3,402 results match your criteria informative proposed


CCIP: Predicting CTCF-mediated chromatin loops with transitivity.

Bioinformatics 2021 Jul 20. Epub 2021 Jul 20.

Department of Computer Science, The University of British Columbia Okanagan, Kelowna, BC, V1V 1V5, Canada.

Motivation: CTCF-mediated chromatin loops underlie the formation of topological associating domains (TADs) and serve as the structural basis for transcriptional regulation. However, the formation mechanism of these loops remains unclear, and the genome-wide mapping of these loops is costly and difficult. Motivated by the recent studies on the formation mechanism of CTCF-mediated loops, we studied the possibility of making use of transitivity-related information of interacting CTCF anchors to predict CTCF loops computationally. Read More

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Harris Hawks optimisation with Simulated Annealing as a deep feature selection method for screening of COVID-19 CT-scans.

Appl Soft Comput 2021 Nov 14;111:107698. Epub 2021 Jul 14.

Department of Computer Science and Engineering, Jadavpur University, Kolkata 700032, India.

Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). It may cause severe ailments in infected individuals. The more severe cases may lead to death. Read More

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November 2021

Lipid Profiling of 20 Mammalian Cells by Capillary Microsampling Combined with High-Resolution Spectral Stitching Nanoelectrospray Ionization Direct-Infusion Mass Spectrometry.

Anal Chem 2021 Jul 16. Epub 2021 Jul 16.

CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023, China.

Studies of cellular metabolism can provide profound insights into the underlying molecular mechanisms and metabolic function. To date, the majority of cellular metabolism studies based on chromatography-mass spectrometry (MS) require population cells to obtain informative metabolome. These methods are not only time-consuming but also not suitable for amount-limited cell samples such as circulating tumor cells, stem cells, and neurons. Read More

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Validation and psychometric properties of the Brazilian-Portuguese dispositional flow scale 2 (DFS-BR).

PLoS One 2021 13;16(7):e0253044. Epub 2021 Jul 13.

Institute of Mathematics and Computer Science, University of São Paulo, São Carlos, Brazil.

Introduction: Flow state is a psychological concept used to describe the optimal engagement in different activities. Therefore, the DFS-2 has been developed as an instrument to measure an individual's dispositional tendency to flow state as a personality trait.

Objective: Aiming to obtain an adapted version of the DFS-2 for the Brazilian-Portuguese language (DFS-BR) and for general activities, we performed its forward- and backward-translation, and we validated it. Read More

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Creating idiometric short-form measures of cognitive appraisal: balancing theory and pragmatics.

J Patient Rep Outcomes 2021 Jul 13;5(1):57. Epub 2021 Jul 13.

Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA.

Background: The Rapkin and Schwartz appraisal theory and measure provided a path toward documenting response-shift effects and describing individual differences in ways of thinking about quality of life (QOL) that distinguished people in different circumstances. Recent work developed and validated the QOL Appraisal Profile (QOLAP), an 85-item measure that taps response-shift-detection domains of Frame of Reference, Standards of Comparison, Sampling of Experience, and Combinatory Algorithm. Recent theoretical work proposed that appraisal measurement constitutes a new class of measurement (idiometric), distinct from psychometric and clinimetric. Read More

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An interpretable multiple-instance approach for the detection of referable diabetic retinopathy in fundus images.

Sci Rep 2021 Jul 12;11(1):14326. Epub 2021 Jul 12.

Multimedia Understanding Group, Information Processing Laboratory, Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, Thessaloniki, Greece.

Diabetic retinopathy (DR) is one of the leading causes of vision loss across the world. Yet despite its wide prevalence, the majority of affected people lack access to the specialized ophthalmologists and equipment required for monitoring their condition. This can lead to delays in the start of treatment, thereby lowering their chances for a successful outcome. Read More

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Recurrent Events Analysis With Data Collected at Informative Clinical Visits in Electronic Health Records.

J Am Stat Assoc 2021 26;116(534):594-604. Epub 2020 Aug 26.

Department of Biostatistics, Columbia University Mailman School of Public Health, New York, NY 10032.

Although increasingly used as a data resource for assembling cohorts, electronic health records (EHRs) pose many analytic challenges. In particular, a patient's health status influences when and what data are recorded, generating sampling bias in the collected data. In this paper, we consider recurrent event analysis using EHR data. Read More

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Accurate and Fast Image Denoising via Attention Guided Scaling.

IEEE Trans Image Process 2021 12;30:6255-6265. Epub 2021 Jul 12.

Image denoising is a classical topic yet still a challenging problem, especially for reducing noise from the texture information. Feature scaling (e.g. Read More

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Optimizing the maximum reported cluster size in the spatial scan statistic for survival data.

