Genetics

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

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Enabling full-length evolutionary profiles based deep convolutional neural network for predicting DNA-binding proteins from sequence.

Sequence based DNA-binding protein (DBP) prediction is a widely studied biological problem. Sliding ...

Applying Deep Neural Network Analysis to High-Content Image-Based Assays.

The etiological underpinnings of many CNS disorders are not well understood. This is likely due to t...

Deconvolution of autoencoders to learn biological regulatory modules from single cell mRNA sequencing data.

BACKGROUND: Unsupervised machine learning methods (deep learning) have shown their usefulness with n...

A practical guide to intelligent image-activated cell sorting.

Intelligent image-activated cell sorting (iIACS) is a machine-intelligence technology that performs ...

BioGD: Bio-inspired robust gradient descent.

Recent research in machine learning pointed to the core problem of state-of-the-art models which imp...

Microbiome composition and implications for ballast water classification using machine learning.

Ballast water is a vector for global translocation of microorganisms, and should be monitored to pro...

Deep learning-based selection of human sperm with high DNA integrity.

Despite the importance of sperm DNA to human reproduction, currently no method exists to assess indi...

CT texture analysis for the prediction of KRAS mutation status in colorectal cancer via a machine learning approach.

PURPOSE: This study aimed to investigate whether a machine learning-based computed tomography (CT) t...

Cancer classification and pathway discovery using non-negative matrix factorization.

OBJECTIVES: Extracting genetic information from a full range of sequencing data is important for und...

Exploring the druggable space around the Fanconi anemia pathway using machine learning and mechanistic models.

BACKGROUND: In spite of the abundance of genomic data, predictive models that describe phenotypes as...

Machine learning to predict microbial community functions: An analysis of dissolved organic carbon from litter decomposition.

Microbial communities are ubiquitous and often influence macroscopic properties of the ecosystems th...

C-HMOSHSSA: Gene selection for cancer classification using multi-objective meta-heuristic and machine learning methods.

BACKGROUND AND OBJECTIVE: Over the last two decades, DNA microarray technology has emerged as a powe...

Gene Expression Data Based Deep Learning Model for Accurate Prediction of Drug-Induced Liver Injury in Advance.

Drug-induced liver injury (DILI), one of the most common adverse effects, leads to drug development ...

A high-throughput screening and computation platform for identifying synthetic promoters with enhanced cell-state specificity (SPECS).

Cell state-specific promoters constitute essential tools for basic research and biotechnology becaus...

Estimation of allele-specific fitness effects across human protein-coding sequences and implications for disease.

A central challenge in human genomics is to understand the cellular, evolutionary, and clinical sign...

EternaBrain: Automated RNA design through move sets and strategies from an Internet-scale RNA videogame.

Emerging RNA-based approaches to disease detection and gene therapy require RNA sequences that fold ...

Identification of a Multiplex Biomarker Panel for Hypertrophic Cardiomyopathy Using Quantitative Proteomics and Machine Learning.

Hypertrophic cardiomyopathy (HCM) is defined by pathological left ventricular hypertrophy (LVH). It ...

Computational and artificial neural network based study of functional SNPs of human LEPR protein associated with reproductive function.

Genetic polymorphisms are mostly associated with inherited diseases, detecting and analyzing the bio...

Dynamics reconstruction and classification via Koopman features.

Knowledge discovery and information extraction of large and complex datasets has attracted great att...

Performance of neural network basecalling tools for Oxford Nanopore sequencing.

BACKGROUND: Basecalling, the computational process of translating raw electrical signal to nucleotid...

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