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At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS1991

Task sequence planning in a robot workcell using AND/OR nets

An approach to task sequence planning for a generalized robotic manufacturing or material handling workcell is described. Given the descriptions of the objects in this system and all feasible geometric relationships among these objects, an AND/OR net which describes the relationships of all feasible geometric states and associated feasibility criteria for net transitions is generated. This AND/OR net is mapped into a Petri net which incorporates all feasible sequences of operations. The resulting Petri net is shown to be bounded and have guaranteed properties of liveness, safeness, and reversibility. Sequences are found from the reachability tree of the Petri net. Feasibility criteria for net transitions may be used to generate an extended Petri net representation of lower level command sequences. The resulting Petri net representation may be used for on-line scheduling and control of the system of feasible sequences. A simulation example of the sequences is described.

Cao, Tiehua↗
NASA NTRS1994

Data compression of discrete sequence: A tree based approach using dynamic programming

A dynamic programming based approach for data compression of a ID sequence is presented. The compression of an input sequence of size N to that of a smaller size k is achieved by dividing the input sequence into k subsequences and replacing the subsequences by their respective average values. The partitioning of the input sequence is carried with the intention of reducing the mean squared error in the reconstructed sequence. The complexity involved in finding the partitions which would result in such an optimal compressed sequence is reduced by using the dynamic programming approach, which is presented.

Shivaram, Gurusrasad↗
NASA NTRS2010

Reporting Differences Between Spacecraft Sequence Files

A suite of computer programs, called seq diff suite, reports differences between the products of other computer programs involved in the generation of sequences of commands for spacecraft. These products consist of files of several types: replacement sequence of events (RSOE), DSN keyword file [DKF (wherein DSN signifies Deep Space Network)], spacecraft activities sequence file (SASF), spacecraft sequence file (SSF), and station allocation file (SAF). These products can include line numbers, request identifications, and other pieces of information that are not relevant when generating command sequence products, though these fields can result in the appearance of many changes to the files, particularly when using the UNIX diff command to inspect file differences. The outputs of prior software tools for reporting differences between such products include differences in these non-relevant pieces of information. In contrast, seq diff suite removes the fields containing the irrelevant pieces of information before processing to extract differences, so that only relevant differences are reported. Thus, seq diff suite is especially useful for reporting changes between successive versions of the various products and in particular flagging difference in fields relevant to the sequence command generation and review process.

Khanampompan, Teerapat↗
NASA NTRS2006

Program Synthesizes UML Sequence Diagrams

A computer program called "Rational Sequence" generates Universal Modeling Language (UML) sequence diagrams of a target Java program running on a Java virtual machine (JVM). Rational Sequence thereby performs a reverse engineering function that aids in the design documentation of the target Java program. Whereas previously, the construction of sequence diagrams was a tedious manual process, Rational Sequence generates UML sequence diagrams automatically from the running Java code.

Barry, Matthew R.↗
NASA NTRS2010

[Characterization of Black and Dichothrix Cyanobacteria Based on the 16S Ribosomal RNA Gene Sequence]

My project focuses on characterizing different cyanobacteria in thrombolitic mats found on the island of Highborn Cay, Bahamas. Thrombolites are interesting ecosystems because of the ability of bacteria in these mats to remove carbon dioxide from the atmosphere and mineralize it as calcium carbonate. In the future they may be used as models to develop carbon sequestration technologies, which could be used as part of regenerative life systems in space. These thrombolitic communities are also significant because of their similarities to early communities of life on Earth. I targeted two cyanobacteria in my research, Dichothrix spp. and whatever black is, since they are believed to be important to carbon sequestration in these thrombolitic mats. The goal of my summer research project was to molecularly identify these two cyanobacteria. DNA was isolated from each organism through mat dissections and DNA extractions. I ran Polymerase Chain Reactions (PCR) to amplify the 16S ribosomal RNA (rRNA) gene in each cyanobacteria. This specific gene is found in almost all bacteria and is highly conserved, meaning any changes in the sequence are most likely due to evolution. As a result, the 16S rRNA gene can be used for bacterial identification of different species based on the sequence of their 16S rRNA gene. Since the exact sequence of the Dichothrix gene was unknown, I designed different primers that flanked the gene based on the known sequences from other taxonomically similar cyanobacteria. Once the 16S rRNA gene was amplified, I cloned the gene into specialized Escherichia coli cells and sent the gene products for sequencing. Once the sequence is obtained, it will be added to a genetic database for future reference to and classification of other Dichothrix sp.

