17,538 results match your criteria allows classify

MAPS: machine-assisted phenotype scoring enables rapid functional assessment of genetic variants by high-content microscopy.

BMC Bioinformatics 2021 Apr 20;22(1):202. Epub 2021 Apr 20.

Department of Cellular and Physiological Sciences, Life Sciences Institute, University of British Columbia, Vancouver, V6T1Z3, Canada.

Background: Genetic testing is widely used in evaluating a patient's predisposition to hereditary diseases. In the case of cancer, when a functionally impactful mutation (i.e. Read More

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A Unified Framework for Personalized Regions Selection and Functional Relation Modeling for Early MCI Identification.

Neuroimage 2021 Apr 17:118048. Epub 2021 Apr 17.

Department of Brain and Cognitive Engineering, Korea University, Republic of Korea; Department of Artificial Intelligence, Korea University, Republic of Korea. Electronic address:

Resting-state functional magnetic resonance imaging (rs-fMRI) has been widely adopted to investigate functional abnormalities in brain diseases. Rs-fMRI data is unsupervised in nature because the psychological and neurological labels are coarse-grained, and no accurate region-wise label is provided along with the complex co-activities of multiple regions. To the best of our knowledge, most studies regarding univariate group analysis or multivariate pattern recognition for brain disease identification have focused on discovering functional characteristics shared across subjects; however, they have paid less attention to individual properties of neural activities that result from different symptoms or degrees of abnormality. Read More

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CiwGAN and fiwGAN: Encoding information in acoustic data to model lexical learning with Generative Adversarial Networks.

Gašper Beguš

Neural Netw 2021 Mar 19;139:305-325. Epub 2021 Mar 19.

Department of Linguistics, University of California, Berkeley, United States of America. Electronic address:

How can deep neural networks encode information that corresponds to words in human speech into raw acoustic data? This paper proposes two neural network architectures for modeling unsupervised lexical learning from raw acoustic inputs: ciwGAN (Categorical InfoWaveGAN) and fiwGAN (Featural InfoWaveGAN). These combine Deep Convolutional GAN architecture for audio data (WaveGAN; Donahue et al., 2019) with the information theoretic extension of GAN - InfoGAN (Chen et al. Read More

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Genotyping atypical porcine pestivirus using NS5a.

Infect Genet Evol 2021 Apr 16:104866. Epub 2021 Apr 16.

Veterinary Diagnostic Laboratory and Department of Veterinary Clinical Medicine, College of Veterinary Medicine, University of Illinois, Urbana, IL, USA. Electronic address:

Atypical porcine pestivirus (APPV) is an emerging virus discovered in 2014 and it can cause congenital tremors in pigs. Molecular epidemiology serves as an essential tool in monitoring and controlling the disease. Virus epidemiology mainly relies on genome sequencing and phylogenetic characterization. Read More

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DeepGCNs: Making GCNs Go as Deep as CNNs.

IEEE Trans Pattern Anal Mach Intell 2021 Apr 19;PP. Epub 2021 Apr 19.

Convolutional Neural Networks have been very successful at solving a variety of computer vision tasks such as object classification and detection, semantic segmentation, activity understanding, to name just a few. One key enabling factor for their great performance has been the ability to train very deep networks. Despite their huge success in many tasks, CNNs do not work well with non-Euclidean data, which is prevalent in many real-world applications. Read More

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Classification of endonasal HHT lesions using digital microscopy.

Orphanet J Rare Dis 2021 Apr 17;16(1):182. Epub 2021 Apr 17.

Department of Otorhinolaryngology, Head and Neck Surgery, University Hospital, LMU Munich, Marchioninistrasse 15, 81377, Munich, Germany.

Background: Recurrent spontaneous epistaxis is the most common clinical manifestation and the most debilitating symptom in hereditary haemorrhagic telangiectasia (HHT) patients. To this date, there exist only a classification of HHT patients by different genetic mutations. There is no standard classification for the mucocutaneous endonasal manifestations of HHT. Read More

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Predicting offenses among individuals with psychiatric disorders - A machine learning approach.

J Psychiatr Res 2021 Mar 29;138:146-154. Epub 2021 Mar 29.