Int J Health Geogr 2021 Jul 8;20(1):33. Epub 2021 Jul 8.

Division of Biostatistics, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, 50-1 Yonsei-ro, Seodaemun-gu, Seoul, 03722, Korea.

Background: The spatial scan statistic is a useful tool for cluster detection analysis in geographical disease surveillance. The method requires users to specify the maximum scanning window size or the maximum reported cluster size (MRCS), which is often set to 50% of the total population. It is important to optimize the maximum reported cluster size, keeping the maximum scanning window size at as large as 50% of the total population, to obtain valid and meaningful results. Read More

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A unified approach to variable selection for Cox's proportional hazards model with interval-censored failure time data.

Stat Methods Med Res 2021 Jul 7:9622802211009259. Epub 2021 Jul 7.

Department of Statistics, University of Missouri, Columbia, MO, USA.

Cox's proportional hazards model is the most commonly used model for regression analysis of failure time data and some methods have been developed for its variable selection under different situations. In this paper, we consider a general type of failure time data, case interval-censored data, that include all of other types discussed as special cases, and propose a unified penalized variable selection procedure. In addition to its generality, another significant feature of the proposed approach is that unlike all of the existing variable selection methods for failure time data, the proposed approach allows dependent censoring, which can occur quite often and could lead to biased or misleading conclusions if not taken into account. Read More

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Insight into chemical basis of traditional Chinese medicine based on the state-of-the-art techniques of liquid chromatography-mass spectrometry.

Acta Pharm Sin B 2021 Jun 26;11(6):1469-1492. Epub 2021 Feb 26.

Shanghai Research Center for Modernization of Traditional Chinese Medicine, National Engineering Laboratory for TCM Standardization Technology, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai 201203, China.

Traditional Chinese medicine (TCM) has been an indispensable source of drugs for curing various human diseases. However, the inherent chemical diversity and complexity of TCM restricted the safety and efficacy of its usage. Over the past few decades, the combination of liquid chromatography with mass spectrometry has contributed greatly to the TCM qualitative analysis. Read More

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Medical Image Fusion Based on Low-Level Features.

Comput Math Methods Med 2021 10;2021:8798003. Epub 2021 Jun 10.

College of Information Technology, Luoyang Normal University, Luoyang 471934, China.

Medical image fusion is an important technique to address the limited depth of the optical lens for a completely informative focused image. It can well improve the accuracy of diagnosis and assessment of medical problems. However, the difficulty of many traditional fusion methods in preserving all the significant features of the source images compromises the clinical accuracy of medical problems. Read More

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Genetic diversity among two native Indian chicken populations using I and DNA barcodes.

Vet World 2021 May 30;14(5):1389-1397. Epub 2021 May 30.

Department of Animal Genetics and Breeding, College of Veterinary Science and Animal Husbandry, Anand, Anand Agricultural University, Gujarat, India.

Background And Aim: India has large varieties (recognized, unrecognized) of native chickens (Desi) scattered throughout the country, managed under scavenging system different from commercial chicken breeds. However, they are less investigated for genetic diversity they harbor. The present study was planned to evaluate genetic diversity among two native chicken populations of North Gujarat (proposed Aravali breed) and South Gujarat (Ankleshwar breed). Read More

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Risk prediction in multicentre studies when there is confounding by cluster or informative cluster size.

BMC Med Res Methodol 2021 Jul 4;21(1):135. Epub 2021 Jul 4.

Department of Statistical Science, UCL, London, UK.

Background: Clustered data arise in research when patients are clustered within larger units. Generalised Estimating Equations (GEE) and Generalised Linear Models (GLMM) can be used to provide marginal and cluster-specific inference and predictions, respectively.

Methods: Confounding by Cluster (CBC) and Informative cluster size (ICS) are two complications that may arise when modelling clustered data. Read More

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New methods for the additive hazards model with the informatively interval-censored failure time data.

Biom J 2021 Jul 3. Epub 2021 Jul 3.

Department of Statistics, University of Missouri, Columbia, MO, USA.

The additive hazards model is one of the most commonly used models for regression analysis of failure time data and many inference procedures have been developed for it under various situations. In particular, Wang et al. (2018a, Computational Statistics and Data Analysis, 125, 1-9) discussed the situation where one observes informatively interval-censored data and proposed a likelihood estimation approach. Read More

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Patch-Type Vibration Visualization (PVV) Sensor System Based on Triboelectric Effect.

Sensors (Basel) 2021 Jun 9;21(12). Epub 2021 Jun 9.

Smart Structural Safety and Prognosis Research Division, Korea Atomic Energy Research Institute, 111 Daedeok-daero 989Beon-gil, Yuseong-gu, Daejeon 34057, Korea.

