheses, some data sets are expanded, others are from entirely new study areas, and the entirety of these data are now available at the Polar Data Catalogue (https://doi.org/10.21963/13215).

54 ENVIRONMENTAL SCIENCES↗