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At least 361 records · Page 20

On the Impact of Widening Vector Registers on Sequence Alignment

Vector extensions, such as SSE, have been part of the x86 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. In this paper, we demonstrate that the trend of widening vector registers adversely affects the state-of-the-art sequence alignment algorithm based on striped data layouts. We present a practically efficient SIMD implementation of a parallel scan based sequence alignment algorithm that can better exploit wider SIMD units. We conduct comprehensive workload and use case analyses to characterize the relative behavior of the striped and scan approaches and identify the best choice of algorithm based on input length and SIMD width.

Needleman-Wunsch↗

A global view of structure–function relationships in the tautomerase superfamily

The tautomerase superfamily (TSF) consists of more than 11,000 nonredundant sequences present throughout the biosphere. Characterized members have attracted much attention because of the unusual and key catalytic role of an N-terminal proline. These few characterized members catalyze a diverse range of chemical reactions, but the full scale of their chemical capabilities and biological functions remains unknown. To gain new insight into TSF structure–function relationships, we performed a global analysis of similarities across the entire superfamily and computed a sequence similarity network to guide classification into distinct subgroups. Our results indicate that TSF members are found in all domains of life, with most being present in bacteria. The eukaryotic members of the cis-3-chloroacrylic acid dehalogenase subgroup are limited to fungal species, whereas the macrophage migration inhibitory factor subgroup has wide eukaryotic representation (including mammals). Unexpectedly, we found that 346 TSF sequences lack Pro-1, of which 85% are present in the malonate semialdehyde decarboxylase subgroup. The computed network also enabled the identification of similarity paths, namely sequences that link functionally diverse subgroups and exhibit transitional structural features that may help explain reaction divergence. A structure-guided comparison of these linker proteins identified conserved transitions between them, and kinetic analysis paralleled these observations. Phylogenetic reconstruction of the linker set was consistent with these findings. Our results also suggest that contemporary TSF members may have evolved from a short 4-oxalocrotonate tautomerase–like ancestor followed by gene duplication and fusion. Our new linker-guided strategy can be used to enrich the discovery of sequence/structure/function transitions in other enzyme superfamilies.

Biochemistry & Molecular Biology↗

Modeling sequential context effects in diagnostic interpretation of screening mammograms

Prior research has shown that physicians’ medical decisions can be influenced by sequential context, particularly in cases where successive stimuli exhibit similar characteristics when analyzing medical images. This type of systematic error is known to psychophysicists as sequential context effect as it indicates that judgments are influenced by features of and decisions about the preceding case in the sequence of examined cases, rather than being based solely on the peculiarities unique to the present case. We determine if radiologists experience some form of context bias, using screening mammography as the use case. To this end, we explore correlations between previous perceptual behavior and diagnostic decisions and current decisions. We hypothesize that a radiologist’s visual search pattern and diagnostic decisions in previous cases are predictive of the radiologist’s current diagnostic decisions. To test our hypothesis, we tasked 10 radiologists of varied experience to conduct blind reviews of 100 four-view screening mammograms. Eye-tracking data and diagnostic decisions were collected from each radiologist under conditions mimicking clinical practice. Perceptual behavior was quantified using the fractal dimension of gaze scanpath, which was computed using the Minkowski–Bouligand box-counting method. To test the effect of previous behavior and decisions, we conducted a multifactor fixed-effects ANOVA. Further, to examine the predictive value of previous perceptual behavior and decisions, we trained and evaluated a predictive model for radiologists’ current diagnostic decisions. ANOVA tests showed that previous visual behavior, characterized by fractal analysis, previous diagnostic decisions, and image characteristics of previous cases are significant predictors of current diagnostic decisions. Additionally, predictive modeling of diagnostic decisions showed an overall improvement in prediction error when the model is trained on additional information about previous perceptual behavior and diagnostic decisions.