Self-powered wireless sensor systems have emerged as an important topic for condition monitoring in nuclear power plants. However, commercial wireless sensor systems still cannot be fully self-sustainable due to the high power consumption caused by excessive signal processing in a mini-electronic computing system. In this sense, it is essential not only to integrate the sensor system with energy-harvesting devices but also to develop simple data processing methods for low power schemes. Read More

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AI-Driven Framework for Recognition of Guava Plant Diseases through Machine Learning from DSLR Camera Sensor Based High Resolution Imagery.

Sensors (Basel) 2021 Jun 1;21(11). Epub 2021 Jun 1.

Department of Information Technology, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.

Plant diseases can cause a considerable reduction in the quality and number of agricultural products. Guava, well known to be the tropics' apple, is one significant fruit cultivated in tropical regions. It is attacked by 177 pathogens, including 167 fungal and others such as bacterial, algal, and nematodes. Read More

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An Autoencoder-Based Deep Learning Approach for Load Identification in Structural Dynamics.

Sensors (Basel) 2021 Jun 19;21(12). Epub 2021 Jun 19.

Dipartimento di Ingegneria Civile e Ambientale, Politecnico di Milano, Piazza L. da Vinci 32, 20133 Milano, Italy.

In civil engineering, different machine learning algorithms have been adopted to process the huge amount of data continuously acquired through sensor networks and solve inverse problems. Challenging issues linked to structural health monitoring or load identification are currently related to big data, consisting of structural vibration recordings shaped as a multivariate time series. Any algorithm should therefore allow an effective dimensionality reduction, retaining the informative content of data and inferring correlations within and across the time series. Read More

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Functional characterization of 105 Factor H variants associated with atypical HUS: lessons for variant classification.

Blood 2021 Jun 29. Epub 2021 Jun 29.

Centro de Investigaciones Biológicas (CSIC), Madrid, Spain.

Atypical hemolytic uremic syndrome (aHUS) is a life-threatening thrombotic microangiopathy that can progress, when untreated, to end-stage renal disease. Most frequently, aHUS is caused by complement dysregulation due to pathogenic variants in genes that encode complement components and regulators. Amongst these genes, the Factor H (FH) gene, CFH, presents with the highest frequency (15-20%) of variants and is associated with the poorest prognosis. Read More

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Web databases of feather photographs are useful tools for avian morphometry studies.

Ecol Evol 2021 Jun 2;11(12):7677-7684. Epub 2021 Jun 2.

Terrestrial Ecology Group (TEG-UAM) Departamento de Ecología Facultad de Ciencias Universidad Autónoma de Madrid Madrid Spain.

Wing area, wing loading, and aspect ratio are key variables for studies of avian comparative ecology, despite the complexity of measuring wing characteristics in living and museum specimens. The systematic databases of feather photographs available on the Internet may offer an alternative way of obtaining such morphometric data. Here, we evaluate whether measurements of scanned feathers from web photograph databases may offer reliable estimates of avian morphometry. Read More

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Regions of genetic divergence in depth-separated Sebastes rockfish species pairs: Depth as a potential driver of speciation.

Mol Ecol 2021 Jun 28. Epub 2021 Jun 28.

Department of Biology, Juniata College, Huntingdon, Pennsylvania, USA.

Depth separation is a proposed driver of speciation in marine fishes, with marine rockfish (genus Sebastes) providing a potentially informative study system. Sebastes rockfishes are commercially and ecologically important. This genus encompasses more than one hundred species and the ecological and morphological variance between these species provides opportunity for identifying speciation-driving adaptations, particularly along a depth gradient. Read More

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Next Generation Sequencing Based Multiplex Long-Range PCR for Routine Genotyping of Autoinflammatory Disorders.

Front Immunol 2021 9;12:666273. Epub 2021 Jun 9.

Department of Paediatrics, Division of Paediatric Rheumatology, Schulich School of Medicine & Dentistry, University of Western Ontario, London, ON, Canada.

Background: During the last decade, remarkable progress with massive sequencing has been made in the identification of disease-associated genes for AIDs using next-generation sequencing technologies (NGS). An international group of experts described the ideal genetic screening method which should give information about SNVs, InDels, Copy Number Variations (CNVs), GC rich regions. We aimed to develop and validate a molecular diagnostic method in conjunction with the NGS platform as an inexpensive, extended and uniform coverage and fast screening tool which consists of nine genes known to be associated with various AIDs. Read More

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A Dynamical Generative Model of Social Interactions.

Front Neurorobot 2021 9;15:648527. Epub 2021 Jun 9.

Section for Computational Sensomotorics, Department of Cognitive Neurology, Centre for Integrative Neuroscience, Hertie Institute for Clinical Brain Research, University Clinic Tübingen, Tübingen, Germany.

