Genetics

Tritium: Its relevance, sources and impacts on non-human biota.

Tritium (H) is a radioactive isotope of hydrogen that is abundantly released from nuclear industries. It is extremely mobile in the environment and in all biological systems, representing an increasing concern for the health of both humans and non-human biota (NHB). The present review examines the sources and characteristics of tritium in the environment, and evaluates available information pertai...

Benchmarking machine learning robustness in Covid-19 genome sequence classification.

The rapid spread of the COVID-19 pandemic has resulted in an unprecedented amount of sequence data of the SARS-CoV-2 genome-millions of sequences and counting. This amount of data, while being orders of magnitude beyond the capacity of traditional approaches to understanding the diversity, dynamics, and evolution of viruses, is nonetheless a rich resource for machine learning (ML) approaches as al...

Estimating resistance surfaces using gradient forest and allelic frequencies.

Understanding landscape connectivity has become a global priority for mitigating the impact of landscape fragmentation on biodiversity. Connectivity m...

Deep Learning Radiomics for the Assessment of Telomerase Reverse Transcriptase Promoter Mutation Status in Patients With Glioblastoma Using Multiparametric MRI.

BACKGROUND: Studies have shown that magnetic resonance imaging (MRI)-based deep learning radiomics (DLR) has the potential to assess glioma grade; how...

Clinical application of AI-based PET images in oncological patients.

Based on the advantages of revealing the functional status and molecular expression of tumor cells, positron emission tomography (PET) imaging has bee...

Highly Performing Automatic Detection of Structural Chromosomal Abnormalities Using Siamese Architecture.

The detection of structural chromosomal abnormalities (SCA) is crucial for diagnosis, prognosis and management of many genetic diseases and cancers. T...

Deep Learning Prediction of Promoter Mutation Status in Thyroid Cancer Using Histologic Images.

objectives: Telomerase reverse transcriptase () promoter mutation, found in a subset of patients with thyroid cancer, is strongly associated with agg...

Prediction and Control in DNA Nanotechnology.

DNA nanotechnology is a rapidly developing field that uses DNA as a building material for nanoscale structures. Key to the field's development has bee...

Comprehensive Functional Annotation of Metagenomes and Microbial Genomes Using a Deep Learning-Based Method.

Comprehensive protein function annotation is essential for understanding microbiome-related disease mechanisms in the host organisms. However, a large...

A novel survival prediction signature outperforms PAM50 and artificial intelligence-based feature-selection methods.

The robustness of a breast cancer gene signature, the super-proliferation set (SPS), is initially tested and investigated on breast cancer cell lines ...

Machine learning-aided scoring of synthesis difficulties for designer chromosomes.

Designer chromosomes are artificially synthesized chromosomes. Nowadays, these chromosomes have numerous applications ranging from medical research to...

Formulation and Characterization of Buccal Films Containing Valsartan with Additional Support from Image Analysis.

The present study was aimed to the development and characterization of valsartan-containing buccal films with an introduction to a novel technique of ...

Predicting survival after radiosurgery in patients with lung cancer brain metastases using deep learning of radiomics and EGFR status.

The early prediction of overall survival (OS) in patients with lung cancer brain metastases (BMs) after Gamma Knife radiosurgery (GKRS) can facilitate...

Towards artificial intelligence to multi-omics characterization of tumor heterogeneity in esophageal cancer.

Esophageal cancer is a unique and complex heterogeneous malignancy, with substantial tumor heterogeneity: at the cellular levels, tumors are composed ...

DeltaMSI: artificial intelligence-based modeling of microsatellite instability scoring on next-generation sequencing data.

BACKGROUND: DNA mismatch repair deficiency (dMMR) testing is crucial for detection of microsatellite unstable (MSI) tumors. MSI is detected by aberran...

A Unified Deep Learning Framework for Single-Cell ATAC-Seq Analysis Based on ProdDep Transformer Encoder.

Recent advances in single-cell sequencing assays for the transposase-accessibility chromatin (scATAC-seq) technique have provided cell-specific chroma...

SCP4ssd: A Serverless Platform for Nucleotide Sequence Synthesis Difficulty Prediction Using an AutoML Model.

DNA synthesis is widely used in synthetic biology to construct and assemble sequences ranging from short RBS to ultra-long synthetic genomes. Many seq...

A deep learning workflow for quantification of micronuclei in DNA damage studies in cultured cancer cell lines: A proof of principle investigation.

The cytokinesis block micronucleus assay is widely used for measuring/scoring/counting micronuclei, a marker of genome instability in cultured and pri...

Cross-platform normalization enables machine learning model training on microarray and RNA-seq data simultaneously.

Large compendia of gene expression data have proven valuable for the discovery of novel biological relationships. Historically, most available RNA ass...

Genetic Risk Assessment of Nonsyndromic Cleft Lip with or without Cleft Palate by Linking Genetic Networks and Deep Learning Models.

Recent deep learning algorithms have further improved risk classification capabilities. However, an appropriate feature selection method is required t...