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At least 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

IMG/VR v4: an expanded database of uncultivated virus genomes within a framework of extensive functional, taxonomic, and ecological metadata

Viruses are widely recognized as critical members of all microbiomes. Metagenomics enables large-scale exploration of the global virosphere, progressively revealing the extensive genomic diversity of viruses on Earth and highlighting the myriad of ways by which viruses impact biological processes. IMG/VR provides access to the largest collection of viral sequences obtained from (meta)genomes, along with functional annotation and rich metadata. A web interface enables users to efficiently browse and search viruses based on genome features and/or sequence similarity. Here, for this work, we present the fourth version of IMG/VR, composed of >15 million virus genomes and genome fragments, a ≈6-fold increase in size compared to the previous version. These clustered into 8.7 million viral operational taxonomic units, including 231 408 with at least one high-quality representative. Viral sequences in IMG/VR are now systematically identified from genomes, metagenomes, and metatranscriptomes using a new detection approach (geNomad), and IMG standard annotation are complemented with genome quality estimation using CheckV, taxonomic classification reflecting the latest taxonomic standards, and microbial host taxonomy prediction. IMG/VR v4 is available at https://img.jgi.doe.gov/vr, and the underlying data are available to download at https://genome.jgi.doe.gov/portal/IMG_VR.

59 BASIC BIOLOGICAL SCIENCES↗
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 OSTI2024

Correction to ‘Twenty-five years of Genomes OnLine Database (GOLD): data updates and new features in v.9’

In the originally published online version of this manuscript, there were two co-authors missing from the author list: Tanja Woyke (https://orcid.org/0000-0002-9485-5637) and Emiley Eloe-Fadrosh (https://orcid.org/0000-0002-8162-1276). The author list should read: ‘Supratim Mukherjee, Dimitri Stamatis, Cindy Tianqing Li, Galina Ovchinnikova, Jon Bertsch, Jagadish Chandrabose Sundaramurthi, Mahathi Kandimalla, Paul A. Nicolopoulos, Alessandro Favognano, Tanja Woyke, Emiley A. Eloe-Fardosh, I-Min A. Chen, Nikos C. Kyrpides and T.B.K. Reddy’. This emendation is outlined only in this correction notice to preserve the version of record.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2024

Correction to ‘Genomes OnLine Database (GOLD) v.8: overview and updates’

In the originally published online version of this manuscript, there were two co-authors missing from the author list: Tanja Woyke (https://orcid.org/0000-0002-9485-5637) and Emiley Eloe-Fadrosh (https://orcid.org/0000-0002-8162-1276). The list should now read: ‘Supratim Mukherjee, Dimitri Stamatis, Jon Bertsch, Galina Ovchinnikova, Jagadish Chandrabose Sundaramurthi, Janey Lee, Mahathi Kandimalla, Tanja Woyke, Emiley A. Eloe-Fardosh, I-Min A. Chen, Nikos C. Kyrpides and T.B.K. Reddy’. The emendation is outlined only in this correction notice to preserve the version of record.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2013

POGO-DB—a database of pairwise-comparisons of genomes and conserved orthologous genes

POGO-DB (http://pogo.ece.drexel.edu/) provides an easy platform for comparative microbial genomics. POGO-DB allows users to compare genomes using pre-computed metrics that were derived from extensive computationally intensive BLAST comparisons of >2000 microbes. These metrics include (i) average protein sequence identity across all orthologs shared by two genomes, (ii) genomic fluidity (a measure of gene content dissimilarity), (iii) number of ‘orthologs’ shared between two genomes, (iv) pairwise identity of the 16S ribosomal RNA genes and (v) pairwise identity of an additional 73 marker genes present in >90% prokaryotes. Users can visualize these metrics against each other in a 2D plot for exploratory analysis of genome similarity and of how different aspects of genome similarity relate to each other. The results of these comparisons are fully downloadable. In addition, users can download raw BLAST results for all or user-selected comparisons. Therefore, we provide users with full flexibility to carry out their own downstream analyses, by creating easy access to data that would normally require heavy computational resources to generate. POGO-DB should prove highly useful for researchers interested in comparative microbiology and benefit the microbiome/metagenomic communities by providing the information needed to select suitable phylogenetic marker genes within particular lineages.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

The MG-RAST Metagenomics Database and Portal in 2015

MG-RAST (http://metagenomics.anl.gov) is an opensubmission data portal for processing, analyzing, sharing and disseminating metagenomic datasets. Currently, the system hosts over 200 000 datasets and is continuously updated. The volume of submissions has increased 4-fold over the past 24 months, now averaging 4 terabasepairs per month. In addition to several new features, we report changes to the analysis workflow and the technologies used to scale the pipeline up to the required throughput levels. Lastly, to show possible uses for the data from MG-RAST, we present several examples integrating data and analyses from MG-RAST into popular third-party analysis tools or sequence alignment tools.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2016

Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center

Here, the Pathosystems Resource Integration Center (PATRIC) is the bacterial Bioinformatics Resource Center. Recent changes to PATRIC include a redesign of the web interface and some new services that provide users with a platform that takes them from raw reads to an integrated analysis experience. The redesigned interface allows researchers direct access to tools and data, and the emphasis has changed to user-created genome-groups, with detailed summaries and views of the data that researchers have selected. Perhaps the biggest change has been the enhanced capability for researchers to analyze their private data and compare it to the available public data. Researchers can assemble their raw sequence reads and annotate the contigs using RASTtk. PATRIC also provides services for RNA-Seq, variation, model reconstruction and differential expression analysis, all delivered through an updated private workspace. Private data can be compared by `virtual integration' to any of PATRIC's public data. The number of genomes available for comparison in PATRIC has expanded to over 80 000, with a special emphasis on genomes with antimicrobial resistance data. PATRIC uses this data to improve both subsystem annotation and k-mer classification, and tags new genomes as having signatures that indicate susceptibility or resistance to specific antibiotics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

