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At least 1,423 records · Page 79

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Efficient DNA sequence compression with neural networks

Abstract Background The increasing production of genomic data has led to an intensified need for models that can cope efficiently with the lossless compression of DNA sequences. Important applications include long-term storage and compression-based data analysis. In the literature, only a few recent articles propose the use of neural networks for DNA sequence compression. However, they fall short when compared with specific DNA compression tools, such as GeCo2. This limitation is due to the absence of models specifically designed for DNA sequences. In this work, we combine the power of neural networks with specific DNA models. For this purpose, we created GeCo3, a new genomic sequence compressor that uses neural networks for mixing multiple context and substitution-tolerant context models. Findings We benchmark GeCo3 as a reference-free DNA compressor in 5 datasets, including a balanced and comprehensive dataset of DNA sequences, the Y-chromosome and human mitogenome, 2 compilations of archaeal and virus genomes, 4 whole genomes, and 2 collections of FASTQ data of a human virome and ancient DNA. GeCo3 achieves a solid improvement in compression over the previous version (GeCo2) of $2.4\%$, $7.1\%$, $6.1\%$, $5.8\%$, and $6.0\%$, respectively. To test its performance as a reference-based DNA compressor, we benchmark GeCo3 in 4 datasets constituted by the pairwise compression of the chromosomes of the genomes of several primates. GeCo3 improves the compression in $12.4\%$, $11.7\%$, $10.8\%$, and $10.1\%$ over the state of the art. The cost of this compression improvement is some additional computational time (1.7–3 times slower than GeCo2). The RAM use is constant, and the tool scales efficiently, independently of the sequence size. Overall, these values outperform the state of the art. Conclusions GeCo3 is a genomic sequence compressor with a neural network mixing approach that provides additional gains over top specific genomic compressors. The proposed mixing method is portable, requiring only the probabilities of the models as inputs, providing easy adaptation to other data compressors or compression-based data analysis tools. GeCo3 is released under GPLv3 and is available for free download at https://github.com/cobilab/geco3.

Silva, Milton↗

NASA NTRS1992

Newly identified main-sequence A stars with circumstellar dust

The IRAS Faint Source Survey data base and the ADDSCAN/SCANPI software are used to search for systems with circumstellar dust in two samples: all of the 62 A stars in Woolley's catalog, which lie near the main sequence and are typically within 25 pc of the sun, and all A stars in the Bright Star Catalogue with mV in the range 4-5 and v sin i not less than 100 km/s. In the first sample, 11 nearby A stars having (12)-(25) and (25)-(60) colors consistent with circumstellar dust are found. The analysis of the second sample demonstrates that the use of the FSS data base increases the likelihood of identifying A stars with circumstellar dust fainter than mV = 4. Three more new dusty systems are found in this sample. Beta Pictoris (A5 IV-V) is the only star within 25 pc of the sun that displays IR colors indicative of both warm and cool dust. It is inferred from the absence of cool dust in the vast majority of the systems that the dust disks of these stars are much less extended than that seen around Beta Pictoris.

Cheng, K.-P.↗

NASA NTRS2015

Systems and Methods for Automated Vessel Navigation Using Sea State Prediction

Systems and methods for sea state prediction and autonomous navigation in accordance with embodiments of the invention are disclosed. One embodiment of the invention includes a method of predicting a future sea state including generating a sequence of at least two 3D images of a sea surface using at least two image sensors, detecting peaks and troughs in the 3D images using a processor, identifying at least one wavefront in each 3D image based upon the detected peaks and troughs using the processor, characterizing at least one propagating wave based upon the propagation of wavefronts detected in the sequence of 3D images using the processor, and predicting a future sea state using at least one propagating wave characterizing the propagation of wavefronts in the sequence of 3D images using the processor. Another embodiment includes a method of autonomous vessel navigation based upon a predicted sea state and target location.

Huntsberger, Terrance L.↗

NASA NTRS2017

Systems and Methods for Automated Vessel Navigation Using Sea State Prediction

Huntsberger, Terrance L.↗

DOE OSTI2015

Towards Batched Linear Solvers on Accelerated Hardware Platforms

As hardware evolves, an increasingly effective approach to develop energy efficient, high-performance solvers, is to design them to work on many small and independent problems. Indeed, many applications already need this functionality, especially for GPUs, which are known to be currently about four to five times more energy efficient than multicore CPUs for every floating-point operation. In this paper, we describe the development of the main one-sided factorizations: LU, QR, and Cholesky; that are needed for a set of small dense matrices to work in parallel. We refer to such algorithms as batched factorizations. Our approach is based on representing the algorithms as a sequence of batched BLAS routines for GPU-contained execution. Note that this is similar in functionality to the LAPACK and the hybrid MAGMA algorithms for large-matrix factorizations. But it is different from a straightforward approach, whereby each of GPU's symmetric multiprocessors factorizes a single problem at a time. We illustrate how our performance analysis together with the profiling and tracing tools guided the development of batched factorizations to achieve up to 2-fold speedup and 3-fold better energy efficiency compared to our highly optimized batched CPU implementations based on the MKL library on a two-sockets, Intel Sandy Bridge server. Compared to a batched LU factorization featured in the NVIDIA's CUBLAS library for GPUs, we achieves up to 2.5-fold speedup on the K40 GPU.

