Genetics

Translational Applications of Artificial Intelligence and Machine Learning for Diagnostic Pathology in Lymphoid Neoplasms: A Comprehensive and Evolutive Analysis.

Genomic analysis and digitalization of medical records have led to a big data scenario within hemato...

Artificial intelligence for diagnosis of inherited retinal disease: an exciting opportunity and one step forward.

DeepD2V: A Novel Deep Learning-Based Framework for Predicting Transcription Factor Binding Sites from Combined DNA Sequence.

Predicting in vivo protein-DNA binding sites is a challenging but pressing task in a variety of fiel...

DeepDISE: DNA Binding Site Prediction Using a Deep Learning Method.

It is essential for future research to develop a new, reliable prediction method of DNA binding site...

COVID-19 diagnosis by routine blood tests using machine learning.

Physicians taking care of patients with COVID-19 have described different changes in routine blood p...

Application of multi-omics data integration and machine learning approaches to identify epigenetic and transcriptomic differences between in vitro and in vivo produced bovine embryos.

Pregnancy rates for in vitro produced (IVP) embryos are usually lower than for embryos produced in v...

Benchmarking deep learning splice prediction tools using functional splice assays.

Hereditary disorders are frequently caused by genetic variants that affect pre-messenger RNA splicin...

MichiGAN: sampling from disentangled representations of single-cell data using generative adversarial networks.

Deep generative models such as variational autoencoders (VAEs) and generative adversarial networks (...

Autosomal deletion/insertion polymorphisms for global stratification analyses and ancestry origin inferences of different continental populations by machine learning methods.

A lot of population data of 30 deletion/insertion polymorphisms (DIPs) of the Investigator DIPplex k...

XGraphBoost: Extracting Graph Neural Network-Based Features for a Better Prediction of Molecular Properties.

Determining the properties of chemical molecules is essential for screening candidates similar to a ...

Role of Regulatory Non-Coding RNAs in Aggressive Thyroid Cancer: Prospective Applications of Neural Network Analysis.

Thyroid cancer (TC) is the most common endocrine malignancy. Most TCs have a favorable prognosis, wh...

Feasibility of predicting allele specific expression from DNA sequencing using machine learning.

Allele specific expression (ASE) concerns divergent expression quantity of alternative alleles and i...

Specificity of SARS-CoV-2 Real-Time PCR Improved by Deep Learning Analysis.

Real-time PCR (RT-PCR) is widely used to diagnose human pathogens. RT-PCR data are traditionally ana...

The in vitro micronucleus assay using imaging flow cytometry and deep learning.

The in vitro micronucleus (MN) assay is a well-established assay for quantification of DNA damage, a...

An improved DNA-binding hot spot residues prediction method by exploring interfacial neighbor properties.

BACKGROUND: DNA-binding hot spots are dominant and fundamental residues that contribute most of the ...

Digital imaging, technologies and artificial intelligence applications during COVID-19 pandemic.

The advancement of technology remained an immersive interest for humankind throughout the past decad...

Identification of potential genomic biomarkers for Parkinson's disease using data pooling of gene expression microarrays.

In this study, we aimed to identify potential diagnostic biomarkers Parkinson's disease (PD) by exp...

Torque Curve Optimization of Ankle Push-Off in Walking Bipedal Robots Using Genetic Algorithm.

Ankle push-off occurs when muscle-tendon units about the ankle joint generate a burst of positive po...

A convolution based computational approach towards DNA N6-methyladenine site identification and motif extraction in rice genome.

DNA N6-methylation (6mA) in Adenine nucleotide is a post replication modification responsible for ma...

Prediction of functional outcomes of schizophrenia with genetic biomarkers using a bagging ensemble machine learning method with feature selection.

Genetic variants such as single nucleotide polymorphisms (SNPs) have been suggested as potential mol...

Kernel machine SNP set analysis finds the association of BUD13, ZPR1, and APOA5 variants with metabolic syndrome in Tehran Cardio-metabolic Genetics Study.

Metabolic syndrome (MetS) is one of the most important risk factors for cardiovascular disease. The ...