AIMC Topic: Phenotype

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Unsupervised discovery of dynamic cell phenotypic states from transmitted light movies.

PLoS computational biology Dec 30, 2021
Identification of cell phenotypic states within heterogeneous populations, along with elucidation of their switching dynamics, is a central challenge in modern biology. Conventional single-cell analysis methods typically provide only indirect, static...
Algorithms Phenotype Leukemia, Myeloid, Acute Humans Blood Cells Time-Lapse Imaging Unsupervised Machine Learning Light Single-Cell Analysis Microscopy Image Processing, Computer-Assisted
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Deep learning radiomics model related with genomics phenotypes for lymph node metastasis prediction in colorectal cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Dec 27, 2021
BACKGROUND AND PURPOSE: The preoperative lymph node (LN) status is important for the treatment of colorectal cancer (CRC). Here, we established and validated a deep learning (DPL) model for predicting lymph node metastasis (LNM) in CRC.
Deep Learning Genomics Lymph Nodes Retrospective Studies Colorectal Neoplasms Lymphatic Metastasis Humans Phenotype
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I, DOCTOR: The role of machine learning in phenotyping ARDS.

EBioMedicine Dec 17, 2021
Machine Learning Phenotype Respiratory Distress Syndrome Humans
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The mining and construction of a knowledge base for gene-disease association in mitochondrial diseases.

Scientific reports Dec 13, 2021
Mitochondrial diseases are a group of heterogeneous genetic metabolic diseases caused by mitochondrial DNA (mtDNA) or nuclear DNA (nDNA) gene mutations. Mining the gene-disease association of mitochondrial diseases is helpful for understanding the pa...
Phenotype Genetic Predisposition to Disease Polymorphism, Single Nucleotide Humans Knowledge Bases Databases, Genetic Genetic Loci Data Mining Mitochondrial Diseases
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Prediction of the importance of auxiliary traits using computational intelligence and machine learning: A simulation study.

PloS one Nov 29, 2021
The present study evaluated the importance of auxiliary traits of a principal trait based on phenotypic information and previously known genetic structure using computational intelligence and machine learning to develop predictive tools for plant bre...
Genotype Phenotype Artificial Intelligence Genetic Linkage Quantitative Trait Loci Plant Breeding Computer Simulation Machine Learning
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Cell-morphodynamic phenotype classification with application to cancer metastasis using cell magnetorotation and machine-learning.

PloS one Nov 17, 2021
We define cell morphodynamics as the cell's time dependent morphology. It could be called the cell's shape shifting ability. To measure it we use a biomarker free, dynamic histology method, which is based on multiplexed Cell Magneto-Rotation and Mach...
Cell Line, Tumor Epithelial-Mesenchymal Transition Humans Neoplasm Metastasis Cell Shape Machine Learning Phenotype
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StomataScorer: a portable and high-throughput leaf stomata trait scorer combined with deep learning and an improved CV model.

Plant biotechnology journal Nov 12, 2021
To measure stomatal traits automatically and nondestructively, a new method for detecting stomata and extracting stomatal traits was proposed. Two portable microscopes with different resolutions (TipScope with a 40× lens attached to a smartphone and ...
Plant Leaves Droughts Plant Stomata Phenotype Deep Learning
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A robust and stable gene selection algorithm based on graph theory and machine learning.

Human genomics Nov 9, 2021
BACKGROUND: Nowadays we are observing an explosion of gene expression data with phenotypes. It enables us to accurately identify genes responsible for certain medical condition as well as classify them for drug target. Like any other phenotype data i...
Algorithms Machine Learning Phenotype Oligonucleotide Array Sequence Analysis
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Deep learning is widely applicable to phenotyping embryonic development and disease.

Development (Cambridge, England) Nov 5, 2021
Genome editing simplifies the generation of new animal models for congenital disorders. However, the detailed and unbiased phenotypic assessment of altered embryonic development remains a challenge. Here, we explore how deep learning (U-Net) can auto...
Mice Disease Models, Animal Microscopy Embryonic Development Mutation Animals Deep Learning Polycystic Kidney Diseases Image Processing, Computer-Assisted Neurodevelopmental Disorders Neural Networks, Computer Craniofacial Abnormalities Xenopus laevis Phenotype Xenopus Proteins
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Identifying clinical phenotypes in extremely low birth weight infants-an unsupervised machine learning approach.

European journal of pediatrics Nov 3, 2021
There is increasing evidence that patient heterogeneity significantly hinders advancement in clinical trials and individualized care. This study aimed to identify distinct phenotypes in extremely low birth weight infants. We performed an agglomerativ...
Infant, Extremely Low Birth Weight Humans Birth Weight Gestational Age Phenotype Infant, Extremely Premature Infant, Newborn Unsupervised Machine Learning
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