Department of Psychiatry and Behavioral Neurosciences, McMaster University, Hamilton, Canada; Neuroscience Graduate Program, McMaster University, Hamilton, Canada; Instituto Nacional de Ciência e Tecnologia Translacional em Medicina (INCT-TM), Porto Alegre, Brazil. Electronic address:

Background: Actuarial risk estimates are considered the gold-standard way to assess whether psychiatric patients are likely to commit prospective criminal offenses. However, these risk estimates cannot individually predict the type of criminal offense a patient will subsequently commit, and often simply assess the general likelihood of crime occurring in a group sample. In order to advance the predictive utility of risk assessments, better statistical strategies are required. Read More

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A considerable proportion of metabolic syndrome-free adults from Bratislava-region, Slovakia, display an increased cardiometabolic burden.

Can J Physiol Pharmacol 2021 Apr 14. Epub 2021 Apr 14.

Comenius University in Bratislava Faculty of Medicine, 59063, Institute of Molecular Biomedicine Sasinkova 4, Bratislava, Slovakia;

Although the dichotomous classification of metabolic syndrome (MS) enables the classification of individuals as MS-free or presenting MS, it is inconvenient for assessing cardiometabolic risk in MS-free ones. Continuous MS score allows for estimation of cardiometabolic burden even in MS-free subjects. We used the scores to estimate the proportion of MS-free subjects on high cardiometabolic risk. Read More

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Transcription factor immunohistochemistry in the diagnosis of pituitary tumours.

Eur J Endocrinol 2021 Apr 1. Epub 2021 Apr 1.

A McCormack, Department of Endocrinology, St Vincent's Hospital Sydney, Darlinghurst, Australia.

Objective: The clinical utility and prognostic value of WHO 2017 lineage-based classification of pituitary tumours have not been assessed. This study aimed to (1) determine the clinical utility of transcription factor analysis for classification of pituitary tumours and (2) determine the prognostic value of improved lineage-based classification of pituitary tumours.

Methods: This was a retrospective evaluation of patients who underwent surgical resection of pituitary tumours at St Vincent's Public and Private Hospitals, Sydney, Australia between 1990 and 2016. Read More

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Auditory stimulus-response modeling with a Match-Mismatch task.

J Neural Eng 2021 Apr 13. Epub 2021 Apr 13.

Danish Research Centre for Magnetic Resonance, Centre for Functional and Diagnostic Imaging and Research, Copenhagen University Hospital, Kettegard Allé 30, Hvidovre, DK-2650, DENMARK.

An auditory stimulus can be related to the brain response that it evokes by a stimulus-response model fit to the data. This offers insight into perceptual processes within the brain and is also of potential use for devices such as Brain Computer Interfaces (BCI). The quality of the model can be quantified by measuring the fit with a regression problem, or by applying it to a classification task and measuring its performance. Read More

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Urology 2021 Apr 10. Epub 2021 Apr 10.

Fundació Puigvert, Barcelona, Spain. Electronic address:

Objective: To assess both the safety and efficacy, in terms of symptomatic improvement, of botulinum toxin injections distributed in the bowel patch and the bladder remnant of failed augmented bladders.

Materials And Methods: A retrospective study was performed on patients with augmented bladders who had presented with clinical and/or urodynamic failure and had received an onabotulinum toxin-A injection at both the bowel and the bladder level due to refractoriness to oral treatment. The primary variable tested was safety, which was assessed by analysing the adverse effects according to the Clavien-Dindo classification. Read More

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ThermoScan: Semi-automatic Identification of Protein Stability Data From PubMed.

Front Mol Biosci 2021 25;8:620475. Epub 2021 Mar 25.

Department of Pharmacy and Biotechnology (FaBiT), University of Bologna, Bologna, Italy.

During the last years, the increasing number of DNA sequencing and protein mutagenesis studies has generated a large amount of variation data published in the biomedical literature. The collection of such data has been essential for the development and assessment of tools predicting the impact of protein variants at functional and structural levels. Nevertheless, the collection of manually curated data from literature is a highly time consuming and costly process that requires domain experts. Read More

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Identification and Development of Subtypes With Poor Prognosis in Pan-Gynecological Cancer Based on Gene Expression in the Glycolysis-Cholesterol Synthesis Axis.

