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https://www.readbyqxmd.com/read/29771380/dbcan2-a-meta-server-for-automated-carbohydrate-active-enzyme-annotation
#1
Han Zhang, Tanner Yohe, Le Huang, Sarah Entwistle, Peizhi Wu, Zhenglu Yang, Peter K Busk, Ying Xu, Yanbin Yin
Complex carbohydrates of plants are the main food sources of animals and microbes, and serve as promising renewable feedstock for biofuel and biomaterial production. Carbohydrate active enzymes (CAZymes) are the most important enzymes for complex carbohydrate metabolism. With an increasing number of plant and plant-associated microbial genomes and metagenomes being sequenced, there is an urgent need of automatic tools for genomic data mining of CAZymes. We developed the dbCAN web server in 2012 to provide a public service for automated CAZyme annotation for newly sequenced genomes...
May 16, 2018: Nucleic Acids Research
https://www.readbyqxmd.com/read/29746521/a-flavin-dependent-halogenase-from-metagenomic-analysis-prefers-bromination-over-chlorination
#2
Pia R Neubauer, Christiane Widmann, Daniel Wibberg, Lea Schröder, Marcel Frese, Tilman Kottke, Jörn Kalinowski, Hartmut H Niemann, Norbert Sewald
Flavin-dependent halogenases catalyse halogenation of aromatic compounds. In most cases, this reaction proceeds with high regioselectivity and requires only the presence of FADH2, oxygen, and halide salts. Since marine habitats contain high concentrations of halides, organisms populating the oceans might be valuable sources of yet undiscovered halogenases. A new Hidden-Markov-Model (HMM) based on the PFAM tryptophan halogenase model was used for the analysis of marine metagenomes. Eleven metagenomes were screened leading to the identification of 254 complete or partial putative flavin-dependent halogenase genes...
2018: PloS One
https://www.readbyqxmd.com/read/29745535/-novel-type-of-unperturbed-sleep-monitoring-scheme-under-pillow-based-on-hidden-markov-model
#3
Xiang Li, Yong Liu, Pengbin Chen, Jiewei Wu, Han Zhang
Sleep status is an important indicator to evaluate the health status of human beings. In this paper, we proposed a novel type of unperturbed sleep monitoring system under pillow to identify the pattern change of heart rate variability (HRV) through obtained RR interval signal, and to calculate the corresponding sleep stages combined with hidden Markov model (HMM) under the no-perception condition. In order to solve the existing problems of sleep staging based on HMM, ensemble empirical mode decomposition (EEMD) was proposed to eliminate the error caused by the individual differences in HRV and then to calculate the corresponding sleep stages...
April 1, 2018: Sheng Wu Yi Xue Gong Cheng Xue za Zhi, Journal of Biomedical Engineering, Shengwu Yixue Gongchengxue Zazhi
https://www.readbyqxmd.com/read/29740654/light-induced-atp-driven-self-assembly-of-actin-and-heavy-meromyosin-in-proteo-tubularsomes-as-a-step-toward-artificial-cells
#4
Satarupa Dhir, Sumalee Salahub, Anu Stella Mathews, Surjith Kumar Kumaran, Carlo D Montemagno, Sinoj Abraham
In this work, we studied the light induced self-assembly of F-actin and heavy meromyosin (HMM) in tubular vesicles or "tubularsomes" during initiation by ATP. To mimic nature, light-induced ATP synthesis was used for the F-actin/HMM self-assembly inside these vesicles created from a triblock copolymer reconstituted with the membrane protein bacteriorhodopsin (bR) and F1F0-ATPase along with F-actin and HMM in the core.