The Planteome database: an integrated resource for reference ontologies, plant genomics and phenomics

The Planteome project (http://www.planteome.org) provides a suite of reference and species-specific ontologies for plants and annotations to genes and phenotypes. Ontologies serve as common standards for semantic integration of a large and growing corpus of plant genomics, phenomics and genetics data. The reference ontologies include the Plant Ontology, Plant Trait Ontology and the Plant Experimental Conditions Ontology developed by the Planteome project, along with the Gene Ontology, Chemical Entities of Biological Interest, Phenotype and Attribute Ontology, and others. The project also provides access to species-specific Crop Ontologies developed by various plant breeding and research communities from around the world. We provide integrated data on plant traits, phenotypes, and gene function and expression from 95 plant taxa, annotated with reference ontology terms. The Planteome project is developing a plant gene annotation platform; Planteome Noctua, to facilitate community engagement. All the Planteome ontologies are publicly available and are maintained at the Planteome GitHub site (https://github.com/Planteome) for sharing, tracking revisions and new requests. The annotated data are freely accessible from the ontology browser (http://browser.planteome.org/amigo) and our data repository.

Biochemistry & Molecular Biology↗
DOE OSTI2014

SU-E-T-310: Targeting Safety Improvements Through Analysis of Near-Miss Error Detection Points in An Incident Learning Database

Purpose: Radiation treatment planning involves a complex workflow that can make safety improvement efforts challenging. This study utilizes an incident reporting system to identify detection points of near-miss errors, in order to guide our departmental safety improvement efforts. Previous studies have examined where errors arise, but not where they are detected or their patterns. Methods: 1377 incidents were analyzed from a departmental nearmiss error reporting system from 3/2012–10/2013. All incidents were prospectively reviewed weekly by a multi-disciplinary team, and assigned a near-miss severity score ranging from 0–4 reflecting potential harm (no harm to critical). A 98-step consensus workflow was used to determine origination and detection points of near-miss errors, categorized into 7 major steps (patient assessment/orders, simulation, contouring/treatment planning, pre-treatment plan checks, therapist/on-treatment review, post-treatment checks, and equipment issues). Categories were compared using ANOVA. Results: In the 7-step workflow, 23% of near-miss errors were detected within the same step in the workflow, while an additional 37% were detected by the next step in the workflow, and 23% were detected two steps downstream. Errors detected further from origination were more severe (p<.001; Figure 1). The most common source of near-miss errors was treatment planning/contouring, with 476 near misses (35%). Of those 476, only 72(15%) were found before leaving treatment planning, 213(45%) were found at physics plan checks, and 191(40%) were caught at the therapist pre-treatment chart review or on portal imaging. Errors that passed through physics plan checks and were detected by therapists were more severe than other errors originating in contouring/treatment planning (1.81 vs 1.33, p<0.001). Conclusion: Errors caught by radiation treatment therapists tend to be more severe than errors caught earlier in the workflow, highlighting the importance of safety checks in dosimetry and physics. We are utilizing our findings to improve manual and automated checklists for dosimetry and physics.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

A Database for Comparative Electrochemical Performance of Commercial 18650-Format Lithium-Ion Cells

Lithium-ion batteries are a central technology to our daily lives with widespread use in mobile devices and electric vehicles. These batteries are also beginning to be widely used in electric grid infrastructure support applications which have stringent safety and reliability requirements. Typically, electrochemical performance data is not available for modelers to validate their simulations, mechanisms, and algorithms for lithium-ion battery performance and lifetime. In this paper, we report on the electrochemical performance of commercial 18650 cells at a variety of temperatures and discharge currents. We found that LiFePO 4 is temperature tolerant for discharge currents at or below 10 A whereas LiCoO 2 , LiNi x Co y Al 1-x-y O 2 , and LiNi 0.80 Mn 0.15 Co 0.05 O 2 exhibited optimal electrochemical performance when the temperature is maintained at 15°C. LiNi x Co y Al 1-x-y O 2 showed signs of lithium plating at lower temperatures, evidenced by irreversible capacity loss and emergence of a high-voltage differential capacity peak. Furthermore, all cells need to be monitored for self-heating, as environment temperature and high discharge currents may elicit an unintended abuse condition. Overall, this study shows that lithium-ion batteries are highly application-specific and electrochemical behavior must be well understood for safe and reliable operation. Additionally, data collected in this study is available for anyone to download for further analysis and model validation.

25 ENERGY STORAGE↗
DOE OSTI2022

Translytics: A Novel Approach for Runtime Selection of Database Layout Based on User’s Context

Currently, organizations have to maintain separate systems for transactions and analytics inside the company. Notably, different vendors provide the capabilities for either of these tasks that require specialized hardware or software. Data engineers are required to retrieve data from one source and transform it into another format to obtain the maximum benefit in a minimum time. Organizations strive for a competitive advantage that is achieved by fetching data from their customers and getting insights earliest for timely decision making. Present practices do not permit the view of the latest data for analytics since the first data have to be fetched from the source, transformed, and loaded to other systems to be utilized for analysis by relevant teams. This paper introduces a single system for both transactions and analytics. Our proposed solution would permit companies to seamlessly adapt our solution without the need to shift all of their data to newer systems and allow all the teams. It would grant all the teams to have a view of the latest available data without extra expertise and budget.

Tanvir, Muhammad Makhshif↗