60 APPLIED LIFE SCIENCES↗

Predicting Antimicrobial Resistance Using Partial Genome Alignments

Antimicrobial resistance (AMR) is an important global health threat that impacts millions of people worldwide each year. Developing methods that can detect and predict AMR phenotypes can help to mitigate the spread of AMR by informing clinical decision making and appropriate mitigation strategies. Many bioinformatic methods have been developed for predicting AMR phenotypes from whole-genome sequences and AMR genes, but recent studies have indicated that predictions can be made from incomplete genome sequence data. In order to more systematically understand this, we built random forest-based machine learning classifiers for predicting susceptible and resistant phenotypes for Klebsiella pneumoniae (1,640 strains), Mycobacterium tuberculosis (2,497 strains), and Salmonella enterica (1,981 strains). We started by building models from alignments that were based on a reference chromosome for each species. We then subsampled each chromosomal alignment and built models for the resulting subalignments, finding that very small regions, representing approximately 0.1 to 0.2% of the chromosome, are predictive. In K. pneumoniae, M. tuberculosis, and S. enterica, the subalignments are able to predict multiple AMR phenotypes with at least 70% accuracy, even though most do not encode an AMR-related function. We used these models to identify regions of the chromosome with high and low predictive signals. Finally, subalignments that retain high accuracy across larger phylogenetic distances were examined in greater detail, revealing genes and intergenic regions with potential links to AMR, virulence, transport, and survival under stress conditions. IMPORTANCE Antimicrobial resistance causes thousands of deaths annually worldwide. Understanding the regions of the genome that are involved in antimicrobial resistance is important for developing mitigation strategies and preventing transmission. Machine learning models are capable of predicting antimicrobial resistance phenotypes from bacterial genome sequence data by identifying resistance genes, mutations, and other correlated features. They are also capable of implicating regions of the genome that have not been previously characterized as being involved in resistance. In this study, we generated global chromosomal alignments for Klebsiella pneumoniae, Mycobacterium tuberculosis, and Salmonella enterica and systematically searched them for small conserved regions of the genome that enable the prediction of antimicrobial resistance phenotypes. In addition to known antimicrobial resistance genes, this analysis identified genes involved in virulence and transport functions, as well as many genes with no previous implication in antimicrobial resistance.

59 BASIC BIOLOGICAL SCIENCES↗

Biological Parts Search Portal (BioParts) v1.0.0

BioParts is a web based search portal for biological parts available in the public domain. It combines the ease and convenience of modern web search engines with the capabilities of bioinformatics search tools such as BLAST. This portal, available at bioparts.org, allows anyone to search for publicly accessible biological part information (e.g., NCBI, iGEM, SynBioHub, Addgene), including parts publicly accessible through ICE Registries. Additionally, the portal offers a REST API that enables third-party applications and tools to access the portal's functionality programmatically. While there are several standalone biological part repositories, there doesn't exist an application that indexes these publicly available parts and enables features such as keyword and BLAST searches along with automatic sequence annotation.

Plahar, Hector↗

Activation of polycystin-1 signaling by binding of stalk-derived peptide agonists

Polycystin-1 (PC1) is the protein product of thePKD1gene whose mutation causes autosomal dominant Polycystic Kidney Disease (ADPKD). PC1 is an atypical G protein-coupled receptor (GPCR) with an autocatalytic GAIN domain that cleaves PC1 into extracellular N-terminal and membrane-embedded C-terminal (CTF) fragments. Recently, activation of PC1 CTF signaling was shown to be regulated by a stalk tethered agonist (TA), resembling the mechanism observed for adhesion GPCRs. Here, synthetic peptides of the first 9- (p9), 17- (p17), and 21-residues (p21) of the PC1 stalk TA were shown to re-activate signaling by a stalkless CTF mutant in human cell culture assays. Novel Peptide Gaussian accelerated molecular dynamics (Pep-GaMD) simulations elucidated binding conformations of p9, p17, and p21 and revealed multiple specific binding regions to the stalkless CTF. Peptide agonists binding to the TOP domain of PC1 induced close TOP-putative pore loop interactions, a characteristic feature of stalk TA-mediated PC1 CTF activation. Additional sequence coevolution analyses showed the peptide binding regions were consistent with covarying residue pairs identified between the TOP domain and the stalk TA. These insights into the structural dynamic mechanism of PC1 activation by TA peptide agonists provide an in-depth understanding that will facilitate the development of therapeutics targeting PC1 for ADPKD treatment.

Life Sciences & Biomedicine - Other Topics↗

Mesoscale history of a small patch of clear air turbulence.