May 9, 2018: Chemical Communications: Chem Comm
https://www.readbyqxmd.com/read/29726433/automated-error-detection-in-physiotherapy-training
#5
Marko Jovanović, Johannes Seiffarth, Ekaterina Kutafina, Stephan M Jonas
BACKGROUND: Manual skills teaching, such as physiotherapy education, requires immediate teacher feedback for the students during the learning process, which to date can only be performed by expert trainers. OBJECTIVES: A machine-learning system trained only on correct performances to classify and score performed movements, to identify sources of errors in the movement and give feedback to the learner. METHODS: We acquire IMU and sEMG sensor data from a commercial-grade wearable device and construct an HMM-based model for gesture classification, scoring and feedback giving...
2018: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/29716080/optical-bistability-based-on-hyperbolic-metamaterials
#6
Myunghwan Kim, Sangin Kim, Soeun Kim
We numerically demonstrate optical bistability in a nonlinear multilayer structure by utilizing the unique dispersion of hyperbolic metamaterials. The linear transmission is varied sharply with topological transition of isofrequency contour of the multilayer structure, and this non-resonant scheme enables realization of optical bistability with a short response time and a relatively low switching intensity. We have investigated exhaustively all possible topological transitions in the dispersion characteristics of the multilayer structure for optical bistability, and shown that the hyperbolic metamaterial (HMM) type transition from Type II to Type I, and the transition from Type II HMM to effective dielectric are suitable for realizing high-performances optical bistability...
April 30, 2018: Optics Express
https://www.readbyqxmd.com/read/29700885/social-networks-cooperative-breeding-and-the-human-milk-microbiome
#7
Courtney L Meehan, Kimberly A Lackey, Edward H Hagen, Janet E Williams, Jennifer Roulette, Courtney Helfrecht, Mark A McGuire, Michelle K McGuire
OBJECTIVES: We present the first available data on the human milk microbiome (HMM) from small-scale societies (hunter-gatherers and horticulturalists in the Central African Republic [CAR]) and explore relationships among subsistence type and seasonality on HMM diversity and composition. Additionally, as humans are cooperative breeders and, throughout our evolutionary history and today, we rear offspring within social networks, we examine associations between the social environment and the HMM...
April 26, 2018: American Journal of Human Biology: the Official Journal of the Human Biology Council
https://www.readbyqxmd.com/read/29700659/mathematical-basis-of-predicting-dominant-function-in-protein-sequences-by-a-generic-hmm-ann-algorithm
#8
Siddhartha Kundu
The accurate annotation of an unknown protein sequence depends on extant data of template sequences. This could be empirical or sets of reference sequences, and provides an exhaustive pool of probable functions. Individual methods of predicting dominant function possess shortcomings such as varying degrees of inter-sequence redundancy, arbitrary domain inclusion thresholds, heterogeneous parameterization protocols, and ill-conditioned input channels. Here, I present a rigorous theoretical derivation of various steps of a generic algorithm that integrates and utilizes several statistical methods to predict the dominant function in unknown protein sequences...
April 26, 2018: Acta Biotheoretica
https://www.readbyqxmd.com/read/29677987/towards-unsupervised-detection-of-process-models-in-healthcare
#9
Amirah Alharbi, Andy Bulpitt, Owen A Johnson
Process mining techniques can play a significant role in understanding healthcare processes by supporting analysis of patient records in electronic health record systems. Healthcare processes are complex and patterns of care may vary considerably within similar cohorts of patients. Process mining often creates "spaghetti" models and require significant domain expert input to refine. Machine learning approaches such as Hidden Markov Models (HMM) may assist this refinement process. HMMs have been advocated for patient pathways clustering purposes; however these models can also be utilized for detecting hidden processes to help event abstraction...
2018: Studies in Health Technology and Informatics
https://www.readbyqxmd.com/read/29675014/the-resistome-of-low-impacted-marine-environments-is-composed-by-distant-metallo-%C3%AE-lactamases-homologs
#10
Erica L Fonseca, Bruno G N Andrade, Ana C P Vicente
The worldwide dispersion and sudden emergence of new antibiotic resistance genes (ARGs) determined the need in uncovering which environment participate most as their source and reservoir. ARGs closely related to those currently found in human pathogens occur in the resistome of anthropogenic impacted environments. However, the role of pristine environment as the origin and source of ARGs remains underexplored and controversy, particularly, the marine environments represented by the oceans. Here, due to the ocean nature, we hypothesized that the resistome of this pristine/low-impacted marine environment is represented by distant ARG homologs...
