Genetics

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

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Showing 4726-4746 of 10,553 articles
Embracing Environmental Genomics and Machine Learning for Routine Biomonitoring.

Genomics is fast becoming a routine tool in medical diagnostics and cutting-edge biotechnologies. Ye...

Identifying mouse developmental essential genes using machine learning.

The genes that are required for organismal survival are annotated as 'essential genes'. Identifying ...

Knowledge base toward understanding actionable alterations and realizing precision oncology.

In Japan, the National Cancer Center and university hospitals have initiated next-generation sequenc...

Leveraging Multilayered "Omics" Data for Atopic Dermatitis: A Road Map to Precision Medicine.

Atopic dermatitis (AD) is a complex multifactorial inflammatory skin disease that affects ~280 milli...

Biomarkers and polymorphisms in pancreatic neuroendocrine tumors treated with sunitinib.

Several circulating biomarkers and single nucleotide polymorphisms (SNPs) have been correlated with ...

Functional expression of porcine interferon-α using a combinational strategy in Pichia pastoris GS115.

Porcine interferon-α (pIFN-α) could be used as the vaccine adjuvant to enhance the antiviral ability...

Multi-trait, Multi-environment Deep Learning Modeling for Genomic-Enabled Prediction of Plant Traits.

Multi-trait and multi-environment data are common in animal and plant breeding programs. However, wh...

Multi-environment Genomic Prediction of Plant Traits Using Deep Learners With Dense Architecture.

Genomic selection is revolutionizing plant breeding and therefore methods that improve prediction ac...

Identifying disease genes using machine learning and gene functional similarities, assessed through Gene Ontology.

Identifying disease genes from a vast amount of genetic data is one of the most challenging tasks in...

Identification of tissue-specific tumor biomarker using different optimization algorithms.

BACKGROUND: Identification of differentially expressed genes, i.e., genes whose transcript abundance...

Prediction of CRISPR sgRNA Activity Using a Deep Convolutional Neural Network.

The CRISPR-Cas9 system derived from adaptive immunity in bacteria and archaea has been developed int...

Contrast enhancement is a prognostic factor in IDH1/2 mutant, but not in wild-type WHO grade II/III glioma as confirmed by machine learning.

BACKGROUND: Mutation of the isocitrate dehydrogenase (IDH) gene and co-deletion on chromosome 1p/19q...

Distillation of the clinical algorithm improves prognosis by multi-task deep learning in high-risk Neuroblastoma.

We introduce the CDRP (Concatenated Diagnostic-Relapse Prognostic) architecture for multi-task deep ...

Effect of inter-individual variability in human liver cytochrome P450 isozymes on cyclophosphamide-induced micronucleus formation.

We investigated the relationship between metabolic activities of cytochrome P450 (CYP) isozymes pres...

A hybrid approach for automated mutation annotation of the extended human mutation landscape in scientific literature.

As the cost of DNA sequencing continues to fall, an increasing amount of information on human geneti...

Improving the calling of non-invasive prenatal testing on 13-/18-/21-trisomy by support vector machine discrimination.

With the advance of next-generation sequencing (NGS) technologies, non-invasive prenatal testing (NI...

Setting Up a Surface-Enhanced Raman Scattering Database for Artificial-Intelligence-Based Label-Free Discrimination of Tumor Suppressor Genes.

The quality of input data in deep learning is tightly associated with the ultimate performance of th...

Porcine single nucleotide polymorphisms and their functional effect: an update.

OBJECTIVE: To aid in the development of a comprehensive list of functional variants in the swine gen...

iSEE: Interface structure, evolution, and energy-based machine learning predictor of binding affinity changes upon mutations.

Quantitative evaluation of binding affinity changes upon mutations is crucial for protein engineerin...

A Primer on Data Analytics in Functional Genomics: How to Move from Data to Insight?

High-throughput methodologies and machine learning have been central in developing systems-level per...

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