Ortega, Maya↗
NASA NTRS2011

MSLICE Sequencing

MSLICE Sequencing is a graphical tool for writing sequences and integrating them into RML files, as well as for producing SCMF files for uplink. When operated in a testbed environment, it also supports uplinking these SCMF files to the testbed via Chill. This software features a free-form textural sequence editor featuring syntax coloring, automatic content assistance (including command and argument completion proposals), complete with types, value ranges, unites, and descriptions from the command dictionary that appear as they are typed. The sequence editor also has a "field mode" that allows tabbing between arguments and displays type/range/units/description for each argument as it is edited. Color-coded error and warning annotations on problematic tokens are included, as well as indications of problems that are not visible in the current scroll range. "Quick Fix" suggestions are made for resolving problems, and all the features afforded by modern source editors are also included such as copy/cut/paste, undo/redo, and a sophisticated find-and-replace system optionally using regular expressions. The software offers a full XML editor for RML files, which features syntax coloring, content assistance and problem annotations as above. There is a form-based, "detail view" that allows structured editing of command arguments and sequence parameters when preferred. The "project view" shows the user s "workspace" as a tree of "resources" (projects, folders, and files) that can subsequently be opened in editors by double-clicking. Files can be added, deleted, dragged-dropped/copied-pasted between folders or projects, and these operations are undoable and redoable. A "problems view" contains a tabular list of all problems in the current workspace. Double-clicking on any row in the table opens an editor for the appropriate sequence, scrolling to the specific line with the problem, and highlighting the problematic characters. From there, one can invoke "quick fix" as described above to resolve the issue. Once resolved, saving the file causes the problem to be removed from the problem view.

Crockett, Thomas M.↗
NASA NTRSDate not supplied

Spaceflight Autonomous Multigenerational Microbial Sequencer in Support of Plant-Growth Systems

The CubeSat platform has proven successful in obtaining meaningful life science information when biological payloads are incorporated. Examples include: 1) the first-ever CubeSat with a biological payload, GeneSat-1, which demonstrated decreased growth rates for flight samples of Escherichia coli in low Earth orbit (Parra et al. 2008); 2) PharmaSat, demonstrated that Saccharomyces cerevisiae in the microgravity environment exhibits a significant level of metabolic activity even at high doses of applied antifungal (Ricco et al. 2011); 3) O/OREOS, which used Bacillus subtilis(bacteria) to demonstrate for the first time that microorganisms can be loaded in a dried, dormant form and then rehydrated and grown in orbit months after launch (Nicholson et al. 2011; Ehrenfreund et al. 2014; 4) the SporeSat payload, which investigated Ceratopteris richardii(fern spores) using lab-on-a-chip devices (BioCDs) and minicentrifuges to produce artificial gravitational forces in ground studies (Park et al. 2017), with demonstration of the BioCD and minicentrifuge in space; 5) EcAMSat, the first CubeSat to be directly deployed from the ISS for an experiment assessing antibiotic resistance of E. coli in the microgravity environment (Padgen et al. 2020); 6) BioSentinel, exposed a culture of yeast to galactic cosmic radiation (GCR) and solar particle events while in heliocentric orbit to measure the rate of double-strand-break repair using DNA-repair-deficient mutants. This effort measures the metabolic parameters of yeast in a deep-space environment compared to Earth ambient conditions using a 3-color LED detection system (Ricco et al. 2020; Padgen et al. 2021). We aim to expand this list to include a Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS). SAMMS will allow for the genome level understanding of changes in growth and metabolic activity for any organism. While microbes are suitable for early studies in our proposed platform because of their small size, small and relatively less-complicated genomes, fast generation times, and relevance to life support systems; multicellular organisms can similarly be evaluated for their genetic response to the spaceflight environment. The Spaceflight Autonomous Multigenerational Microbial Sequencer (SAMMS) will enable autonomous sequencing of biological samples in plant production units, cislunar orbit and on the lunar surface to examine spaceflight effects (ie. radiation, altered gravity, reduced pressures) on plant and microbial genomes.On this team a Kennedy Space Center (KSC) space crop production and water systems microbiologist/molecular biologist works with a Johnson Space Center (JSC) International Space Station (ISS) microbial sequencing expert and an Ames Research Center (ARC) CubeSat Engineering team to convert an automated Oxford Nanopore librarypreparation and sequencing method to a fluidic CubeSat payload system. The Oxford Nanopore MinION sequencing platform has proven successful in the spaceflight environment onboard the ISS (Stahl-Rommel et al. 2021). Further long-duration spaceflight and exposure to high levels of radiation will cause genotypic effects in biological organisms that may affect their function. Monitoring the adaption of a population to the spaceflight environment and any subsequent beneficial mutations will allow for the harnessing of organisms best suited for use in life support systems. This will ensure that the selected life support-essential microorganisms maintain their intended specified function over generations of culturing in the relevant spaceflight environment without becoming hazardous to crew or spacecraft systems.

