keyword
MENU ▼
Read by QxMD icon Read
search

Hidden markov

keyword
https://www.readbyqxmd.com/read/28524088/a-hybrid-generalized-hidden-markov-model-based-condition-monitoring-approach-for-rolling-bearings
#1
Jie Liu, Youmin Hu, Bo Wu, Yan Wang, Fengyun Xie
The operating condition of rolling bearings affects productivity and quality in the rotating machine process. Developing an effective rolling bearing condition monitoring approach is critical to accurately identify the operating condition. In this paper, a hybrid generalized hidden Markov model-based condition monitoring approach for rolling bearings is proposed, where interval valued features are used to efficiently recognize and classify machine states in the machine process. In the proposed method, vibration signals are decomposed into multiple modes with variational mode decomposition (VMD)...
May 18, 2017: Sensors
https://www.readbyqxmd.com/read/28522725/draft-genome-sequences-of-five-enterococcus-species-isolated-from-the-gut-of-patients-with-suspected-clostridium-difficile-infection
#2
Eduardo Castro-Nallar, Sandro L Valenzuela, Sebastián Baquedano, Carolina Sánchez, Fabiola Fernández, Annette N Trombert
We present draft genome sequences of five Enterococcus species from patients suspected of Clostridium difficile infection. Genome completeness was confirmed by presence of bacterial orthologs (97%). Gene searches using Hidden-Markov models revealed that the isolates harbor between seven and 11 genes involved in antibiotic resistance to tetracyclines, beta-lactams, and vancomycin.
May 18, 2017: Genome Announcements
https://www.readbyqxmd.com/read/28506839/evolutionary-relationships-among-protein-lysine-deacetylases-of-parasites-causing-neglected-diseases
#3
Larissa L S Scholte, Marina M Mourão, Fabiano Sviatopolk-Mirsky Pais, Jelena Melesina, Dina Robaa, Angela C Volpini, Wolfgang Sippl, Raymond J Pierce, Guilherme Oliveira, Laila A Nahum
The availability of the genomic data of diverse parasites provides an opportunity to identify new drug candidates against neglected tropical diseases affecting people worldwide. Histone modifying enzymes (HMEs) are potential candidates since they play key roles in the regulation of chromatin modifications, thus globally regulating gene expression. Furthermore, aberrant epigenetic states are often associated with human diseases, leading to great interest in HMEs as therapeutic targets. Our work focused on two families of protein lysine deacetylases (HDACs and sirtuins)...
May 13, 2017: Infection, Genetics and Evolution
https://www.readbyqxmd.com/read/28505138/estimating-density-and-temperature-dependence-of-juvenile-vital-rates-using-a-hidden-markov-model
#4
Robert M McElderry
Organisms in the wild have cryptic life stages that are sensitive to changing environmental conditions and can be difficult to survey. In this study, I used mark-recapture methods to repeatedly survey Anaea aidea (Nymphalidae) caterpillars in nature, then modeled caterpillar demography as a hidden Markov process to assess if temporal variability in temperature and density influence the survival and growth of A. aidea over time. Individual encounter histories result from the joint likelihood of being alive and observed in a particular stage, and I have included hidden states by separating demography and observations into parallel and independent processes...
May 15, 2017: Insects
https://www.readbyqxmd.com/read/28504948/substructural-regularization-with-data-sensitive-granularity-for-sequence-transfer-learning
#5
Shichang Sun, Hongbo Liu, Jiana Meng, C L Philip Chen, Yu Yang
Sequence transfer learning is of interest in both academia and industry with the emergence of numerous new text domains from Twitter and other social media tools. In this paper, we put forward the data-sensitive granularity for transfer learning, and then, a novel substructural regularization transfer learning model (STLM) is proposed to preserve target domain features at substructural granularity in the light of the condition of labeled data set size. Our model is underpinned by hidden Markov model and regularization theory, where the substructural representation can be integrated as a penalty after measuring the dissimilarity of substructures between target domain and STLM with relative entropy...
May 12, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28499990/a-state-space-and-density-estimation-framework-for-sleep-staging-in-obstructive-sleep-apnea
#6
Dae Y Kang, Pamela N DeYoung, Atul Malhotra, Robert L Owens, Todd P Coleman
OBJECTIVE: Although the importance of sleep is increasingly recognized, the lack of robust and efficient algorithms hinders scalable sleep assessment in healthy persons and those with sleep disorders. Polysomnography (PSG) and visual/manual scoring remain the gold standard in sleep evaluation, but more efficient/automated systems are needed. Most previous works have demonstrated algorithms in high agreement with the gold standard in healthy/normal (HN) individuals - not those with sleep disorders...
May 8, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28497059/a-new-algorithm-for-identifying-cis-regulatory-modules-based-on-hidden-markov-model
#7
Haitao Guo, Hongwei Huo
The discovery of cis-regulatory modules (CRMs) is the key to understanding mechanisms of transcription regulation. Since CRMs have specific regulatory structures that are the basis for the regulation of gene expression, how to model the regulatory structure of CRMs has a considerable impact on the performance of CRM identification. The paper proposes a CRM discovery algorithm called ComSPS. ComSPS builds a regulatory structure model of CRMs based on HMM by exploring the rules of CRM transcriptional grammar that governs the internal motif site arrangement of CRMs...