Haidar, Azzam↗

DOE OSTI2018

Alignment-free genome comparison enables accurate geographic sourcing of white oak DNA

Background: The application of genomic data and bioinformatics for the identification of restricted or illegally-sourced natural products is urgently needed. The taxonomic identity and geographic provenance of raw and processed materials have implications in sustainable-use commercial practices, and relevance to the enforcement of laws that regulate or restrict illegally harvested materials, such as timber. Improvements in genomics make it possible to capture and sequence partial-to-complete genomes from challenging tissues, such as wood and wood products. Results: In this paper, we report the success of an alignment-free genome comparison method, d 2; that differentiates different geographic sources of white oak (Quercus) species with a high level of accuracy with very small amount of genomic data. The method is robust to sequencing errors, different sequencing laboratories and sequencing platforms. Conclusions: This method offers an approach based on genome-scale data, rather than panels of pre-selected markers for specific taxa. The method provides a generalizable platform for the identification and sourcing of materials using a unified next generation sequencing and analysis framework.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

High throughput, accurate gene annotation through AI and HPC-enabled structural analysis

With the advances in next generation sequencing technologies, the number of sequenced genomes is growing exponentially, resulting in a technology bottleneck for the translation of sequence information into usable hypotheses about the function of each gene. We have proposed leveraging our leadership high-performance computing (HPC) resources to help break this annotation bottleneck. Here we design an HPC-based framework to infer gene function from gene sequence by incorporating information about protein structure and interactions predicted by deep learning approaches. Accurate functional prediction and gene annotation using computational methods will facilitate breakthroughs in the genomic sciences essential to understanding and harnessing life processes in bacteria, fungi and plants. The development and applications of the state-of-the-art deep neural networks to protein structural modeling, interaction prediction, sequence comparison, and quality assessment of protein structural models will be made possible by leadership computational resources. These HPC-enabled bioinformatics and molecular modeling tools will provide powerful insights into molecular functions of genes.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

Isolation and characterization of a virus infecting the freshwater algae Chrysochromulina parva

Water samples from Lake Ontario, Canada were tested for lytic activity against the freshwater haptophyte algae Chrysochromulina parva. A filterable lytic agent was isolated and identified as a virus via transmission electron microscopy and molecular methods. The virus, CpV-BQ1, is icosahedral, ca. 145 nm in diameter, assembled within the cytoplasm, and has a genome size of ca. 485 kb. Sequences obtained through PCR-amplification of DNA polymerase (polB) genes clustered among sequences from the family Phycodnaviridae, whereas major capsid protein (MCP) sequences clustered among sequences from either the Phycodnaviridae or Mimiviridae. Based on quantitative molecular assays, C. parva's abundance in Lake Ontario was relatively stable, yet CpV-BQ1's abundance was variable suggesting complex virus-host dynamics. This study demonstrates that CpV-BQ1 is a member of the proposed order Megavirales with characteristics of both phycodnaviruses and mimiviruses indicating that, in addition to its complex ecological dynamics, it also has a complex evolutionary history. - Highlights: • A virus infecting the algae C. parva was isolated from Lake Ontario. • Virus characteristics demonstrated that this novel virus is an NCLDV. • The virus's polB sequence suggests taxonomic affiliation with the Phycodnaviridae. • The virus's capsid protein sequences also suggest Mimiviridae ancestry. • Surveys of host and virus natural abundances revealed complex host–virus dynamics.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2012

A UNIFIED EMPIRICAL MODEL FOR INFRARED GALAXY COUNTS BASED ON THE OBSERVED PHYSICAL EVOLUTION OF DISTANT GALAXIES

We reproduce the mid-infrared to radio galaxy counts with a new empirical model based on our current understanding of the evolution of main-sequence (MS) and starburst (SB) galaxies. We rely on a simple spectral energy distribution (SED) library based on Herschel observations: a single SED for the MS and another one for SB, getting warmer with redshift. Our model is able to reproduce recent measurements of galaxy counts performed with Herschel, including counts per redshift slice. This agreement demonstrates the power of our 2-Star-Formation Modes (2SFM) decomposition in describing the statistical properties of infrared sources and their evolution with cosmic time. We discuss the relative contribution of MS and SB galaxies to the number counts at various wavelengths and flux densities. We also show that MS galaxies are responsible for a bump in the 1.4 GHz radio counts around 50 {mu}Jy. Material of the model (predictions, SED library, mock catalogs, etc.) is available online.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2019