Aubrie E Orourke↗
NASA NTRS2019

Size and Structure of the Sequence Space of Repeat Proteins

The coding space of protein sequences is shaped by evolutionary constraints set by requirements of function and stability. We show that the coding space of a given protein family— the total number of sequences in that family—can be estimated using models of maximum entropy trained on multiple sequence alignments of naturally occurring amino acid sequences. We analyzed and calculated the size of three abundant repeat proteins families, whose members are large proteins made of many repetitions of conserved portions of *30 amino acids. While amino acid conservation at each position of the alignment explains most of the reduction of diversity relative to completely random sequences, we found that correlations between amino acid usage at different positions significantly impact that diversity. We quantified the impact of different types of correlations, functional and evolutionary, on sequence diversity. Analysis of the detailed structure of the coding space of the families revealed a rugged landscape, with many local energy minima of varying sizes with a hierarchical structure, reminiscent of frustrated energy landscapes of spin glass in physics. This clustered structure indicates a multiplicity of subtypes within each family and suggests new strategies for protein design.

Jacopo Marchi↗
NASA NTRS2018

On the Natural Structure of Amino Acid Patterns in Families of Protein Sequences

All known terrestrial proteins are coded as continuous strings of ≈20 amino acids. The patterns formed by the repetitions of elements in groups of finite sequences describes the natural architectures of protein families. We present a method to search for patterns and groupings of patterns in protein sequences using a mathematically precise definition for “repetition”, an efficient algorithmic implementation and a robust scoring system with no adjustable parameters. We show that the sequence patterns can be well-separated into disjoint classes according to their recurrence in nested structures. The statistics of the occurrences of patterns indicate that short repetitions are sufficient to account for the differences between natural families and randomized groups of sequences by more than 10 standard deviations, while contiguous sequence patterns shorter than 5 residues are effectively random in their occurrences. A small subset of patterns is sufficient to account for a robust ”familiarity” definition between arbitrary sets of sequences.

Pablo Turjanski↗
NASA NTRSDate not supplied

Optimizing Single Nuclei Sequencing of Brain Samples From Space Flown Mice Across Age and Strain

The NASA GeneLab Sample Processing Laboratory offers high-throughput sequencing services to NASA-funded space biology researchers. Space biology studies have specific challenges such as low sample numbers, introducing susceptibility to batch effects from sample handling. These issues are compounded by complex protocols such as single-nuclei isolation and sequencing, which has recently become an attractive methodology for assessing the cellular diversity within spaceflight samples. High quality single-nuclei sequencing requires reproducible protocols to dissociate tissue and generate clean suspension of intact single nuclei. Producing single-nuclei suspension from brain tissue is particularly challenging due to cell type heterogeneity and the myelin sheath that carries over into the nuclei suspension as debris. Current procedures tend to be time consuming and sometimes include steps that can alter gene expression and create cell-type bias. Commercially available nuclei isolation kits, such as the 10X Genomics nuclei isolation kit, offers a streamlined way to process samples for nuclei isolation, thereby minimizing batch effects and enabling reproducibility. In this study, we report on the performance of the 10X Genomics nuclei isolation kit and Chromium Next GEM Single Cell Multiome ATAC + Gene Expression kit to generate sequencing libraries from space-flown mouse brain samples. Single nuclei sequencing was performed on frozen mouse brain tissue from two spaceflight missions, Rodent Research-10 (RR-10) and RR Reference Mission-2 (RRRM-2). RR-10 mice were female B6129SF2/J, euthanized at 18-19 weeks whereas RRRM-2 mice were female C57BL/6NTac, euthanized at 20 or 37 weeks. Sequencing data was processed using standard GeneLab data processing pipelines. We report evaluation of the performance of the 10X Genomics nuclei isolation kit for spaceflight samples from mouse brain, and evaluation of reproducibility across different mouse strains and age groups. We also report preliminary scientific results including cell type inference, cell clustering, and differentially expressed genes and pathways between spaceflight and ground control samples.