The ability to make accurate social inferences makes humans able to navigate and act in their social environment effortlessly. Converging evidence shows that motion is one of the most informative cues in shaping the perception of social interactions. However, the scarcity of parameterized generative models for the generation of highly-controlled stimuli has slowed down both the identification of the most critical motion features and the understanding of the computational mechanisms underlying their extraction and processing from rich visual inputs. Read More

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Assisted differential network analysis for gene expression data.

Genet Epidemiol 2021 Jun 26. Epub 2021 Jun 26.

Department of Biostatistics, Yale University, New Haven, CT, USA.

In the analysis of gene expression data, when there are two or more disease conditions/groups (e.g., diseased and normal, responder and nonresponder, and multiple stages/subtypes), differential analysis has been extensively conducted to identify key differences and has important implications. Read More

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Reliable wolf-dog hybrid detection in Europe using a reduced SNP panel developed for non-invasively collected samples.

BMC Genomics 2021 Jun 25;22(1):473. Epub 2021 Jun 25.

Conservation Genetics Group, Senckenberg Research Institute and Natural History Museum Frankfurt, Gelnhausen, Germany.

Background: Understanding the processes that lead to hybridization of wolves and dogs is of scientific and management importance, particularly over large geographical scales, as wolves can disperse great distances. However, a method to efficiently detect hybrids in routine wolf monitoring is lacking. Microsatellites offer only limited resolution due to the low number of markers showing distinctive allele frequencies between wolves and dogs. Read More

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Change point detection with multiple alternatives reveals parallel evaluation of the same stream of evidence along distinct timescales.

Sci Rep 2021 Jun 23;11(1):13098. Epub 2021 Jun 23.

Center for Neuroscience, University of California Davis, Davis, CA, USA.

In order to behave appropriately in a rapidly changing world, individuals must be able to detect when changes occur in that environment. However, at any given moment, there are a multitude of potential changes of behavioral significance that could occur. Here we investigate how knowledge about the space of possible changes affects human change point detection. Read More

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Accurate detection of COVID-19 patients based on distance biased Naïve Bayes (DBNB) classification strategy.

Pattern Recognit 2021 Nov 16;119:108110. Epub 2021 Jun 16.

Electronics and Communication Dept. faculty of engineering Mansoura University, Egypt.

COVID-19, as an infectious disease, has shocked the world and still threatens the lives of billions of people. Early detection of COVID-19 patients is an important issue for treating and controlling the disease from spreading. In this paper, a new strategy for detecting COVID-19 infected patients will be introduced, which is called Distance Biased Naïve Bayes (DBNB). Read More

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November 2021

Categorizing the characteristics of human carcinogens: a need for specificity.

Arch Toxicol 2021 Aug 20;95(8):2883-2889. Epub 2021 Jun 20.

Royal College of Physicians, London, UK.

The International Agency for Research on Cancer (IARC) has recently proposed employing "ten key characteristics of human carcinogens" (TKCs) to determine the potential of agents for harmful effects. The TKCs seem likely to confuse the unsatisfactory correlation from testing regimes that have ignored the differences evident when cellular changes are compared in short and long-lived species, with their very different stem cell and somatic cell phylogenies. The proposed characteristics are so broad that their use will lead to an increase in the current unacceptably high rate of false positives. Read More

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Multispectral co-occurrence of wavelet coefficients for malignancy assessment of brain tumors.

PLoS One 2021 17;16(6):e0250964. Epub 2021 Jun 17.

Biomedical Imaging and Bioinformatics Lab, Machine Intelligence Unit, Indian Statistical Institute, Kolkata, West Bengal, India.

Brain tumor is not most common, but truculent type of cancer. Therefore, correct prediction of its aggressiveness nature at an early stage would influence the treatment strategy. Although several diagnostic methods based on different modalities exist, a pre-operative method for determining tumor malignancy state still remains as an active research area. Read More

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Reduce Surface Electromyography Channels for Gesture Recognition by Multitask Sparse Representation and Minimum Redundancy Maximum Relevance.

J Healthc Eng 2021 27;2021:9929684. Epub 2021 May 27.

College of Electronic and Information Engineering, Shandong University of Science and Technology, Qingdao, China.

Surface electromyography- (sEMG-) based gesture recognition is widely used in rehabilitation training, artificial prosthesis, and human-computer interaction. The purpose of this study is to simplify the sEMG devices by reducing channels while achieving comparably high gesture recognition accuracy. We propose a compound channel selection scheme by combining the variable selection algorithms based on multitask sparse representation (MTSR) and minimum Redundancy Maximum Relevance (mRMR). Read More

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