Výsledky vyhledávání - Autoencoder-based phenotypic

Multi-Omics Data Integration for Improved Cancer Subtyping via Denoising Autoencoder-Based Multi-Kernel Learning.

Autoři: Yao, Xiukun Wang, Tong Yang, Qi a další

Zdroj: Genes; Nov2025, Vol. 16 Issue 11, p1246, 24p

Témata: MULTIOMICS, DATA integration, AUTOENCODERS, ENSEMBLE learning, BIOMARKERS, INDIVIDUALIZED medicine, SURVIVAL analysis (Biometry), TUMOR classification

Phenotypic screening and genetic insights for predicting major vascular-related diseases using retinal imaging.

Autoři: Lu, Menglin Mao, Yiheng Zhu, Hui a další

Zdroj: NPJ Digital Medicine; 7/14/2025, Vol. 8 Issue 1, p1-16, 16p

Témata: VASCULAR disease diagnosis, RETINA abnormalities, RISK assessment, MYOCARDIAL infarction, RESEARCH funding, OPTICAL coherence tomography, MENDELIAN randomization, QUANTITATIVE research, DESCRIPTIVE statistics, GENETIC risk score, CHRONIC kidney failure, RETINA, MEDICAL screening, ATTRIBUTION (Social psychology), STROKE, DATA analysis software, VASCULAR diseases, PHENOTYPES, DISEASE risk factors

Korporace: UK Biobank Ltd.

Anomaly detection for high-content image-based phenotypic cell profiling

Autoři: Alon Shpigler Naor Kolet Shahar Golan a další

Zdroj: bioRxiv

Témata: Article

Přístupová URL adresa: https://pubmed.ncbi.nlm.nih.gov/38895267

A machine learning approach for predicting familial and sporadic disease cases based on clinical symptoms: introduction of a new dataset.

Alternate Title: Klinik belirtilere dayalı ailesel ve sporadik hastalık vakalarını tahmin etmek için bir makine öğrenimi yaklaşımı: yeni bir veri kümesinin tanıtımı. (Turkish)

Autoři: SHARAFI, Parisa ARSLAN, Hilal ERSOY EVANS, Sibel a další

Zdroj: Turkish Bulletin of Hygiene & Experimental Biology / Türk Hijyen ve Deneysel Biyoloji; 2025, Vol. 82 Issue 1, p99-106, 8p

Témata: MACHINE learning, ARTIFICIAL neural networks, SUPPORT vector machines, NEUROFIBROMATOSIS 1, PHENOTYPIC plasticity

Automated Honey Bee Subspecies Identification Using Advanced Wing Venation Analysis and Adaptive Hierarchical Clustering.

Autoři: Dadgostar, Shahram Mobini Dehkordi, Parsa Khodarahmi, Saman a další

Zdroj: Ecology & Evolution (20457758); Sep2025, Vol. 15 Issue 9, p1-16, 16p

Témata: SUBSPECIES, IMAGE processing, MORPHOMETRICS, CLUSTER analysis (Statistics), HONEYBEES, POLLINATION, BIODIVERSITY conservation

Anomaly detection for high-content image-based phenotypic cell profiling.

Autoři: Shpigler, Alon Kolet, Naor Golan, Shahar a další

Zdroj: Cell Syst ; ISSN:2405-4720

Témata: anomaly detection, explainability, high-content image-based cell profiling

Relation: https://doi.org/10.1016/j.cels.2025.101429; https://pubmed.ncbi.nlm.nih.gov/41167192

Dostupnost: https://doi.org/10.1016/j.cels.2025.101429
https://pubmed.ncbi.nlm.nih.gov/41167192

Deep Sparse Autoencoder-based Feature Selection for SNPs validation in Prostate Cancer Radiogenomics

Autoři: M. C. Massi F. Ieva A. Paganoni a další

Témata: Deep Learning, Feature selection, Radiogenomics, Autoencoder, SNPs

Popis souboru: application/pdf

Přístupová URL adresa: https://hdl.handle.net/11311/1150035

CopyVAE: a variational autoencoder-based approach for copy number variation inference using single-cell transcriptomics.

Autoři: Kurt, Semih Chen, Mandi Toosi, Hosein a další

Zdroj: Bioinformatics; May2024, Vol. 40 Issue 5, p1-9, 9p

Témata: TRANSCRIPTOMES, RNA sequencing, DEEP learning, CANCER invasiveness, SENSITIVITY & specificity (Statistics)

Korporace: MASSACHUSETTS Institute of Technology

Technical and legal aspects of federated learning in bioinformatics: applications, challenges and opportunities.