RR-10↗
DOE OSTI2014

Solid phase sequencing of biopolymers

This invention relates to methods for detecting and sequencing target nucleic acid sequences, to mass modified nucleic acid probes and arrays of probes useful in these methods, and to kits and systems which contain these probes. Useful methods involve hybridizing the nucleic acids or nucleic acids which represent complementary or homologous sequences of the target to an array of nucleic acid probes. These probes comprise a single-stranded portion, an optional double-stranded portion and a variable sequence within the single-stranded portion. The molecular weights of the hybridized nucleic acids of the set can be determined by mass spectroscopy, and the sequence of the target determined from the molecular weights of the fragments. Probes may be affixed to a solid support such as a hybridization chip to facilitate automated molecular weight analysis and identification of the target sequence.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2015

Pairwise Sequence Alignment Library

Vector extensions, such as SSE, have been part of the x86 CPU since the 1990s, with applications in graphics, signal processing, and scientific applications. Although many algorithms and applications can naturally benefit from automatic vectorization techniques, there are still many that are difficult to vectorize due to their dependence on irregular data structures, dense branch operations, or data dependencies. Sequence alignment, one of the most widely used operations in bioinformatics workflows, has a computational footprint that features complex data dependencies. The trend of widening vector registers adversely affects the state-of-the-art sequence alignment algorithm based on striped data layouts. Therefore, a novel SIMD implementation of a parallel scan-based sequence alignment algorithm that can better exploit wider SIMD units was implemented as part of the Parallel Sequence Alignment Library (parasail). Parasail features: Reference implementations of all known vectorized sequence alignment approaches. Implementations of Smith Waterman (SW), semi-global (SG), and Needleman Wunsch (NW) sequence alignment algorithms. Implementations across all modern CPU instruction sets including AVX2 and KNC. Language interfaces for C/C++ and Python.

Jeff Daily, PNNL↗
DOE OSTI2018

Method for instruction sequence execution analysis and visualization

Various technologies pertaining to computer-executable instruction sequence forensics are described herein. In a general embodiment, an application development framework supports a function library that includes a plurality of recording functions. Calls to these functions are inserted into source code or bytecode of the computer-executable instruction sequence. The source code is then compiled, resulting in formation of instrumented machine code of the computer-executable instruction sequence. Alternately, the runtime environment interprets instrumented bytecode for the instruction sequence. A processor executes the machine code, and the called functions cause the processor to generate forensic data pertaining to portions of the computer-executable instruction sequence that correspond to locations in the source code where the calls were inserted. An execution instance of the computer-executable instruction sequence is visualized based upon the forensic data.

Sundermier, Amy↗
DOE OSTI2019

Analysis of Transcriptome and Epitranscriptome in Plants Using PacBio Iso-Seq and Nanopore-Based Direct RNA Sequencing

Nanopore sequencing from Oxford Nanopore Technologies (ONT) and Pacific BioSciences (PacBio) single-molecule real-time (SMRT) long-read isoform sequencing (Iso-Seq) are revolutionizing the way transcriptomes are analyzed. These methods offer many advantages over most widely used high-throughput short-read RNA sequencing (RNA-Seq) approaches and allow a comprehensive analysis of transcriptomes in identifying full-length splice isoforms and several other post-transcriptional events. In addition, direct RNA-Seq provides valuable information about RNA modifications, which are lost during the PCR amplification step in other methods. Here, we present a comprehensive summary of important applications of these technologies in plants, including identification of complex alternative splicing (AS), full-length splice variants, fusion transcripts, and alternative polyadenylation (APA) events. Furthermore, we discuss the impact of the newly developed nanopore direct RNA-Seq in advancing epitranscriptome research in plants. Additionally, we summarize computational tools for identifying and quantifying full-length isoforms and other co/post-transcriptional events and discussed some of the limitations with these methods. Sequencing of transcriptomes using these new single-molecule long-read methods will unravel many aspects of transcriptome complexity in unprecedented ways as compared to previous short-read sequencing approaches. Analysis of plant transcriptomes with these new powerful methods that require minimum sample processing is likely to become the norm and is expected to uncover novel co/post-transcriptional gene regulatory mechanisms that control biological outcomes during plant development and in response to various stresses.

alternative polyadenylation↗
NASA NTRS1995

Statistical properties of DNA sequences

We review evidence supporting the idea that the DNA sequence in genes containing non-coding regions is correlated, and that the correlation is remarkably long range--indeed, nucleotides thousands of base pairs distant are correlated. We do not find such a long-range correlation in the coding regions of the gene. We resolve the problem of the "non-stationarity" feature of the sequence of base pairs by applying a new algorithm called detrended fluctuation analysis (DFA). We address the claim of Voss that there is no difference in the statistical properties of coding and non-coding regions of DNA by systematically applying the DFA algorithm, as well as standard FFT analysis, to every DNA sequence (33301 coding and 29453 non-coding) in the entire GenBank database. Finally, we describe briefly some recent work showing that the non-coding sequences have certain statistical features in common with natural and artificial languages. Specifically, we adapt to DNA the Zipf approach to analyzing linguistic texts. These statistical properties of non-coding sequences support the possibility that non-coding regions of DNA may carry biological information.