2018: Frontiers in Microbiology
https://www.readbyqxmd.com/read/29666568/biologically-inspired-spike-based-automatic-speech-recognition-of-isolated-digits-over-a-reproducing-kernel-hilbert-space
#11
Kan Li, José C Príncipe
This paper presents a novel real-time dynamic framework for quantifying time-series structure in spoken words using spikes. Audio signals are converted into multi-channel spike trains using a biologically-inspired leaky integrate-and-fire (LIF) spike generator. These spike trains are mapped into a function space of infinite dimension, i.e., a Reproducing Kernel Hilbert Space (RKHS) using point-process kernels, where a state-space model learns the dynamics of the multidimensional spike input using gradient descent learning...
2018: Frontiers in Neuroscience
https://www.readbyqxmd.com/read/29617803/genome-wide-association-study-for-feed-efficiency-traits-using-snp-and-haplotype-models
#12
K R Schweer, S D Kachman, L A Kuehn, H C Freetly, E J Pollak, M L Spangler
Feed costs comprise the majority of variable expenses in beef cattle systems making feed efficiency an important economic consideration within the beef industry. Due to the expense of recording individual feed intake phenotypes, a genomic-enabled approach could be advantageous towards improving this economically relevant trait complex. A genome-wide association study (GWAS) was performed using 748 crossbred steers and heifers representing seven sire breeds with phenotypes for average daily gain (ADG) and average daily feed intake (ADFI)...
March 29, 2018: Journal of Animal Science
https://www.readbyqxmd.com/read/29571901/disease-genes-prediction-by-hmm-based-pu-learning-using-gene-expression-profiles
#13
Ozra Nikdelfaz, Saeed Jalili
Predicting disease candidate genes from human genome is a crucial part of nowadays biomedical research. According to observations, diseases with the same phenotype have the similar biological characteristics and genes associated with these same diseases tend to share common functional properties. Therefore, by applying machine learning methods, new disease genes are predicted based on previous ones. In recent studies, some semi-supervised learning methods, called Positive-Unlabeled Learning (PU-Learning) are used for predicting disease candidate genes...
March 20, 2018: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/29571832/clinical-prediction-performance-of-glaucoma-progression-using-a-2-dimensional-continuous-time-hidden-markov-model-with-structural-and-functional-measurements
#14
Youngseok Song, Hiroshi Ishikawa, Mengfei Wu, Yu-Ying Liu, Katie A Lucy, Fabio Lavinsky, Mengling Liu, Gadi Wollstein, Joel S Schuman
PURPOSE: Previously, we introduced a state-based 2-dimensional continuous-time hidden Markov model (2D CT HMM) to model the pattern of detected glaucoma changes using structural and functional information simultaneously. The purpose of this study was to evaluate the detected glaucoma change prediction performance of the model in a real clinical setting using a retrospective longitudinal dataset. DESIGN: Longitudinal, retrospective study. PARTICIPANTS: One hundred thirty-four eyes from 134 participants diagnosed with glaucoma or as glaucoma suspects (average follow-up, 4...
March 20, 2018: Ophthalmology
https://www.readbyqxmd.com/read/29549553/automated-surgical-skill-assessment-in-rmis-training
#15
Aneeq Zia, Irfan Essa
PURPOSE: Manual feedback in basic robot-assisted minimally invasive surgery (RMIS) training can consume a significant amount of time from expert surgeons' schedule and is prone to subjectivity. In this paper, we explore the usage of different holistic features for automated skill assessment using only robot kinematic data and propose a weighted feature fusion technique for improving score prediction performance. Moreover, we also propose a method for generating 'task highlights' which can give surgeons a more directed feedback regarding which segments had the most effect on the final skill score...
