Genetics

Latest AI and machine learning research in genetics for healthcare professionals.

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Lineage-specific regulatory evolution: insights from massively parallel reporter assays.

Lineage-specific genetic variants play a key role in evolutionary divergence, particularly through c...

Applying multimodal AI to physiological waveforms improves genetic prediction of cardiovascular traits.

Electronic health records, biobanks, and wearable biosensors enable the collection of multiple healt...

Multistage nucleation pathway in LiF molten salt mirrors the crystal-melt interface structure.

Despite over a century of studies, fundamental questions remain about the processes governing crysta...

Leveraging viral genome sequences and machine learning models for identification of potentially selective antiviral agents.

Viral genome sequencing provides valuable information for antiviral development, yet its integration...

Few shot learning for phenotype-driven diagnosis of patients with rare genetic diseases.

There are over 7000 rare diseases, some affecting 3500 or fewer patients in the United States. Due t...

Investigating the metastability of amorphous calcium carbonate by droplet microfluidics experiments using machine learning.

Amorphous calcium carbonate (ACC) plays an important role in the crystallization pathways of calcite...

Deciphering Cell Type Abundance in Proteomics Data Through Graph Neural Networks.

Recent advancements in proteomics sequencing have significantly enhanced our ability to explore cell...

A Salient Object Detection Network Enhanced by Nonlinear Spiking Neural Systems and Transformer.

Although a variety of deep learning-based methods have been introduced for Salient Object Detection ...

A compact encoding of the genome suitable for machine learning prediction of traits and genetic risk scores.

Genotype to phenotype prediction is a central problem in biology and medicine. Machine learning is a...

Multi-omics approaches: transforming the landscape of natural product isolation.

The field of natural product (NPs) discovery has significantly evolved with the advent of multi-omic...

Decoding the interactions and functions of non-coding RNA with artificial intelligence.

In addition to encoding proteins, mRNAs have context-specific regulatory roles that contribute to ma...

MVHGCN: Predicting circRNA-disease associations with multi-view heterogeneous graph convolutional neural networks.

Circular RNA, a class of RNA molecules gaining widespread attentions, has been widely recognized as ...

Design of Hopfield Neural Network Based on DNA Strand Displacement Circuits and Its Application in Sudoku Conjecture.

In recent years, biological neural networks have developed rapidly due to their advantages of fast p...

WISP2/CCN5 revealed as a potential diagnostic biomarker for endometriosis based on machine learning and single-cell transcriptomic analysis.

OBJECTIVE: Endometriosis is a prevalent gynecological disease characterized by the ectopic growth of...

In vivo mapping of mutagenesis sensitivity of human enhancers.

Distant-acting enhancers are central to human development. However, our limited understanding of the...

Divergence in a eukaryotic transcription factor's co-TF dependence involves multiple intrinsically disordered regions.

Combinatorial control by transcription factors (TFs) is central to eukaryotic gene regulation, yet i...

Integrating AI and genomics: predictive CNN models for schizophrenia phenotypes.

This study explores the use of deep learning to analyze genetic data and predict phenotypic traits a...

Morphological traits and machine learning for genetic lineage prediction of two reef-building corals.

Integrating multiple lines of evidence that support molecular taxonomy analysis has proven to be a r...

DeepRice6mA: A convolutional neural network approach for 6mA site prediction in the rice Genome.

As one of the most critical post-replication modifications, N6-methylation (6mA) at adenine residue ...

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