Sequential analyses of data from a network of eight special rawinsonde stations 100 km apart demonstrate the important effects of mesoscale disturbances in a 2.5-hr episode of light-to-moderate clear air turbulence (CAT). The most significant feature was the development of two turbulent fields below and above a 2-km region of a wind minimum which passed over Wallops Island, Va., near 1530 GMT on Feb. 4, 1970. The small scale of these features precludes their detection in the standard 12-hr observation sequence. The rawinsonde network utilized, which incorporates fine-scale details in both space and time, is adequate to provide a very useful current CAT depiction and an excellent source for the preparation of a short-range forecast of CAT.

Boucher, R. J.↗

Spectrophotometry of comet Kohoutek (1973f) during pre-perihelion period

Scans of the head of comet Kohoutek obtained during the pre-perihelion period with a photoelectric spectrum scanner are discussed. The mean relative flux distributions and the continuum energy distribution of the head of comet Kohoutek are given and normalized to 479 nm. The emission features of CN, C3, Ch, and the principal Swan band sequences of C2 and Na are identified and discussed. The adopted monochromatic values relative to 479 nm are given and plotted along with the energy distribution of the sun.

Babu, G. S. D.↗

Preliminary geologic mapping of Arsia Mons, Mars

Geologic mapping of the Tharsis Montes at a scale of 1:500,000 was recently initiated as part of the Mars Geologic Mapping Program of NASA. Detailed mapping of the three large shield volcanoes and their surroundings will help to clarify the sequence of events which led to the formation of these features, as well as provide a basis for comparing the complex histories of the three related yet distinctive volcanic centers. Preliminary mapping of Arsia Mons at a scale of 1:2 M was carried out in preparation for detailed mapping. A map is presented along with a discussion of its contents.

Zimbelman, James R.↗

A magnetospheric magnetic field model with flexible current systems driven by independent physical parameters

A tilt-dependent magnetic field model of the Earth's magnetosphere with variable magnetopause standoff distance is presented. Flexible analytic representations for the ring and cross-tail currents, each composed of the elements derived from the Tsyganenko and Usmanov (1982) model, are combined with the fully shielded vacuum dipole configurations of Voigt (1981). Although the current sheet does not warp in the y-z plane, changes in the shape and position of the neutral sheet with dipole tilt are consistent with both MHD equilibrium theory and observations. In addition, there is good agreement with observed Delta B profiles and the average equatorial contours of magnetic field magnitude. While the dipole field is rigorously shielded within the defined magnetopause, the ring and cross-tails currents are not similarly confined, consequently, the model's region of validity is limited to the inner magnetosphere. The model depends on four independent external parameters. We present a simple but limited method of simulating several substorm related magnetic field changes associated with the disrupion of the near-Earth cross-tail current sheet and collapse of the midnight magnetotail field region. This feature further facilitates the generation of magnetic field configuration time sequences useful in plasma convection simulations of real magnetospheric events.

Hilmer, Robert V.↗

Preliminary Stratigraphic Basis for Geologic Mapping of Venus

The age relations between geologic formations have been studied at 36 1000x1000 km areas centered at the dark paraboloid craters. The geologic setting in all these sites could be characterized using only 16 types of features and terrains (units). These units form a basic stratigraphic sequence (from older to younger: (1) Tessera (Tt); (2-3) Densely fractured terrains associated with coronae (COdf) and in the form of remnants among plains (Pdf); (4) Fractured and ridged plains (Pfr); (5) Plains with wrinkle ridges (Pwr); (6-7) Smooth and lobate plains (Ps/Pl); and (8) Rift-associated fractures (Fra). The stratigraphic position of the other units is determined by their relation with the units of the basic sequence: (9) Ridge bells (RB), contemporary with Pfr; (10-11) Ridges of coronae and arachnoids annuli (COar/Aar), contemporary with wrinkle ridges of Pwr; (12) Fractures of coronae annuli (COaf) disrupt Pwr and Ps/Pl; (13) Fractures (F) disrupt Pwr or younger units; (14) Craters with associated dark paraboloids (Cdp), which are on top of all volcanic and tectonic units except the youngest episodes of rift-associated fracturing and volcanism; (15-16) Surficial streaks (Ss) and surficial patches (Sp) are approximately contemporary with Cdp. These units may be used as a tentative basis for the geologic mapping of Venus including VMAP. This mapping should test the stratigraphy and answer the question of whether this stratigraphic sequence corresponds to geologic events which were generally synchronous all around the planet or whether the sequence is simply a typical sequence of events which occurred in different places at diffferent times.