May 2018: International Journal of Computer Assisted Radiology and Surgery
https://www.readbyqxmd.com/read/29529749/biaxial-hyperbolic-metamaterials-using-anisotropic-few-layer-black-phosphorus
#16
Xianglian Song, Zizhuo Liu, Yuanjiang Xiang, Koray Aydin
Most of hyperbolic metamaterials (HMMs) investigated to date are based on isotropic materials resulting in uniaxial HMMs in which dielectric permittivities perpendicular to the propagation direction are the same. Using an anisotropic material constituent to form a HMM is a promising research direction providing opportunities to control the dielectric permittivity in all three directions independently. Herein, we propose and theoretically demonstrate novel biaxial HMMs composed of multilayer stacks of few-layer black phosphorus (BP) and Au thin films...
March 5, 2018: Optics Express
https://www.readbyqxmd.com/read/29522408/improving-acoustic-models-in-torgo-dysarthric-speech-database
#17
Neethu Mariam Joy, S Umesh
Assistive speech-based technologies can improve the quality of life for people affected with dysarthria, a motor speech disorder. In this paper, we explore multiple ways to improve Gaussian mixture model and deep neural network (DNN) based hidden Markov model (HMM) automatic speech recognition systems for TORGO dysarthric speech database. This work shows significant improvements over the previous attempts in building such systems in TORGO. We trained speaker-specific acoustic models by tuning various acoustic model parameters, using speaker normalized cepstral features and building complex DNN-HMM models with dropout and sequence-discrimination strategies...
March 2018: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/29512215/nanostructuring-multilayer-hyperbolic-metamaterials-for-ultrafast-and-bright-green-ingan-quantum-wells
#18
Dylan Lu, Haoliang Qian, Kangwei Wang, Hao Shen, Feifei Wei, Yunfeng Jiang, Eric E Fullerton, Paul K L Yu, Zhaowei Liu
Semiconductor quantum well (QW) light-emitting diodes (LEDs) have limited temporal modulation bandwidth of a few hundred MHz due to the long carrier recombination lifetime. Material doping and structure engineering typically leads to incremental change in the carrier recombination rate, whereas the plasmonic-based Purcell effect enables dramatic improvement for modulation frequency beyond the GHz limit. By stacking Ag-Si multilayers, the resulting hyperbolic metamaterials (HMMs) have shown tunability in the plasmonic density of states for enhancing light emission at various wavelengths...
April 2018: Advanced Materials
https://www.readbyqxmd.com/read/29500532/evolutionary-divergence-of-tnl-disease-resistant-proteins-in-soybean-glycine-max-and-common-bean-phaseolus-vulgaris
#19
Surendra Neupane, Qin Ma, Febina M Mathew, Adam J Varenhorst, Ethan J Andersen, Madhav P Nepal
Disease-resistant genes (R genes) encode proteins that are involved in protecting plants from their pathogens and pests. Availability of complete genome sequences from soybean and common bean allowed us to perform a genome-wide identification and analysis of the Toll interleukin-1 receptor-like nucleotide-binding site leucine-rich repeat (TNL) proteins. Hidden Markov model (HMM) profiling of all protein sequences resulted in the identification of 117 and 77 regular TNL genes in soybean and common bean, respectively...
March 2, 2018: Biochemical Genetics
https://www.readbyqxmd.com/read/29495754/histogram-equalization-with-bayesian-estimation-for-noise-robust-speech-recognition
#20
Youngjoo Suh, Hoirin Kim
The histogram equalization approach is an efficient feature normalization technique for noise robust automatic speech recognition. However, it suffers from performance degradation when some fundamental conditions are not satisfied in the test environment. To remedy these limitations of the original histogram equalization methods, class-based histogram equalization approach has been proposed. Although this approach showed substantial performance improvement under noise environments, it still suffers from performance degradation due to the overfitting problem when test data are insufficient...
February 2018: Journal of the Acoustical Society of America
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