Front Oncol 2021 24;11:636565. Epub 2021 Mar 24.

Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China.

Metabolic reprogramming is an important biomarker of cancer. Metabolic adaptation driven by oncogenes allows tumor cells to survive and grow in a complex tumor microenvironment. The heterogeneity of tumor metabolism is related to survival time, somatic cell-driven gene mutations, and tumor subtypes. Read More

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What Every Neuropathologist Needs to Know: Practical Aspects and Pitfalls in Molecular Diagnosis of Brain Tumors.

J Neuropathol Exp Neurol 2021 Apr;80(5):415-418

Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA.

Molecular testing has become part of the routine diagnostic workup of brain tumors after the implementation of integrated histomolecular diagnoses in the 2016 WHO classification update. It is important for every neuropathologist to be aware of practical preanalytical, analytical, and postanalytical factors that impact the performance and interpretation of molecular tests. Prior to testing, optimizing tumor purity and tumor amount increases the ability of the molecular test to detect the genetic alteration of interest. Read More

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The Histogenetic Model of Melanoma in the Modern Era of Personalized Medicine.

Acta Dermatovenerol Croat 2020 Dec;28(7):236-237

Prof. Luca Roncati, MD, DMLS, PhD , Polyclinic Hospital, Largo del Pozzo 71 - 41124 , Modena (MO), Italy;

Malignant melanoma (M) can be defined, quite simply, as a malignant neoplasm derived from melanocytes; however, there is great histological and, consequently, clinical variability from case to case (1). In order to try to overcome this intrinsic difficulty, various classification systems have been proposed over the years; as part of this effort, the World Health Organization (WHO) introduced its famous classification about half a century ago (2). Currently, the International Classification of Diseases for Oncology (ICD-O), provided by the WHO International Agency for Research on Cancer (IARC), distinguishes the in situ forms from invasive ones, recognizing four main morphological subtypes: nodular M, superficial spreading M, lentigo maligna M, and acral lentiginous M (3). Read More

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December 2020

DisBalance: a platform to automatically build balance-based disease prediction models and discover microbial biomarkers from microbiome data.

Brief Bioinform 2021 Apr 8. Epub 2021 Apr 8.

Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China.

How best to utilize the microbial taxonomic abundances in regard to the prediction and explanation of human diseases remains appealing and challenging, and the relative nature of microbiome data necessitates a proper feature selection method to resolve the compositional problem. In this study, we developed an all-in-one platform to address a series of issues in microbiome-based human disease prediction and taxonomic biomarkers discovery. We prioritize the interpretation, runtime and classification accuracy of the distal discriminative balances analysis (DBA-distal) method in selecting a set of distal discriminative balances, and develop DisBalance, a comprehensive platform, to integrate and streamline the workflows of disease model building, disease risk prediction and disease-related biomarker discovery for microbiome-based binary classifications. Read More

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On the structural formula of smectites: a review and new data on the influence of exchangeable cations.

J Appl Crystallogr 2021 Feb 1;54(Pt 1):251-262. Epub 2021 Feb 1.

Department of Geology, University of Salamanca, Plaza de la Merced s/n, Salamanca 37008, Spain.

The understanding of the structural formula of smectite minerals is basic to predicting their physicochemical properties, which depend on the location of the cation substitutions within their 2:1 layer. This implies knowing the correct distribution and structural positions of the cations, which allows assigning the source of the layer charge of the tetrahedral or octahedral sheet, determining the total number of octahedral cations and, consequently, knowing the type of smectite. However, sometimes the structural formula obtained is not accurate. Read More

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February 2021

Improving patient identification for advanced cardiac imaging through machine learning-integration of clinical and coronary CT angiography data.

Int J Cardiol 2021 Apr 5. Epub 2021 Apr 5.

Department of Cardiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, 9700RB Groningen, the Netherlands; Turku PET Centre, University of Turku and Turku University Hospital, Kiinamyllynkatu 4-8, 20520 Turku, Finland; Department of Cardiology, Hart and Lung Division, University Medical Centre Utrecht, Heidelberglaan 100, 3508, GA, Utrecht, the Netherlands. Electronic address:

Background: Standard computed tomography angiography (CTA) outputs a myriad of interrelated variables in the evaluation of suspected coronary artery disease (CAD). But an important proportion of obstructive lesions does not cause significant myocardial ischemia. Nowadays, machine learning (ML) allows integration of numerous variables through complex interdependencies that optimize classification and prediction at the individual level. Read More

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Microsaccades: Empirical Research and Methodological Advances - Introduction to Part 1 of the Thematic Special Issue.