2017: BioMed Research International
https://www.readbyqxmd.com/read/28496407/unsupervised-idealization-of-ion-channel-recordings-by-minimum-description-length-application-to-human-piezo1-channels
#8
Radhakrishnan Gnanasambandam, Morten S Nielsen, Christopher Nicolai, Frederick Sachs, Johannes P Hofgaard, Jakob K Dreyer
Researchers can investigate the mechanistic and molecular basis of many physiological phenomena in cells by analyzing the fundamental properties of single ion channels. These analyses entail recording single channel currents and measuring current amplitudes and transition rates between conductance states. Since most electrophysiological recordings contain noise, the data analysis can proceed by idealizing the recordings to isolate the true currents from the noise. This de-noising can be accomplished with threshold crossing algorithms and Hidden Markov Models, but such procedures generally depend on inputs and supervision by the user, thus requiring some prior knowledge of underlying processes...
2017: Frontiers in Neuroinformatics
https://www.readbyqxmd.com/read/28486689/the-phytoclust-tool-for-metabolic-gene-clusters-discovery-in-plant-genomes
#9
Nadine Töpfer, Lisa-Maria Fuchs, Asaph Aharoni
The existence of Metabolic Gene Clusters (MGCs) in plant genomes has recently raised increased interest. Thus far, MGCs were commonly identified for pathways of specialized metabolism, mostly those associated with terpene type products. For efficient identification of novel MGCs, computational approaches are essential. Here, we present PhytoClust; a tool for the detection of candidate MGCs in plant genomes. The algorithm employs a collection of enzyme families related to plant specialized metabolism, translated into hidden Markov models, to mine given genome sequences for physically co-localized metabolic enzymes...
May 9, 2017: Nucleic Acids Research
https://www.readbyqxmd.com/read/28482128/hidden-markov-models-for-extended-batch-data
#10
Laura L E Cowen, Panagiotis Besbeas, Byron J T Morgan, Carl J Schwarz
Batch marking provides an important and efficient way to estimate the survival probabilities and population sizes of wild animals. It is particularly useful when dealing with animals that are difficult to mark individually. For the first time, we provide the likelihood for extended batch-marking experiments. It is often the case that samples contain individuals that remain unmarked, due to time and other constraints, and this information has not previously been analyzed. We provide ways of modeling such information, including an open N-mixture approach...
May 8, 2017: Biometrics
https://www.readbyqxmd.com/read/28470722/estimation-and-simulation-of-foraging-trips-in-land-based-marine-predators
#11
Théo Michelot, Roland Langrock, Sophie Bestley, Ian D Jonsen, Theoni Photopoulou, Toby A Patterson
The behaviour of colony-based marine predators is the focus of much research globally. Large telemetry and tracking data sets have been collected for this group of animals, and are accompanied by many empirical studies that seek to segment tracks in some useful way, as well as theoretical studies of optimal foraging strategies. However, relatively few studies have detailed statistical methods for inferring behaviours in central place foraging trips. In this paper we describe an approach based on hidden Markov models, which splits foraging trips into segments labeled as "outbound", "search", "forage", and "inbound"...
May 4, 2017: Ecology
https://www.readbyqxmd.com/read/28469382/performance-of-hidden-markov-models-in-recovering-the-standard-classification-of-glycoside-hydrolases
#12
Mariana Fonseca Rossi, Beatriz Mello, Carlos G Schrago
Glycoside hydrolases (GHs) are carbohydrate-active enzymes that assist the hydrolysis of glycoside bonds of complex sugars into carbohydrates. The current standard GH family classification is available in the CAZy database, which is based on the similarities of amino acid sequences and curated semi-automatically. However, with the exponential increase in data availability from genome sequences, automated classification methods are required for the fast annotation of coding sequences. Currently, the dbCAN database offers automatic annotations of signature domains from CAZy-defined classifications using a statistical approach, the hidden Markov models (HMMs)...
2017: Evolutionary Bioinformatics Online
https://www.readbyqxmd.com/read/28466793/seqping-gene-prediction-pipeline-for-plant-genomes-using-self-training-gene-models-and-transcriptomic-data
#13
Kuang-Lim Chan, Rozana Rosli, Tatiana V Tatarinova, Michael Hogan, Mohd Firdaus-Raih, Eng-Ti Leslie Low
BACKGROUND: Gene prediction is one of the most important steps in the genome annotation process. A large number of software tools and pipelines developed by various computing techniques are available for gene prediction. However, these systems have yet to accurately predict all or even most of the protein-coding regions. Furthermore, none of the currently available gene-finders has a universal Hidden Markov Model (HMM) that can perform gene prediction for all organisms equally well in an automatic fashion...
