AI Medical Compendium Journal:
Frontiers in genetics

Showing 21 to 30 of 44 articles

Identifying Membrane Protein Types Based on Lifelong Learning With Dynamically Scalable Networks.

Frontiers in genetics
Membrane proteins are an essential part of the body's ability to maintain normal life activities. Further research into membrane proteins, which are present in all aspects of life science research, will help to advance the development of cells and dr...

Relationships Among Arsenic-Related Traits, Including Rice Grain Arsenic Concentration and Straighthead Resistance, as Revealed by Genome-Wide Association.

Frontiers in genetics
There is global concern that rice grains and foods can contain harmful amounts of arsenic (As), motivating breeders to produce cultivars that restrict As accumulation in grains to protect human health. Arsenic is also toxic to plants, with straighthe...

Predicting Mutational Status of Driver and Suppressor Genes Directly from Histopathology With Deep Learning: A Systematic Study Across 23 Solid Tumor Types.

Frontiers in genetics
In the last four years, advances in Deep Learning technology have enabled the inference of selected mutational alterations directly from routine histopathology slides. In particular, recent studies have shown that genetic changes in clinically releva...

Metabolomic Profiling Reveals That 5-Hydroxylysine and 1-Methylnicotinamide Are Metabolic Indicators of Keloid Severity.

Frontiers in genetics
Keloid is a skin fibroproliferative disease with unknown pathogenesis. Metabolomics provides a new perspective for revealing biomarkers related to metabolites and their metabolic mechanisms. Metabolomics and transcriptomics were used for data analy...

A Tumor Suppressor Gene-Based Prognostic Classifier Predicts Prognosis, Tumor Immune Infiltration, and Small Molecule Compounds in Breast Cancer.

Frontiers in genetics
Tumor suppressor genes (TSGs) play critical roles in the cell cycle checkpoints and in modulating genomic stability. Here, we aimed to develop a TSG-based prognostic classifier for breast cancer. Gene expression profiles and clinical information of...

Machine Learning of Single Cell Transcriptomic Data From anti-PD-1 Responders and Non-responders Reveals Distinct Resistance Mechanisms in Skin Cancers and PDAC.

Frontiers in genetics
Immune checkpoint therapies such as PD-1 blockade have vastly improved the treatment of numerous cancers, including basal cell carcinoma (BCC). However, patients afflicted with pancreatic ductal carcinoma (PDAC), one of the deadliest malignancies, ov...

Ookinete-Specific Genes and 18S SSU rRNA Evidenced in Selection and Adaptation by Sympatric Vectors.

Frontiers in genetics
In the southern Pacific coast of Chiapas, Mexico (SM), the two most abundant vector species, and , were susceptible to different Pvs25/28 haplotypes. To broaden our understanding of the existing in the area, genes encoding proteins relevant for oo...

An Information Entropy-Based Approach for Computationally Identifying Histone Lysine Butyrylation.

Frontiers in genetics
Butyrylation plays a crucial role in the cellular processes. Due to limit of techniques, it is a challenging task to identify histone butyrylation sites on a large scale. To fill the gap, we propose an approach based on information entropy and machin...

Corrigendum: Digitaldlsorter: Deep-Learning on scRNA-Seq to Deconvolute Gene Expression Data.

Frontiers in genetics
[This corrects the article DOI: 10.3389/fgene.2019.00978.].

A Three-Gene Classifier Associated With MicroRNA-Mediated Regulation Predicts Prostate Cancer Recurrence After Radical Prostatectomy.

Frontiers in genetics
BACKGROUND AND OBJECTIVE: After radical prostatectomy (RP), prostate cancer (PCa) patients may experience biochemical recurrence (BCR) and clinical recurrence, which remains a dominant issue in PCa treatment. The purpose of this study was to identify...