J Eye Mov Res 2020 Jun 19;12(6). Epub 2020 Jun 19.

University of Bern and SciAns GmbH, Iffwil, Switzerland.

Recent technical developments and increased affordability of high-speed eye tracking devices have brought microsaccades to the forefront of research in many areas of sensory, perceptual, and cognitive processes. The present thematic issue on "Microsaccades: Empirical Research and Methodological Advances" invited authors to submit original research and reviews encompassing measurements and data analyses in fundamental, translational, and applied studies. We present the first volume of this special issue, comprising 14 articles by research teams around the world. Read More

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Assessing the potential for deep learning and computer vision to identify bumble bee species from images.

Sci Rep 2021 Apr 7;11(1):7580. Epub 2021 Apr 7.

Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS, USA.

Pollinators are undergoing a global decline. Although vital to pollinator conservation and ecological research, species-level identification is expensive, time consuming, and requires specialized taxonomic training. However, deep learning and computer vision are providing ways to open this methodological bottleneck through automated identification from images. Read More

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EzMAP: Easy Microbiome Analysis Platform.

BMC Bioinformatics 2021 Apr 7;22(1):179. Epub 2021 Apr 7.

Department of Biotechnology, Yeungnam University, Gyeongsan, 38541, Gyeongbuk, Korea.

Background: The rapid advances in next-generation sequencing technologies have revolutionized the microbiome research by greatly increasing our ability to understand diversity of microbes in a given sample. Over the past decade, several computational pipelines have been developed to efficiently process and annotate these microbiome data. However, most of these pipelines require an implementation of additional tools for downstream analyses as well as advanced programming skills. Read More

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Distinct SARS-CoV-2 antibody reactivity patterns in coronavirus convalescent plasma revealed by a coronavirus antigen microarray.

Sci Rep 2021 04 6;11(1):7554. Epub 2021 Apr 6.

Vaccine Research and Development Center, Department of Physiology and Biophysics, School of Medicine, University of California, Irvine, CA, USA.

A coronavirus antigen microarray (COVAM) was constructed containing 11 SARS-CoV-2, 5 SARS-1, 5 MERS, and 12 seasonal coronavirus recombinant proteins. The array is designed to measure immunoglobulin isotype and subtype levels in serum or plasma samples against each of the individual antigens printed on the array. We probed the COVAM with COVID-19 convalescent plasma (CCP) collected from 99 donors who recovered from a PCR+ confirmed SARS-CoV-2 infection. Read More

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Deep artificial neural network based on environmental sound data for the generation of a children activity classification model.

PeerJ Comput Sci 2020 9;6:e308. Epub 2020 Nov 9.

Unidad Académica de Ingeniería Eléctrica, Universidad Autónoma de Zacatecas, Zacatecas, Zacatecas, México.

Children activity recognition (CAR) is a subject for which numerous works have been developed in recent years, most of them focused on monitoring and safety. Commonly, these works use as data source different types of sensors that can interfere with the natural behavior of children, since these sensors are embedded in their clothes. This article proposes the use of environmental sound data for the creation of a children activity classification model, through the development of a deep artificial neural network (ANN). Read More

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November 2020

Enhancement of conformational B-cell epitope prediction using CluSMOTE.

PeerJ Comput Sci 2020 1;6:e275. Epub 2020 Jun 1.

Department of Computer Science and Electronics, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Yogyakarta, Indonesia.

Background: A conformational B-cell epitope is one of the main components of vaccine design. It contains separate segments in its sequence, which are spatially close in the antigen chain. The availability of Ag-Ab complex data on the Protein Data Bank allows for the development predictive methods. Read More

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A comparative study of machine learning and deep learning algorithms to classify cancer types based on microarray gene expression data.

PeerJ Comput Sci 2020 13;6:e270. Epub 2020 Apr 13.

