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Genomics

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GenCoder: A Novel Convolutional Neural Network Based Autoencoder for Genomic Sequence Data Compression.

IEEE/ACM transactions on computational biology and bioinformatics
Revolutionary advances in DNA sequencing technologies fundamentally change the nature of genomics. Today's sequencing technologies have opened into an outburst in genomic data volume. These data can be used in various applications where long-term sto...

Optimizing clinico-genomic disease prediction across ancestries: a machine learning strategy with Pareto improvement.

Genome medicine
BACKGROUND: Accurate prediction of an individual's predisposition to diseases is vital for preventive medicine and early intervention. Various statistical and machine learning models have been developed for disease prediction using clinico-genomic da...

Multi-Instance Multi-Task Learning for Joint Clinical Outcome and Genomic Profile Predictions From the Histopathological Images.

IEEE transactions on medical imaging
With the remarkable success of digital histopathology and the deep learning technology, many whole-slide pathological images (WSIs) based deep learning models are designed to help pathologists diagnose human cancers. Recently, rather than predicting ...

A Quadruple Revolution: Deciphering Biological Complexity with Artificial Intelligence, Multiomics, Precision Medicine, and Planetary Health.

Omics : a journal of integrative biology
A quiet quadruple revolution has been in the making in systems science with convergence of (1) artificial intelligence, machine learning, and other digital technologies; (2) multiomics big data integration; (3) growing interest in the "variability sc...

Integrating Bioinformatics and Machine Learning for Genomic Prediction in Chickens.

Genes
Genomic prediction plays an increasingly important role in modern animal breeding, with predictive accuracy being a crucial aspect. The classical linear mixed model is gradually unable to accommodate the growing number of target traits and the increa...

Regulatory barriers to US-China collaboration for generative AI development in genomic research.

Cell genomics
Here, we examine the challenges posed by laws in the United States and China for generative-AI-assisted genomic research collaboration. We recommend renewing the Agreement on Cooperation in Science and Technology to promote responsible principles for...

Residual networks without pooling layers improve the accuracy of genomic predictions.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
Residual neural network genomic selection is the first GS algorithm to reach 35 layers, and its prediction accuracy surpasses previous algorithms. With the decrease in DNA sequencing costs and the development of deep learning, phenotype prediction ac...

AVBAE-MODFR: A novel deep learning framework of embedding and feature selection on multi-omics data for pan-cancer classification.

Computers in biology and medicine
Integration analysis of cancer multi-omics data for pan-cancer classification has the potential for clinical applications in various aspects such as tumor diagnosis, analyzing clinically significant features, and providing precision medicine. In thes...

Omics data classification using constitutive artificial neural network optimized with single candidate optimizer.

Network (Bristol, England)
Recent technical advancements enable omics-based biological study of molecules with very high throughput and low cost, such as genomic, proteomic, and microbionics'. To overcome this drawback, Omics Data Classification using Constitutive Artificial N...

Fundamentals for predicting transcriptional regulations from DNA sequence patterns.

Journal of human genetics
Cell-type-specific regulatory elements, cataloged through extensive experiments and bioinformatics in large-scale consortiums, have enabled enrichment analyses of genetic associations that primarily utilize positional information of the regulatory el...