Basilevsky, A. T.↗

Carbonate Platform Development and Stromatolite Morphogenesis: Constraints on Environmental and Biological Evolution

Work has been completed on the digital mapping of a terminal Proterozoic reef complex in Namibia. This complex formed an isolated carbonate platform developed downdip on a carbonate ramp of the Nama Group. The stratigraphic evolution of the platform was digitally reconstructed from an extensive dataset that was compiled by using digital surveying technologies. The platform comprises three accommodation cycles in which each subsequent cycle experienced progressively greater influence of a long-term accommodation increase. Aggradation and progradation during the first cycle resulted in a flat, uniform, sheet-like platform. The coarsening and shallowing-upward sequence representing the first cycle is dominated by columnar stromatolitic thrombolites and massive dolostones with interbedded mudstone-grainstone at the base of the sequence grading into cross-bedded dolostones. The second cycle features aggradation, formation of a distinct margin containing thrombolite mounds and domes, and the development of a bucket geometry. Columnar stromatolitic thrombolites dominate the platform interior. The final stage of platform development shows a deepening trend with initial aggradation and formation of well-bedded, thin deposits in the interior and mound development at the margins. While the interior drowned, the platform margin kept up with rising sea level and a complex pinnacle reef formed containing fused and coalesced thrombolite mounds flanked by bioclastic grainstones (containing Cloudina and Namacalathus fossils) and collapse breccias. A set of isolated large thrombolite mounds flanked by shales indicate the final stage of the carbonate platform. During a progressive increase in accommodation, a flat-topped isolated carbonate platform becomes aerially less extensive by either backstepping or formation of smaller pinnacles or a combination of both. The overall geometric evolution of the studied platform from flat-topped to bucket with elevated margins is recorded in many Proterozoic and Phanerozoic isolated carbonate platforms with similar dimensions. The terminal Proterozoic, microbial-dominated, isolated carbonate platform of this study clearly illustrates that the answer to accommodation changes was already familiar among carbonate platforms before the dawn of metazoan-dominated platforms.

Grotzinger, John P.↗

Robot Acting on Moving Bodies (RAMBO): Interaction with tumbling objects

Interaction with tumbling objects will become more common as human activities in space expand. Attempting to interact with a large complex object translating and rotating in space, a human operator using only his visual and mental capacities may not be able to estimate the object motion, plan actions or control those actions. A robot system (RAMBO) equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a tumbling object, is being developed. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations rearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enhancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using dynamic interpolations between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

Davis, Larry S.↗

DeepGRN: prediction of transcription factor binding site across cell-types using attention-based deep neural networks

Abstract Background Due to the complexity of the biological systems, the prediction of the potential DNA binding sites for transcription factors remains a difficult problem in computational biology. Genomic DNA sequences and experimental results from parallel sequencing provide available information about the affinity and accessibility of genome and are commonly used features in binding sites prediction. The attention mechanism in deep learning has shown its capability to learn long-range dependencies from sequential data, such as sentences and voices. Until now, no study has applied this approach in binding site inference from massively parallel sequencing data. The successful applications of attention mechanism in similar input contexts motivate us to build and test new methods that can accurately determine the binding sites of transcription factors. Results In this study, we propose a novel tool (named DeepGRN) for transcription factors binding site prediction based on the combination of two components: single attention module and pairwise attention module. The performance of our methods is evaluated on the ENCODE-DREAM in vivo Transcription Factor Binding Site Prediction Challenge datasets. The results show that DeepGRN achieves higher unified scores in 6 of 13 targets than any of the top four methods in the DREAM challenge. We also demonstrate that the attention weights learned by the model are correlated with potential informative inputs, such as DNase-Seq coverage and motifs, which provide possible explanations for the predictive improvements in DeepGRN. Conclusions DeepGRN can automatically and effectively predict transcription factor binding sites from DNA sequences and DNase-Seq coverage. Furthermore, the visualization techniques we developed for the attention modules help to interpret how critical patterns from different types of input features are recognized by our model.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Mechanical model of an earthquake fault

The dynamic behavior of a simple mechanical model of an earthquake fault is studied. This model, introduced originally by Burridge and Knopoff (1967), consists of an elastically coupled chain of masses in contact with a moving rough surface. The present version of the model retains the full Newtonian dynamics with inertial effects and contains no externally imposed stochasticity or spatial inhomogeneity. The only nonlinear feature is a velocity-weakening stick-slip friction force between the masses and the moving surface. This system is being driven persistently toward a slipping instability and therefore exhibits noisy sequences of earthquakelike events. These events are observed in numerical simulations, and many of their features can be predicted analytically.