Similarities and differences between variants called with human reference genome HG19 or HG38

Reference genome selection is a prerequisite for successful analysis of next generation sequencing (NGS) data. Current practice employs one of the two most recent human reference genome versions: HG19 or HG38. To date, the impact of genome version on SNV identification has not been rigorously assessed. We conducted analysis comparing the SNVs identified based on HG19 vs HG38, leveraging whole genome sequencing (WGS) data from the genome-in-a-bottle (GIAB) project. First, SNVs were called using 26 different bioinformatics pipelines with either HG19 or HG38. Next, two tools were used to convert the called SNVs between HG19 and HG38. Lastly we calculated conversion rates, analyzed discordant rates between SNVs called with HG19 or HG38, and characterized the discordant SNVs. The conversion rates from HG38 to HG19 (average 95%) were lower than the conversion rates from HG19 to HG38 (average 99%). The conversion rates varied slightly among the various calling pipelines. Around 1.5% SNVs were discordantly converted between HG19 or HG38. The conversions from HG38 to HG19 had more SNVs which failed conversion and more discordant SNVs than the opposite conversion (HG19 to HG38). Most of the discordant SNVs had low read depth, were low confidence SNVs as defined by GIAB, and/or were predominated by G/C alleles (52% observed versus 42% expected). A significant number of SNVs could not be converted between HG19 and HG38. Based on careful review of our comparisons, we recommend HG38 (the newer version) for NGS SNV analysis. To summarize, our findings suggest caution when translating identified SNVs between different versions of the human reference genome.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

A new primer set for Clade I nosZ that recovers genes from a broader range of taxa

Denitrification is an important global N cycle process. The gene encoding NosZ that converts nitrous oxide (N 2 O) to N 2 has been widely used as a biomarker to study denitrifying communities. However, conventional PCR primers target a limited range of the genetically diverse Clade I nosZ, and the amplicons are too long for sequencing on current NGS platforms. To address these issues, here we developed a new PCR primer set that amplifies a 355-bp region of Clade I nosZ and captures broader taxonomic coverage than conventional primers in in silico tests. When compared with the widely used nosZF_nosZR_Rich_2003 set using the same soil samples and the same sequencing depth, the new set retrieved genes from four times more unique species, with consistently higher general diversity-based metrics. The new primer set performed well with different sequencing platforms (Ion Torrent and Illumina), and among a wide variety of soils from polar to tropical, desert to agricultural, and surface to a very low biomass subsoil, with significant differences in denitrifying community diversity and composition. This new primer set for Clade I together with the primers recently reported for Clade II by Chee-Sanford et al. provides a more comprehensive assessment of denitrifier gene hosts, their ecological patterns, and the degree of novelty in retrieved gene sequences.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2014

DMINDA: an integrated web server for DNA motif identification and analyses

DMINDA (DNA motif identification and analyses) is an integrated web server for DNA motif identification and analyses, which is accessible at http: //csbl.bmb.uga.edu/DMINDA/. This web site is freely available to all users and there is no login requirement. This server provides a suite of cis-regulatory motif analysis functions on DNA sequences, which are important to elucidation of the mechanisms of transcriptional regulation: (i) de novo motif finding for a given set of promoter sequences along with statistical scores for the predicted motifs derived based on information extracted from a control set, (ii) scanning motif instances of a query motif in provided genomic sequences, (iii) motif comparison and clustering of identified motifs, and (iv) co-occurrence analyses of query motifs in given promoter sequences. The server is powered by a backend computer cluster with over 150 computing nodes, and is particularly useful for motif prediction and analyses in prokaryotic genomes. We believe that DMINDA, as a new and comprehensive web server for cis-regulatory motif finding and analyses, will benefit the genomic research community in general and prokaryotic genome researchers in particular.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Structure of the divergent human astrovirus MLB capsid spike

Despite their worldwide prevalence and association with human disease, the molecular bases of human astrovirus (HAstV) infection and evolution remain poorly characterized. Here, we report the structure of the capsid protein spike of the divergent HAstV MLB clade (HAstV MLB). While the structure shares a similar folding topology with that of classical-clade HAstV spikes, it is otherwise strikingly different. We find no evidence of a conserved receptor-binding site between the MLB and classical HAstV spikes, suggesting that MLB and classical HAstVs utilize different receptors for host-cell attachment. We provide evidence for this hypothesis using a novel HAstV infection competition assay. Comparisons of the HAstV MLB spike structure with structures predicted from its sequence reveal poor matches, but template-based predictions were surprisingly accurate relative to machine-learning-based predictions. Our data provide a foundation for understanding the mechanisms of infection by diverse HAstVs and can support structure determination in similarly unstudied systems.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