Non-NASA Center↗
NASA NTRS1995

Systematic analysis of coding and noncoding DNA sequences using methods of statistical linguistics

We compare the statistical properties of coding and noncoding regions in eukaryotic and viral DNA sequences by adapting two tests developed for the analysis of natural languages and symbolic sequences. The data set comprises all 30 sequences of length above 50 000 base pairs in GenBank Release No. 81.0, as well as the recently published sequences of C. elegans chromosome III (2.2 Mbp) and yeast chromosome XI (661 Kbp). We find that for the three chromosomes we studied the statistical properties of noncoding regions appear to be closer to those observed in natural languages than those of coding regions. In particular, (i) a n-tuple Zipf analysis of noncoding regions reveals a regime close to power-law behavior while the coding regions show logarithmic behavior over a wide interval, while (ii) an n-gram entropy measurement shows that the noncoding regions have a lower n-gram entropy (and hence a larger "n-gram redundancy") than the coding regions. In contrast to the three chromosomes, we find that for vertebrates such as primates and rodents and for viral DNA, the difference between the statistical properties of coding and noncoding regions is not pronounced and therefore the results of the analyses of the investigated sequences are less conclusive. After noting the intrinsic limitations of the n-gram redundancy analysis, we also briefly discuss the failure of the zeroth- and first-order Markovian models or simple nucleotide repeats to account fully for these "linguistic" features of DNA. Finally, we emphasize that our results by no means prove the existence of a "language" in noncoding DNA.

NASA Discipline Number 14-10↗
NASA NTRS1995

Long-range correlation properties of coding and noncoding DNA sequences: GenBank analysis

An open question in computational molecular biology is whether long-range correlations are present in both coding and noncoding DNA or only in the latter. To answer this question, we consider all 33301 coding and all 29453 noncoding eukaryotic sequences--each of length larger than 512 base pairs (bp)--in the present release of the GenBank to dtermine whether there is any statistically significant distinction in their long-range correlation properties. Standard fast Fourier transform (FFT) analysis indicates that coding sequences have practically no correlations in the range from 10 bp to 100 bp (spectral exponent beta=0.00 +/- 0.04, where the uncertainty is two standard deviations). In contrast, for noncoding sequences, the average value of the spectral exponent beta is positive (0.16 +/- 0.05) which unambiguously shows the presence of long-range correlations. We also separately analyze the 874 coding and the 1157 noncoding sequences that have more than 4096 bp and find a larger region of power-law behavior. We calculate the probability that these two data sets (coding and noncoding) were drawn from the same distribution and we find that it is less than 10(-10). We obtain independent confirmation of these findings using the method of detrended fluctuation analysis (DFA), which is designed to treat sequences with statistical heterogeneity, such as DNA's known mosaic structure ("patchiness") arising from the nonstationarity of nucleotide concentration. The near-perfect agreement between the two independent analysis methods, FFT and DFA, increases the confidence in the reliability of our conclusion.

Non-NASA Center↗
DOE OSTI2019

Counting Kmers for Biological Sequences at Large Scale

Counting the abundance of all the distinct kmers in biological sequence data is a fundamental step in bioinformatics. These applications include de novo genome assembly, error correction, etc. With the development of sequencing technology, the sequence data in a single project can reach Petabyte-scale or Terabyte-scale nucleotides. Counting demand for the abundance of these sequencing data is beyond the memory and computing capacity of single computing node, and how to process it efficiently is a challenge on a high-performance computing cluster. As such, we propose SWAPCounter, a highly scalable distributed approach for kmer counting. This approach is embedded with an MPI streaming I/O module for loading huge data set at high speed, and a counting bloom filter module for both memory and communication efficiency. By overlapping all the counting steps, SWAPCounter achieves high scalability with high parallel efficiency. In this work, the experimental results indicate that SWAPCounter has competitive performance with two other tools on shared memory environment, KMC 2 , and MSPKmerCounter. Moreover, SWAPCounter also shows the highest scalability under strong scaling experiments. In our experiment on Cetus supercomputer, SWAPCounter scales to 32,768 cores with 79% parallel efficiency (using 2048 cores as baseline) when processing 4 TB sequence data of 1000 Genomes. The source code of SWAPCounter is publicly available at https://github.com/mengjintao/SWAPCounter.

59 BASIC BIOLOGICAL SCIENCES↗