Autoři: Malpetti, Daniele Scutari, Marco Gualdi, Francesco a další

Zdroj: Frontiers in Digital Health; 2025, p1-17, 17p

Témata: FEDERATED learning, GENOME-wide association studies, MULTIOMICS, PRIVACY, BIOINFORMATICS, PROTEOMICS, MASS spectrometry, MEDICAL ethics, GENOTYPES, PHENOTYPES

Geografický termín: UNITED States, SWITZERLAND, UNITED Kingdom, NETHERLANDS

Korporace: UK Biobank Ltd.

A Deep Autoencoder Compression-Based Genomic Prediction Method for Whole-Genome Sequencing Data.

Autoři: Song, Hailiang Dong, Tian Wang, Wei a další

Zdroj: Biology (2079-7737); Nov2025, Vol. 14 Issue 11, p1622, 17p

Témata: WHOLE genome sequencing, AUTOENCODERS, ANIMAL breeding, OPTIMIZATION algorithms, DATA compression, DATA structures, ARTIFICIAL intelligence

Enhancing yield prediction from plot-level satellite imagery through genotype and environment feature disentanglement.

Autoři: Powadi, Anirudha A. Jubery, Talukder Z. Tross, Michael a další

Zdroj: Frontiers in Plant Science; 2025, p1-16, 16p

Témata: GENOTYPES, DEEP learning, FEATURE extraction, PLANT breeding, REMOTE-sensing images, HUMAN ecology, PRECISION farming, AGRICULTURAL forecasts

ODBAE: a high-performance model identifying complex phenotypes in high-dimensional biological datasets.

Autoři: Shen, Yafei Zhang, Tao Liu, Zhiwei a další

Zdroj: Communications Biology; 10/2/2025, Vol. 8 Issue 1, p1-19, 19p

Témata: PHENOTYPES, BIOLOGICAL systems, ENERGY metabolism, BIOLOGICAL databases, MACHINE learning, OUTLIER detection, AUTOENCODERS

AE-TPGG: a novel autoencoder-based approach for single-cell RNA-seq data imputation and dimensionality reduction.

Autoři: Zhao, Shuchang Zhang, Li Liu, Xuejun

Zdroj: Frontiers of Computer Science; Jun2023, Vol. 17 Issue 3, p1-18, 18p

Detecting antibiotic resistance: classical, molecular, advanced bioengineering, and AI-enhanced approaches.

Autoři: Aldea, Alexandru Constantin Diguṭă, Filofteia Camelia Presacan, Oriana a další

Zdroj: Frontiers in Microbiology; 2025, p1-33, 33p

Témata: DRUG resistance in bacteria, ARTIFICIAL intelligence, BIOENGINEERING, DETECTION algorithms, MICROFLUIDICS, CRISPRS, BIOSENSORS, MOLECULAR diagnosis

A comparison of integration methods for single‐cell RNA sequencing data and ATAC sequencing data.

Autoři: Kan, Yulong Wang, Weihao Qi, Yunjing a další

Zdroj: Quantitative Biology; Jun2025, Vol. 13 Issue 2, p1-19, 19p

Témata: DATA integration, RNA sequencing, TASK analysis, CLUSTER analysis (Statistics), METABOLOMICS

Drug–drug interaction prediction with Wasserstein Adversarial Autoencoder-based knowledge graph embeddings.

Autoři: Dai, Yuanfei Guo, Chenhao Guo, Wenzhong a další

Zdroj: Briefings in Bioinformatics; Jul2021, Vol. 22 Issue 4, p1-16, 16p

Témata: DRUG interactions, KNOWLEDGE graphs, DRUG development, FORECASTING

Genomic selection: Essence, applications, and prospects.

Autoři: Escamilla, Diana M. Li, Dongdong Negus, Karlene L. a další

Zdroj: Plant Genome; Jun2025, Vol. 18 Issue 2, p1-32, 32p

Machine Learning for Prediction of Resistance Scores in Wheat (Triticum aestivum L.).

Autoři: Heilmann, Philipp Georg Difabachew, Yohannes Fekadu Frisch, Matthias a další

Zdroj: Plant Breeding; Apr2025, Vol. 144 Issue 2, p192-205, 14p

Témata: FEATURE selection, SUPPORT vector machines, MYCOSES, RANDOM forest algorithms, WHEAT

Interpretable Fine‐Grained Phenotypes of Subcellular Dynamics via Unsupervised Deep Learning.

Autoři: Wang, Chuangqi Choi, Hee June Woodbury, Lucy a další

Zdroj: Advanced Science; 11/6/2024, Vol. 11 Issue 41, p1-21, 21p

Témata: ARTIFICIAL neural networks, CELL imaging, MACHINE learning, FEATURE extraction, CELL migration

An Autoencoder-Based Deep Learning Classifier for Efficient Diagnosis of Autism.

Autoři: Sewani, Harshini Kashef, Rasha

Zdroj: Children; Oct2020, Vol. 7 Issue 10, p391-408, 18p

Témata: AUTISM spectrum disorders, AUTISM, CONVOLUTIONAL neural networks, MACHINE learning, BIOLOGICAL neural networks