Department of Physics and Mathematics, Universidad Autónoma de Manizales, Manizales, Caldas, Colombia.

Cancer classification is a topic of major interest in medicine since it allows accurate and efficient diagnosis and facilitates a successful outcome in medical treatments. Previous studies have classified human tumors using a large-scale RNA profiling and supervised Machine Learning (ML) algorithms to construct a molecular-based classification of carcinoma cells from breast, bladder, adenocarcinoma, colorectal, gastro esophagus, kidney, liver, lung, ovarian, pancreas, and prostate tumors. These datasets are collectively known as the 11_tumor database, although this database has been used in several works in the ML field, no comparative studies of different algorithms can be found in the literature. Read More

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Combining Multicolor FISH with Fluorescence Lifetime Imaging for Chromosomal Identification and Chromosomal Sub Structure Investigation.

Front Mol Biosci 2021 17;8:631774. Epub 2021 Mar 17.

Central Laser Facility, Science and Technology Facilities Council, Rutherford Appleton Laboratory, Oxon, United Kingdom.

Understanding the structure of chromatin in chromosomes during normal and diseased state of cells is still one of the key challenges in structural biology. Using DAPI staining alone together with Fluorescence lifetime imaging (FLIM), the environment of chromatin in chromosomes can be explored. Fluorescence lifetime can be used to probe the environment of a fluorophore such as energy transfer, pH and viscosity. Read More

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Modeling and Bioinformatics Identify Responders to G-CSF in Patients With Amyotrophic Lateral Sclerosis.

Front Neurol 2021 18;12:616289. Epub 2021 Mar 18.

Department of Neurology, University Hospital Regensburg, Regensburg, Germany.

Developing an integrative approach to early treatment response classification using survival modeling and bioinformatics with various biomarkers for early assessment of filgrastim (granulocyte colony stimulating factor) treatment effects in amyotrophic lateral sclerosis (ALS) patients. Filgrastim, a hematopoietic growth factor with excellent safety, routinely applied in oncology and stem cell mobilization, had shown preliminary efficacy in ALS. We conducted individualized long-term filgrastim treatment in 36 ALS patients. Read More

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Two-community noisy Kuramoto model with general interaction strengths. II.

Chaos 2021 Mar;31(3):033116

Amsterdam Business School, University of Amsterdam, P.O. Box 15953, 1001 NL Amsterdam, The Netherlands.

We generalize the study of the noisy Kuramoto model, considered on a network of two interacting communities, to the case where the interaction strengths within and across communities are taken to be different in general. Using a geometric interpretation of the self-consistency equations developed in Paper I of this series as well as perturbation arguments, we are able to identify all solution boundaries in the phase diagram. This allows us to completely classify the phase diagram in the four-dimensional parameter space and identify all possible bifurcation points. Read More

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PharmaKU: A Web-Based Tool Aimed at Improving Outreach and Clinical Utility of Pharmacogenomics.

J Pers Med 2021 Mar 16;11(3). Epub 2021 Mar 16.

Genetics & Bioinformatics, Dasman Diabetes Institute, 15462 Dasman, Kuwait.

With the tremendous advancements in genome sequencing technology in the field of pharmacogenomics, data have to be made accessible to be more efficiently utilized by broader clinical disciplines. Physicians who require the drug-genome interactome information, have been challenged by the complicated pharmacogenomic star-based classification system. We present here an end-to-end web-based pharmacogenomics tool, PharmaKU, which has a comprehensive easy-to-use interface. Read More

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gcProfileMakeR: An R Package for Automatic Classification of Constitutive and Non-Constitutive Metabolites.

Metabolites 2021 Mar 31;11(4). Epub 2021 Mar 31.

Genética Molecular, Instituto de Biotecnología Vegetal, Edificio I+D+I, Plaza del Hospital s/n, Universidad Politécnica de Cartagena, 30202 Cartagena, Spain.

Metabolomes comprise constitutive and non-constitutive metabolites produced due to physiological, genetic or environmental effects. However, finding constitutive metabolites and non-constitutive metabolites in large datasets is technically challenging. We developed gcProfileMakeR, an R package using standard Excel output files from an Agilent Chemstation GC-MS for automatic data analysis using CAS numbers. Read More

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