Genetics

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

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Development and validation of an interpretable risk prediction model for the early classification of thalassemia.

Thalassemia is an inherited blood disorder. Current diagnostic methods mainly rely on sophisticated ...

Chatbot for the Return of Positive Genetic Screening Results for Hereditary Cancer Syndromes: Prompt Engineering Project.

The increasing demand for population-wide genomic screening and the limited availability of genetic ...

Tailoring Corynebacterium glutamicum for Sustainable Biomanufacturing: From Traditional to Cutting-Edge Technologies.

As the workhorse of industrial amino acid production, Corynebacterium glutamicum is the focus of thi...

A library of lineage-specific driver lines connects developing neuronal circuits to behavior in the ventral nerve cord.

Understanding developmental changes in neuronal lineages is crucial to elucidate how they assemble i...

Linking autism risk genes to morphological and pharmaceutical screening by high-content imaging: Future directions and opinion.

Next-generation sequencing has identified risk genes with large effect sizes for autism spectrum dis...

From code to archetype: Toward a unified theory of biological, neural, and artificial artifacts.

Carl Jung's concept of archetypes as innate, universal structures of the human psyche finds surprisi...

Machine Learning Prediction on Birefringence of Nonlinear Optical Crystals and Polymorphs with Different Birefringence Activities.

Nonlinear optical (NLO) crystal materials have been widely used in the scientific and industrial fie...

Identification of Isomerically Diverse Ginsenosides Using Engineered Aerolysin Nanopore via Non-Translocation Blockade Sensing.

Typical nanopore sensing depends on slowed translocation through the pore to acquire effective block...

Codes across (life)sciences.

The concept of "code" connotes different meanings, intentions, and formalizations. From mathematics ...

Single-cell sequencing and machine learning reveal the role of dioxin-interacting genes in HCC prognosis and immune microenvironment.

Dioxins are persistent environmental pollutants that bioaccumulate in the food chain, posing signifi...

Identification of macrophage-associated diagnostic biomarkers and molecular subtypes in gestational diabetes mellitus based on machine learning.

Gestational diabetes mellitus (GDM) is a common metabolic disorder during pregnancy, involving multi...

Assessing simulation-based supervised machine learning for demographic parameter inference from genomic data.

The ever-increasing availability of high-throughput DNA sequences and the development of numerous co...

Machine learning techniques for continuous genetic assignment of geographic origin of forest trees.

Origin tracking is important to ensure use of the right seed source and trade with legally harvested...

MFDSMC: Accurate Identification of Cancer-Driver Synonymous Mutations Using Multiperspective Feature Representation Learning.

Synonymous mutations do not change amino acid sequences, but they can drive cancer by influencing sp...

scGANSL: Graph Attention Network with Subspace Learning for scRNA-seq Data Clustering.

Single-cell RNA sequencing (scRNA-seq) has become a crucial technology for analyzing cellular divers...

Detecting genetic interactions with visible neural networks.

Non-linear interactions among single nucleotide polymorphisms (SNPs), genes, and pathways play an im...

Machine learning and multi-omics analysis reveal key regulators of proneural-mesenchymal transition in glioblastoma.

Glioblastoma (GBM) is classified into subtypes according to the molecular expression profile; the pr...

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