January 27, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28465594/crowding-facilitated-macromolecular-transport-in-attractive-micropost-arrays
#14
Fan-Tso Chien, Po-Keng Lin, Wei Chien, Cheng-Hsiang Hung, Ming-Hung Yu, Chia-Fu Chou, Yeng-Long Chen
Our study of DNA dynamics in weakly attractive nanofabricated post arrays revealed crowding enhances polymer transport, contrary to hindered transport in repulsive medium. The coupling of DNA diffusion and adsorption to the microposts results in more frequent cross-post hopping and increased long-term diffusivity with increased crowding density. We performed Langevin dynamics simulations and found maximum long-term diffusivity in post arrays with gap sizes comparable to the polymer radius of gyration. We found that macromolecular transport in weakly attractive post arrays is faster than in non-attractive dense medium...
May 2, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28462208/diagnosis-of-the-ocd-patients-using-drawing-features-of-the-bender-gestalt-shapes
#15
R Boostani, F Asadi, N Mohammadi
BACKGROUND: Since psychological tests such as questionnaire or drawing tests are almost qualitative, their results carry a degree of uncertainty and sometimes subjectivity. The deficiency of all drawing tests is that the assessment is carried out after drawing the objects and lots of information such as pen angle, speed, curvature and pressure are missed through the test. In other words, the psychologists cannot assess their patients while running the tests. One of the famous drawing tests to measure the degree of Obsession Compulsion Disorder (OCD) is the Bender Gestalt, though its reliability is not promising...
March 2017: Journal of Biomedical Physics & Engineering
https://www.readbyqxmd.com/read/28462050/a-profile-hidden-markov-model-to-investigate-the-distribution-and-frequency-of-lanb-encoding-lantibiotic-modification-genes-in-the-human-oral-and-gut-microbiome
#16
Calum J Walsh, Caitriona M Guinane, Paul W O' Toole, Paul D Cotter
BACKGROUND: The human microbiota plays a key role in health and disease, and bacteriocins, which are small, bacterially produced, antimicrobial peptides, are likely to have an important function in the stability and dynamics of this community. Here we examined the density and distribution of the subclass I lantibiotic modification protein, LanB, in human oral and stool microbiome datasets using a specially constructed profile Hidden Markov Model (HMM). METHODS: The model was validated by correctly identifying known lanB genes in the genomes of known bacteriocin producers more effectively than other methods, while being sensitive enough to differentiate between different subclasses of lantibiotic modification proteins...
2017: PeerJ
https://www.readbyqxmd.com/read/28460141/hh-motif-de-novo-detection-of-short-linear-motifs-in-proteins-by-hidden-markov-model-comparisons
#17
Roman Prytuliak, Michael Volkmer, Markus Meier, Bianca H Habermann
Short linear motifs (SLiMs) in proteins are self-sufficient functional sequences that specify interaction sites for other molecules and thus mediate a multitude of functions. Computational, as well as experimental biological research would significantly benefit, if SLiMs in proteins could be correctly predicted de novo with high sensitivity. However, de novo SLiM prediction is a difficult computational task. When considering recall and precision, the performances of published methods indicate remaining challenges in SLiM discovery...
April 29, 2017: Nucleic Acids Research
https://www.readbyqxmd.com/read/28459175/a-change-point-model-for-detecting-heterogeneity-in-ordered-survival-responses
#18
Olivier Bouaziz, Grégory Nuel
In this article, we suggest a new statistical approach considering survival heterogeneity as a breakpoint model in an ordered sequence of time-to-event variables. The survival responses need to be ordered according to a numerical covariate. Our estimation method will aim at detecting heterogeneity that could arise through the ordering covariate. We formally introduce our model as a constrained Hidden Markov Model, where the hidden states are the unknown segmentation (breakpoint locations) and the observed states are the survival responses...
January 1, 2017: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/28453653/the-bologna-annotation-resource-bar-3-0-improving-protein-functional-annotation
#19
Giuseppe Profiti, Pier Luigi Martelli, Rita Casadio
BAR 3.0 updates our server BAR (Bologna Annotation Resource) for predicting protein structural and functional features from sequence. We increase data volume, query capabilities and information conveyed to the user. The core of BAR 3.0 is a graph-based clustering procedure of UniProtKB sequences, following strict pairwise similarity criteria (sequence identity ≥40% with alignment coverage ≥90%). Each cluster contains the available annotation downloaded from UniProtKB, GO, PFAM and PDB. After statistical validation, GO terms and PFAM domains are cluster-specific and annotate new sequences entering the cluster after satisfying similarity constraints...
April 27, 2017: Nucleic Acids Research
https://www.readbyqxmd.com/read/28443037/analyzing-dyadic-sequence-data-research-questions-and-implied-statistical-models
#20
Peter Fuchs, Fridtjof W Nussbeck, Nathalie Meuwly, Guy Bodenmann
The analysis of observational data is often seen as a key approach to understanding dynamics in romantic relationships but also in dyadic systems in general. Statistical models for the analysis of dyadic observational data are not commonly known or applied. In this contribution, selected approaches to dyadic sequence data will be presented with a focus on models that can be applied when sample sizes are of medium size (N = 100 couples or less). Each of the statistical models is motivated by an underlying potential research question, the most important model results are presented and linked to the research question...
2017: Frontiers in Psychology
keyword
keyword
10336
1
2
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read
×

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"