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Robosample: A rigid-body molecular simulation program based on robot mechanics.

Biochimica et biophysica acta. General subjects Apr 13, 2020
BACKGROUND: Compared with all-atom molecular dynamics (MD), constrained MD methods allow for larger time steps, potentially reducing computational cost. For this reason, there has been continued interest in improving constrained MD algorithms to incr...
Monte Carlo Method Alanine Molecular Dynamics Simulation Dipeptides Software Robotics
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Deep learning for survival outcomes.

Statistics in medicine Apr 13, 2020
Deep learning is a class of machine learning algorithms that are popular for building risk prediction models. When observations are censored, the outcomes are only partially observed and standard deep learning algorithms cannot be directly applied. W...
Deep Learning Probability Survival Analysis Software Algorithms Humans Machine Learning
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FF-QuantSC: accurate quantification of fetal fraction by a neural network model.

Molecular genetics & genomic medicine Apr 13, 2020
BACKGROUND: Noninvasive prenatal testing (NIPT) is one of the most commonly employed clinical measures for screening of fetal aneuploidy. Fetal Fraction (ff) has been demonstrated to be one of the key factors affecting the performance of NIPT. Accura...
Neural Networks, Computer Software Pregnancy Humans Sensitivity and Specificity Sequence Analysis, DNA Noninvasive Prenatal Testing Female Adult
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DeLTA: Automated cell segmentation, tracking, and lineage reconstruction using deep learning.

PLoS computational biology Apr 13, 2020
Microscopy image analysis is a major bottleneck in quantification of single-cell microscopy data, typically requiring human oversight and curation, which limit both accuracy and throughput. To address this, we developed a deep learning-based image an...
Cell Tracking Escherichia coli Microscopy, Fluorescence Electronic Data Processing Lab-On-A-Chip Devices Image Processing, Computer-Assisted Software Microfluidics Computational Biology Algorithms Deep Learning Single-Cell Analysis
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PredDBP-Stack: Prediction of DNA-Binding Proteins from HMM Profiles using a Stacked Ensemble Method.

BioMed research international Apr 13, 2020
DNA-binding proteins (DBPs) play vital roles in all aspects of genetic activities. However, the identification of DBPs by using wet-lab experimental approaches is often time-consuming and laborious. In this study, we develop a novel computational met...
Software Databases, Protein Support Vector Machine DNA-Binding Proteins
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Top-down machine learning approach for high-throughput single-molecule analysis.

eLife Apr 8, 2020
Single-molecule approaches provide enormous insight into the dynamics of biomolecules, but adequately sampling distributions of states and events often requires extensive sampling. Although emerging experimental techniques can generate such large dat...
Software Fluorescent Dyes Algorithms High-Throughput Screening Assays Unsupervised Machine Learning Single Molecule Imaging
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MicrographCleaner: A python package for cryo-EM micrograph cleaning using deep learning.

Journal of structural biology Apr 7, 2020
Cryo-EM Single Particle Analysis workflows require tens of thousands of high-quality particle projections to unveil the three-dimensional structure of macromolecules. Conventional methods for automatic particle picking tend to suffer from high false-...
Deep Learning Macromolecular Substances Software Algorithms Cryoelectron Microscopy
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Multiview learning for understanding functional multiomics.

PLoS computational biology Apr 2, 2020
The molecular mechanisms and functions in complex biological systems currently remain elusive. Recent high-throughput techniques, such as next-generation sequencing, have generated a wide variety of multiomics datasets that enable the identification ...
Proteomics Cluster Analysis Data Interpretation, Statistical DNA Metabolomics Machine Learning Genomics Software Computational Biology Brain Algorithms Humans Single-Cell Analysis Chlamydomonas reinhardtii Alzheimer Disease High-Throughput Nucleotide Sequencing
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Artificial intelligence and machine learning in nephropathology.

Kidney international Apr 1, 2020
Artificial intelligence (AI) for the purpose of this review is an umbrella term for technologies emulating a nephropathologist's ability to extract information on diagnosis, prognosis, and therapy responsiveness from native or transplant kidney biops...
Neural Networks, Computer Machine Learning Software Artificial Intelligence Reproducibility of Results
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Molib: A machine learning based classification tool for the prediction of biofilm inhibitory molecules.

Genomics Mar 27, 2020
Identification of biofilm inhibitory small molecules appears promising for therapeutic intervention against biofilm-forming bacteria. However, the experimental identification of such molecules is a time-consuming task, and thus, the computational app...
Anti-Bacterial Agents Machine Learning Biofilms Software Principal Component Analysis
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