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Rapid Reconstruction of Time-varying Gene Regulatory Networks with Limited Main Memory.

IEEE/ACM transactions on computational biology and bioinformatics Aug 6, 2021
Reconstruction of time-varying gene regulatory networks underlying a time-series gene expression data is a fundamental challenge in the computational systems biology. The challenge increases multi-fold if the target networks need to be constructed fo...
Models, Statistical Bayes Theorem Machine Learning Algorithms Computational Biology Databases, Genetic Time Factors Gene Regulatory Networks
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Hybrid Machine Learning Models for Predicting Types of Human T-cell Lymphotropic Virus.

IEEE/ACM transactions on computational biology and bioinformatics Aug 6, 2021
Life threatening diseases like adult T-cell leukemia, neurodegenerative diseases, and demyelinating diseases such as HTLV-1 based myelopathy/tropical spastic paraparesis (HAM/TSP), hypocalcaemia, and bone lesions are caused by a group of human retrov...
Viral Proteins HTLV-I Infections Human T-lymphotropic virus 1 Machine Learning Algorithms Computational Biology Models, Statistical Humans
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Using normative modelling to detect disease progression in mild cognitive impairment and Alzheimer's disease in a cross-sectional multi-cohort study.

Scientific reports Aug 3, 2021
Normative modelling is an emerging method for quantifying how individuals deviate from the healthy populational pattern. Several machine learning models have been implemented to develop normative models to investigate brain disorders, including regre...
Humans Neuroimaging Middle Aged Disease Progression Case-Control Studies Female Models, Statistical Cognitive Dysfunction Neural Networks, Computer Aged Cross-Sectional Studies Alzheimer Disease Cohort Studies Male Machine Learning Brain
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Utilizing deep neural networks and electroencephalogram for objective evaluation of surgeon's distraction during robot-assisted surgery.

Brain research Aug 2, 2021
OBJECTIVE: To develop an algorithm for objective evaluation of distraction of surgeons during robot-assisted surgery (RAS).
Male Surgeons Middle Aged Deep Learning Reproducibility of Results Adult Students, Medical Robotic Surgical Procedures Psychomotor Performance General Surgery Clinical Competence Models, Statistical Electroencephalography Algorithms Female Humans Neural Networks, Computer
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Editorial: The National COVID Cohort Collaborative Consortium Combines Population Data with Machine Learning to Evaluate and Predict Risk Factors for the Severity of COVID-19.

Medical science monitor : international medical journal of experimental and clinical research Aug 2, 2021
Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19) commonly presents with pneumonia. However, COVID-19 is now recognized to involve multiple organ systems with varying severity ...
COVID-19 Female SARS-CoV-2 Risk Factors Severity of Illness Index Diagnosis, Computer-Assisted Humans Models, Statistical Adult Population Health Machine Learning Male Middle Aged
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Predicting mutant outcome by combining deep mutational scanning and machine learning.

Proteins Jul 31, 2021
Deep mutational scanning provides unprecedented wealth of quantitative data regarding the functional outcome of mutations in proteins. A single experiment may measure properties (eg, structural stability) of numerous protein variants. Leveraging the ...
Algorithms DNA Mutational Analysis Protein Interaction Maps Machine Learning Computational Biology Proteins Models, Statistical Mutation High-Throughput Nucleotide Sequencing
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Discovery of Parkinson's disease states and disease progression modelling: a longitudinal data study using machine learning.

The Lancet. Digital health Jul 29, 2021
BACKGROUND: Parkinson's disease is heterogeneous in symptom presentation and progression. Increased understanding of both aspects can enable better patient management and improve clinical trial design. Previous approaches to modelling Parkinson's dis...
Biological Variation, Population Female Humans Aged Machine Learning Longitudinal Studies Models, Statistical Male Middle Aged Parkinson Disease Biological Variation, Individual Dopamine Agents Disease Progression
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Interrogating theoretical models of neural computation with emergent property inference.

eLife Jul 29, 2021
A cornerstone of theoretical neuroscience is the circuit model: a system of equations that captures a hypothesized neural mechanism. Such models are valuable when they give rise to an experimentally observed phenomenon -- whether behavioral or a patt...
Neural Networks, Computer Models, Statistical Computational Biology Visual Cortex Models, Neurological
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Machine learning methods for imbalanced data set for prediction of faecal contamination in beach waters.

Water research Jul 23, 2021
Predicting water contamination by statistical models is a useful tool to manage health risk in recreational beaches. Extreme contamination events, i.e. those exceeding normative are generally rare with respect to bathing conditions and thus the data ...
Models, Statistical Machine Learning Algorithms Support Vector Machine
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PEDF, a pleiotropic WTC-LI biomarker: Machine learning biomarker identification and validation.

PLoS computational biology Jul 21, 2021
Biomarkers predict World Trade Center-Lung Injury (WTC-LI); however, there remains unaddressed multicollinearity in our serum cytokines, chemokines, and high-throughput platform datasets used to phenotype WTC-disease. To address this concern, we used...
Reproducibility of Results Adult Sensitivity and Specificity Longitudinal Studies Models, Statistical Male Middle Aged Humans Machine Learning September 11 Terrorist Attacks Biomarkers Occupational Diseases Eye Proteins Firefighters Serpins Inhalation Exposure Lung Injury Nerve Growth Factors
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