Carlson, J. M.↗

The pesticidal Cry6Aa toxin from Bacillus thuringiensis is structurally similar to HlyE-family alpha pore-forming toxins

Background: The Cry6 family of proteins from Bacillus thuringiensis represents a group of powerful toxins with great potential for use in the control of coleopteran insects and of nematode parasites of importance to agriculture. These proteins are unrelated to other insecticidal toxins at the level of their primary sequences and the structure and function of these proteins has been poorly studied to date. This has inhibited our understanding of these toxins and their mode of action, along with our ability to manipulate the proteins to alter their activity to our advantage. To increase our understanding of their mode of action and to facilitate further development of these proteins we have determined the structure of Cry6Aa in protoxin and trypsin-activated forms and demonstrated a pore-forming mechanism of action. Results: The two forms of the toxin were resolved to 2.7 Å and 2.0 Å respectively and showed very similar structures. We report Cry6Aa shows structural homology to a known class of pore-forming toxins including hemolysin E from Escherichia coli and two Bacillus cereus proteins: the hemolytic toxin HblB and the NheA component of the non-hemolytic toxin (pfam05791). Cry6Aa also shows atypical features compared to other members of this family, including internal repeat sequences and small loop regions within major alpha helices. Trypsin processing was found to result in the loss of some internal sequences while the C-terminal region remains disulfide-linked to the main core of the toxin. Based on the structural similarity of Cry6Aa to other toxins, the mechanism of action of the toxin was probed and its ability to form pores in vivo in Caenorhabditis elegans was demonstrated. A non-toxic mutant was also produced, consistent with the proposed pore-forming mode of action. Conclusions: Cry6 proteins are members of the alpha helical pore-forming toxins – a structural class not previously recognized among the Cry toxins of B. thuringiensis and representing a new paradigm for nematocidal and insecticidal proteins. Elucidation of both the structure and the pore-forming mechanism of action of Cry6Aa now opens the way to more detailed analysis of toxin specificity and the development of new toxin variants with novel activities.

59 BASIC BIOLOGICAL SCIENCES↗

System for detecting objects in streaming 3D images formed from data acquired with a medium penetrating sensor

A detection system that detects subsurface objects within a medium and estimates various features of the objects is provided. The detection system receives a streaming sequence of image frames of the medium at various along-medium locations. An image frame contains voxel values (intensities) representing characteristics of the medium across the medium and in the depth (range) direction. The detection system depth-compensates the intensities for determining which voxels are part of an object using an unsupervised binary classifier. The detection system then connects object voxels into distinct objects and recursively estimates the features of those objects as the image frames stream based on the locations and intensities of the object voxels.

Paglieroni, David W.↗

Ecological connectivity and habitat loss shape patterns of genetic diversity in a threatened salamander

Context The maintenance of genetic diversity is essential for preserving adaptive potential in populations, yet it is increasingly threatened by landscape alteration. The field of landscape genetics offers a framework for assessing how patch-level landscape conditions, modeled at multiple scales, influence genetic diversity. Objectives We sought to assess how local environmental features and connectivity influence genetic diversity across 74 four-toed salamander (Hemidactylium scutatum) breeding wetlands in the southeastern United States. Methods Using next-generation sequencing data and hierarchical Bayesian models, we examined genome-wide heterozygosity in relation to local landscape features and ecological connectivity. We also assessed the scale of effect of landscape features and tested for temporal lag effects. Results Genetic diversity was lower in wetlands with higher levels of historic deforestation and lower connectivity. An interaction between deforestation and connectivity indicated that deforestation had stronger negative effects in isolated wetlands but weaker effects in well-connected wetlands. Accounting for scale of effect and temporal lags was critical for detecting these relationships. Conclusions Our analyses highlight the importance of assessing the spatial scale (scale of effect) and temporal lag of landscape features to detect key drivers of genetic diversity. In line with population genetic theory, our results indicate that the genetic consequences of habitat loss do not affect populations uniformly and are most severe in isolated populations where gene flow cannot buffer against loss of diversity. Altogether, we highlight the importance of considering the interaction of habitat loss and connectivity in conservation genetic management.

Hemidactylium scutatum↗