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Hidden markov

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https://www.readbyqxmd.com/read/28092512/a-hidden-markov-model-for-seismocardiography
#1
Johan Wahlstrom, Isaac Skog, Peter Handel, Farzad Khosrow-Khavar, Kouhyar Tavakolian, Phyllis K Stein, Arye Nehorai
We propose a hidden Markov model approach for processing seismocardiograms. The seismocardiogram morphology is learned using the expectation-maximization algorithm, and the state of the heart at a given time instant is estimated by the Viterbi algorithm. From the obtained Viterbi sequence, it is then straightforward to estimate instantaneous heart rate, heart rate variability measures, and cardiac time intervals (the latter requiring a small number of manual annotations). As is shown in the conducted experimental study, the presented algorithm outperforms the state-of-the-art in seismocardiogrambased heart rate and heart rate variability estimation Moreover, the isovolumic contraction time and the left ventricular ejection time are estimated with mean absolute errors of about 5 [ms] and 9 [ms], respectively...
January 9, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28092026/hidden-markov-models-for-protein-domain-homology-identification-and-analysis
#2
Karl Jablonowski
Protein domain identification and analysis are cornerstones of modern proteomics. The tools available to protein domain researchers avail a variety of approaches to understanding large protein domain families. Hidden Markov Models (HMM) form the basis for identifying and categorizing evolutionarily linked protein domains. Here I describe the use of HMM models for predicting and identifying Src Homology 2 (SH2) domains within the proteome.
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/28087663/evolution-and-structural-diversification-of-nictaba-like-lectin-genes-in-food-crops-with-a-focus-on-soybean-glycine-max
#3
Sofie Van Holle, Pierre Rougé, Els J M Van Damme
BACKGROUND AND AIMS: The Nictaba family groups all proteins that show homology to Nictaba, the tobacco lectin. So far, Nictaba and an Arabidopsis thaliana homologue have been shown to be implicated in the plant stress response. The availability of more than 50 sequenced plant genomes provided the opportunity for a genome-wide identification of Nictaba-like genes in 15 species, representing members of the Fabaceae, Poaceae, Solanaceae, Musaceae, Arecaceae, Malvaceae and Rubiaceae. Additionally, phylogenetic relationships between the different species were explored...
January 12, 2017: Annals of Botany
https://www.readbyqxmd.com/read/28086791/identification-of-functional-enolase-genes-of-the-silkworm-bombyx-mori-from-public-databases-with-a-combination-of-dry-and-wet-bench-processes
#4
Akira Kikuchi, Takeru Nakazato, Katsuhiko Ito, Yosui Nojima, Takeshi Yokoyama, Kikuo Iwabuchi, Hidemasa Bono, Atsushi Toyoda, Asao Fujiyama, Ryoichi Sato, Hiroko Tabunoki
BACKGROUND: Various insect species have been added to genomic databases over the years. Thus, researchers can easily obtain online genomic information on invertebrates and insects. However, many incorrectly annotated genes are included in these databases, which can prevent the correct interpretation of subsequent functional analyses. To address this problem, we used a combination of dry and wet bench processes to select functional genes from public databases. RESULTS: Enolase is an important glycolytic enzyme in all organisms...
January 13, 2017: BMC Genomics
https://www.readbyqxmd.com/read/28076801/msmbuilder-statistical-models-for-biomolecular-dynamics
#5
Matthew P Harrigan, Mohammad M Sultan, Carlos X Hernández, Brooke E Husic, Peter Eastman, Christian R Schwantes, Kyle A Beauchamp, Robert T McGibbon, Vijay S Pande
MSMBuilder is a software package for building statistical models of high-dimensional time-series data. It is designed with a particular focus on the analysis of atomistic simulations of biomolecular dynamics such as protein folding and conformational change. MSMBuilder is named for its ability to construct Markov state models (MSMs), a class of models that has gained favor among computational biophysicists. In addition to both well-established and newer MSM methods, the package includes complementary algorithms for understanding time-series data such as hidden Markov models and time-structure based independent component analysis...
January 10, 2017: Biophysical Journal
https://www.readbyqxmd.com/read/28067598/why-so-narrow-distribution-of-anti-sense-regulated-type-i-toxin-antitoxin-systems-compared-to-type-ii-and-type-iii-systems
#6
Dorien S Coray, Nicole E Wheeler, Jack A Heinemann, Paul P Gardner
Toxin-antitoxin (TA) systems are gene modules that appear to be horizontally mobile across a wide range of prokaryotes. It has been proposed that type I TA systems, with an antisense RNA-antitoxin, are less mobile than other TAs that rely on direct toxin-antitoxin binding but no direct comparisons have been made. We searched for type I, II and III toxin families using iterative searches with profile hidden Markov models across phyla and replicons. The distribution of type I toxin families were comparatively narrow, but these patterns weakened with recently discovered families...
