Genetics

Comparative analysis of machine learning approaches to classify tumor mutation burden in lung adenocarcinoma using histopathology images.

Both histologic subtypes and tumor mutation burden (TMB) represent important biomarkers in lung cancer, with implications for patient prognosis and treatment decisions. Typically, TMB is evaluated by comprehensive genomic profiling but this requires use of finite tissue specimens and costly, time-consuming laboratory processes. Histologic subtype classification represents an established component ...

The "GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork": Origins, Rationale, Organization, and Prospects.

Musculoskeletal research has been enriched in the past ten years with a great wealth of new discoveries arising from genome wide association studies (GWAS). In addition to the novel factors identified by GWAS, the advent of whole-genome and whole-exome sequencing efforts in family based studies has also identified new genes and pathways. However, the function and the mechanisms by which such genes...

HELLO: improved neural network architectures and methodologies for small variant calling.

BACKGROUND: Modern Next Generation- and Third Generation- Sequencing methods such as Illumina and PacBio Circular Consensus Sequencing platforms provi...

Deep learning-based gene selection in comprehensive gene analysis in pancreatic cancer.

The selection of genes that are important for obtaining gene expression data is challenging. Here, we developed a deep learning-based feature selectio...

Interleukin-37 gene polymorphism and susceptibility to pulmonary tuberculosis among Iraqi patients.

BACKGROUND: Control of tuberculosis (TB) depends on a balance between host's immune factors and bacterial evasion strategies. Interleukin-37 (IL-37) i...

Identification of disease genes and assessment of eye-related diseases caused by disease genes using JMFC and GDLNN.

Early detection of disease genes helps humans to recover from certain gene-related diseases, like genetic eye diseases. This work identifies the possi...

A deep learning approach to automate whole-genome prediction of diverse epigenomic modifications in plants.

Epigenetic modifications function in gene transcription, RNA metabolism, and other biological processes. However, multiple factors currently limit the...

Accurate Estimation of Solvent Accessible Surface Area for Coarse-Grained Biomolecular Structures with Deep Learning.

Coarse-grained (CG) models of biomolecules have been widely used in protein/ribonucleic acid (RNA) three-dimensional structure prediction, docking, dr...

DeepG4: A deep learning approach to predict cell-type specific active G-quadruplex regions.

DNA is a complex molecule carrying the instructions an organism needs to develop, live and reproduce. In 1953, Watson and Crick discovered that DNA is...

Sequence Ontology terminology for gene regulation.

The Sequence Ontology (SO) is a structured, controlled vocabulary that provides terms and definitions for genomic annotation. The Gene Regulation Ense...

The alterations of miRNA and mRNA expression profile and their integration analysis induced by silica nanoparticles in spermatocyte cells.

Air pollution and the application of Silica nanoparticles (SiNPs) have increased the risk of human exposure to SiNPs. SiNPs are known to induce cytoto...

Identification of conserved transcriptome features between humans and Drosophila in the aging brain utilizing machine learning on combined data from the NIH Sequence Read Archive.

Aging is universal, yet characterizing the molecular changes that occur in aging which lead to an increased risk for neurological disease remains a ch...

Bidirectional deep neural networks to integrate RNA and DNA data for predicting outcome for patients with hepatocellular carcinoma.

Individualized patient profiling is instrumental for personalized management in hepatocellular carcinoma (HCC). This study built a model based on bid...

iPromoter-ET: Identifying promoters and their strength by extremely randomized trees-based feature selection.

Promoter is a region of DNA that determines the transcription of a particular gene. There are several σ factors in the RNA polymerase, which has the f...

SCAPTURE: a deep learning-embedded pipeline that captures polyadenylation information from 3' tag-based RNA-seq of single cells.

Single-cell RNA-seq (scRNA-seq) profiles gene expression with high resolution. Here, we develop a stepwise computational method-called SCAPTURE to ide...

Business English Translation Model Based on BP Neural Network Optimized by Genetic Algorithm.

In recent years, most of the communication places are using business English manual simultaneous interpretation or electronic equipment translation. I...

Discovering differential genome sequence activity with interpretable and efficient deep learning.

Discovering sequence features that differentially direct cells to alternate fates is key to understanding both cellular development and the consequenc...

Machine learning-based identification and characterization of 15 novel pathogenic SUOX missense mutations.

Isolated sulfite oxidase deficiency (ISOD) is a rare hereditary metabolic disease caused by absence of functional sulfite oxidase (SO) due to mutation...

Discriminant Projection Shared Dictionary Learning for Classification of Tumors Using Gene Expression Data.

With a variety of tumor subtypes, personalized treatments need to identify the subtype of a tumor as accurately as possible. The development of DNA mi...

DeepDRBP-2L: A New Genome Annotation Predictor for Identifying DNA-Binding Proteins and RNA-Binding Proteins Using Convolutional Neural Network and Long Short-Term Memory.

DNA-binding proteins (DBPs) and RNA-binding proteins (RBPs) are two kinds of crucial proteins, which are associated with various cellule activities an...