The crystal structure of yeast mitochondrial ThrRS in complex with the canonical threonine tRNA

In mitochondria of Saccharomyces cerevisiae, a single aminoacyl-tRNA synthetase (aaRS), MST1, aminoacylates two isoacceptor tRNAs, tRNA 1 Thr and tRNA 2 Thr , that harbor anticodon loops of different size and sequence. As a result of this promiscuity, reassignment of the CUN codon box from leucine to threonine is facilitated. However, the mechanism by which a single aaRS binds distinct anticodon loops with high specificity is not well understood. Herein, we present the crystal structure of MST1 in complex with the canonical tRNA 2 Thr and non-hydrolyzable analog of threonyl adenylate. Our structure reveals that the dimeric arrangement of MST1 is essential for binding the 5'-phosphate, the second base pair of the acceptor stem, the first two base pairs of the anticodon stem and the first nucleotide of the variable arm. Further, in contrast to the bacterial ortholog that ‘reads’ the entire anticodon sequence, MST1 recognizes bases in the second and third position and the nucleotide upstream of the anticodon sequence. We speculate that a flexible loop linking strands β4 and β5 may be allosteric regulator that establishes cross-subunit communication between the aminoacylation and tRNA-binding sites. We also propose that structural features of the anticodon-binding domain in MST1 permit binding of the enlarged anticodon loop of tRNA 1 Thr .

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Machine learning guided selection of broad-spectrum epitope-specific functional antibodies for "Disease X"

Our project established and demonstrated a transfer learning framework that enables prediction of antibody–antigen interactions across related viruses. The approach focused on three major activities: 1. Conserved region and epitope identification – We compared viral protein structures and sequences to identify shared receptor-binding domains and neutralizing epitope regions across variants and related viruses. These conserved features formed the foundation for discovering broadly functional antibodies. 2. Machine learning model development – We built neural network–based models that integrate epitope features with antibody sequence information. Instead of relying solely on structural or physical properties, the models learned transferable patterns that describe antibody binding potential across different viral families. 3. Transfer learning and validation – Using SARS-CoV-2 and Ebola as source systems, we successfully transferred learned epitope features to predict antibody interactions for SARS CoV-1 and Marburg virus. Iterative cycles of dataset generation, retraining, and evaluation improved generalization and predictive power, ensuring the framework can adapt to new threats.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2021

Cross-reactive immunogenicity of group A streptococcal vaccines designed using a recurrent neural network to identify conserved M protein linear epitopes

The M protein of group A streptococci (Strep A) is a major virulence determinant and protective antigen. The N-terminal sequence of the protein defines the more than 200 M types of Strep A and also contains epitopes that elicit opsonic antibodies, some of which cross-react with heterologous M types. Current efforts to develop broadly protective M protein-based vaccines are directed at identifying potential cross-protective epitopes located in the N-terminal regions of cluster-related M proteins for use as vaccine antigens. In this study, we have used a comprehensive approach using the recurrent neural network ABCpred and IEDB epitope conservancy analysis tools to predict 16 residue linear B-cell epitopes from 117 clinically relevant M types of Strep A (~88% of global Strep A infections). Furthermore, to examine the immunogenicity of these epitope-based vaccines, nine peptides that together shared ≥60% sequence identity with 37 heterologous M proteins were incorporated into two recombinant hybrid protein vaccines, in which the epitopes were repeated 2 or 3 times, respectively. The combined immune responses of immunized rabbits showed that the vaccines elicited significant levels of antibodies against all nine vaccine epitopes present in homologous N-terminal 1–50 amino acid synthetic M peptides, as well as cross-reactive antibodies against 16 of 37 heterologous M peptides predicted to contain similar epitopes. The epitope-specificity of the cross-reactive antibodies was confirmed by ELISA inhibition assays and functional opsonic activity was assayed in HL-60-based bactericidal assays. The results provide important information for the future design of broadly protective M protein-based Strep A vaccines.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Edge Bioinformatics

Edge Bioinformatics is a developmental bioinformatics and data management platform which seeks to supply laboratories with bioinformatics pipelines for analyzing data associated with common samples case goals. Edge Bioinformatics enables sequencing as a solution and forward-deployed situations where human-resources, space, bandwidth, and time are limited. The Edge bioinformatics pipeline was designed based on following USE CASES and specific to illumina sequencing reads. 1. Assay performance adjudication (PCR): Analysis of an existing PCR assay in a genomic context, and automated design of a new assay to resolve conflicting results; 2. Clinical presentation with extreme symptoms: Characterization of a known pathogen or co-infection with a. Novel emerging disease outbreak or b. Environmental surveillance

Lo, Chien-Chi↗

DOE OSTI2015

Edge Bioinformatics

Lo, Chien-Chi↗