January 9, 2017: RNA Biology
https://www.readbyqxmd.com/read/28065836/learning-effective-connectivity-from-fmri-using-autoregressive-hidden-markov-model-with-missing-data
#7
Shilpa Dang, Santanu Chaudhury, Brejesh Lall, Prasun Kumar Roy
BACKGROUND: Effective connectivity (EC) analysis of neuronal groups using fMRI delivers insights about functional-integration. However, fMRI signal has low-temporal resolution due to down-sampling and indirectly measures underlying neuronal activity. NEW METHOD: The aim is to address above issues for more reliable EC estimates. This paper proposes use of autoregressive hidden Markov model with missing data (AR-HMM-md) in dynamically multi-linked (DML) framework for learning EC using multiple fMRI time series...
January 5, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/28062446/phmm-tree-phylogeny-of-profile-hidden-markov-models
#8
Luyang Huo, Han Zhang, Xueting Huo, Yasong Yang, Xueqiong Li, Yanbin Yin
: Protein families are often represented by profile hidden Markov models (pHMMs). Homology between two distant protein families can be determined by comparing the pHMMs. Here we explored the idea of building a phylogeny of protein families using the distance matrix of their pHMMs. We developed a new software and web server (pHMM-tree) to allow four major types of inputs: (i) multiple pHMM files, (ii) multiple aligned protein sequence files, (iii) mixture of pHMM and aligned sequence files and (iv) unaligned protein sequences in a single file...
January 5, 2017: Bioinformatics
https://www.readbyqxmd.com/read/28060703/a-dataset-and-benchmarks-for-segmentation-and-recognition-of-gestures-in-robotic-surgery
#9
Narges Ahmidi, Lingling Tao, Shahin Sefati, Yixin Gao, Colin Lea, Benjamin Bejar, Luca Zappella, Sanjeev Khudanpur, Rene Vidal, Gregory D Hager
OBJECTIVE: State-of-the-art techniques for surgical data analysis report promising results for automated skill assessment and action recognition. The contributions of many of these techniques, however, are limited to study-specific data and validation metrics, making assessment of progress across the field extremely challenging. METHODS: In this paper, we address two major problems for surgical data analysis: (1) lack of uniform shared datasets and benchmarks and (2) lack of consistent validation processes...
January 4, 2017: IEEE Transactions on Bio-medical Engineering
https://www.readbyqxmd.com/read/28056037/accurate-promoter-and-enhancer-identification-in-127-encode-and-roadmap-epigenomics-cell-types-and-tissues-by-genostan
#10
Benedikt Zacher, Margaux Michel, Björn Schwalb, Patrick Cramer, Achim Tresch, Julien Gagneur
Accurate maps of promoters and enhancers are required for understanding transcriptional regulation. Promoters and enhancers are usually mapped by integration of chromatin assays charting histone modifications, DNA accessibility, and transcription factor binding. However, current algorithms are limited by unrealistic data distribution assumptions. Here we propose GenoSTAN (Genomic STate ANnotation), a hidden Markov model overcoming these limitations. We map promoters and enhancers for 127 cell types and tissues from the ENCODE and Roadmap Epigenomics projects, today's largest compendium of chromatin assays...
2017: PloS One
https://www.readbyqxmd.com/read/28052496/species-interactions-and-the-effects-of-climate-variability-on-a-wetland-amphibian-metacommunity
#11
Courtney L Davis, David A W Miller, Susan C Walls, William J Barichivich, Jeffrey W Riley, Mary E Brown
Disentangling the role that multiple interacting factors have on species responses to shifting climate poses a significant challenge. However, our ability to do so is of utmost importance to predict the effects of climate change on species distributions. We examined how populations of three species of wetland-breeding amphibians, which varied in life history requirements, responded to a six-year period of extremely variable precipitation. This interval was punctuated by both extensive drought and heavy precipitation and flooding, providing a natural experiment to measure community responses to environmental perturbations...
January 2017: Ecological Applications: a Publication of the Ecological Society of America
https://www.readbyqxmd.com/read/28048485/su-d-bra-05-time-series-analysis-of-epid-images-to-identify-patients-in-need-of-treatment-adaptation
#12
L Archambault, O Piron, N Varfalvy
PURPOSE: to evaluate if time series analysis of portal dose images can be used to identify patients undergoing important anatomical changes. METHODS: daily EPID images of every treatment fields were acquired for 48 patients treated for lung cancer. In addition, CBCT were acquired on a regular basis (weekly or biweekly). Gamma analysis was performed relative to the first fraction given that no significant anatomical change was observed on the CBCT of the first fraction compared to the planning CT...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28046627/tu-ab-202-11-tumor-segmentation-by-fusion-of-multi-tracer-pet-images-using-copula-based-statistical-methods
#13
J Lapuyade-Lahorgue, S Ruan, H Li, P Vera
PURPOSE: Multi-tracer PET imaging is getting more attention in radiotherapy by providing additional tumor volume information such as glucose and oxygenation. However, automatic PET-based tumor segmentation is still a very challenging problem. We propose a statistical fusion approach to joint segment the sub-area of tumors from the two tracers FDG and FMISO PET images. METHODS: Non-standardized Gamma distributions are convenient to model intensity distributions in PET...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28045893/a-hidden-markov-model-approach-for-simultaneously-estimating-local-ancestry-and-admixture-time-using-next-generation-sequence-data-in-samples-of-arbitrary-ploidy
#14
Russell Corbett-Detig, Rasmus Nielsen
Admixture-the mixing of genomes from divergent populations-is increasingly appreciated as a central process in evolution. To characterize and quantify patterns of admixture across the genome, a number of methods have been developed for local ancestry inference. However, existing approaches have a number of shortcomings. First, all local ancestry inference methods require some prior assumption about the expected ancestry tract lengths. Second, existing methods generally require genotypes, which is not feasible to obtain for many next-generation sequencing projects...
January 3, 2017: PLoS Genetics
https://www.readbyqxmd.com/read/28042076/longitudinal-examination-of-symptom-profiles-among-breast-cancer-survivors
#15
Nancy E Avis, Beverly Levine, Sarah A Marshall, Edward H Ip
CONTEXT: Identification of cancer patients with similar symptom profiles may facilitate targeted symptom management. OBJECTIVES: To identify subgroups of breast cancer survivors based on differential experience of symptoms, examine change in subgroup membership over time, and identify relevant characteristics and quality of life (QOL) among subgroups. METHODS: Secondary analyses of data from 653 breast cancer survivors recruited within 8 months of diagnosis who completed questionnaires at five timepoints...
December 29, 2016: Journal of Pain and Symptom Management
https://www.readbyqxmd.com/read/28040034/automatic-measurement-of-vowel-duration-via-structured-prediction
#16
Yossi Adi, Joseph Keshet, Emily Cibelli, Erin Gustafson, Cynthia Clopper, Matthew Goldrick
A key barrier to making phonetic studies scalable and replicable is the need to rely on subjective, manual annotation. To help meet this challenge, a machine learning algorithm was developed for automatic measurement of a widely used phonetic measure: vowel duration. Manually-annotated data were used to train a model that takes as input an arbitrary length segment of the acoustic signal containing a single vowel that is preceded and followed by consonants and outputs the duration of the vowel. The model is based on the structured prediction framework...
December 2016: Journal of the Acoustical Society of America
https://www.readbyqxmd.com/read/28033039/the-effects-of-probe-similarity-on-retrieval-and-comparison-processes-in-associative-recognition
#17
Qiong Zhang, Matthew M Walsh, John R Anderson
In this study, we investigated the information processing stages underlying associative recognition. We recorded EEG data while participants performed a task that involved deciding whether a probe word triple matched any previously studied triple. We varied the similarity between probes and studied triples. According to a model of associative recognition developed in the Adaptive Control of Thought-Rational cognitive architecture, probe similarity affects the duration of the retrieval stage: Retrieval is fastest when the probe is similar to a studied triple...
February 2017: Journal of Cognitive Neuroscience
https://www.readbyqxmd.com/read/28027304/decoding-single-molecule-time-traces-with-dynamic-disorder
#18
Wonseok Hwang, Il-Buem Lee, Seok-Cheol Hong, Changbong Hyeon
Single molecule time trajectories of biomolecules provide glimpses into complex folding landscapes that are difficult to visualize using conventional ensemble measurements. Recent experiments and theoretical analyses have highlighted dynamic disorder in certain classes of biomolecules, whose dynamic pattern of conformational transitions is affected by slower transition dynamics of internal state hidden in a low dimensional projection. A systematic means to analyze such data is, however, currently not well developed...
December 2016: PLoS Computational Biology
https://www.readbyqxmd.com/read/28011233/septic-shock-prediction-for-icu-patients-via-coupled-hmm-walking-on-sequential-contrast-patterns
#19
Shameek Ghosh, Jinyan Li, Longbing Cao, Kotagiri Ramamohanarao
BACKGROUND AND OBJECTIVE: Critical care patient events like sepsis or septic shock in intensive care units (ICUs) are dangerous complications which can cause multiple organ failures and eventual death. Preventive prediction of such events will allow clinicians to stage effective interventions for averting these critical complications. METHODS: It is widely understood that physiological conditions of patients on variables such as blood pressure and heart rate are suggestive to gradual changes over a certain period of time, prior to the occurrence of a septic shock...
December 20, 2016: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28009838/modeling-driver-behavior-near-intersections-in-hidden-markov-model
#20
Juan Li, Qinglian He, Hang Zhou, Yunlin Guan, Wei Dai
Intersections are one of the major locations where safety is a big concern to drivers. Inappropriate driver behaviors in response to frequent changes when approaching intersections often lead to intersection-related crashes or collisions. Thus to better understand driver behaviors at intersections, especially in the dilemma zone, a Hidden Markov Model (HMM) is utilized in this study. With the discrete data processing, the observed dynamic data of vehicles are used for the inference of the Hidden Markov Model...
December 21, 2016: International Journal of Environmental Research and Public Health
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