Genetics

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

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Machine learning technology in the application of genome analysis: A systematic review.

Machine learning (ML) is a powerful technique to tackle many problems in data mining and predictive ...

Machine-learning based radiogenomics analysis of MRI features and metagenes in glioblastoma multiforme patients with different survival time.

BACKGROUND: This study aimed to examine multi-dimensional MRI features' predictability on survival o...

PGxO and PGxLOD: a reconciliation of pharmacogenomic knowledge of various provenances, enabling further comparison.

BACKGROUND: Pharmacogenomics (PGx) studies how genomic variations impact variations in drug response...

SPINDLE: End-to-end learning from EEG/EMG to extrapolate animal sleep scoring across experimental settings, labs and species.

Understanding sleep and its perturbation by environment, mutation, or medication remains a central p...

DNAPred: Accurate Identification of DNA-Binding Sites from Protein Sequence by Ensembled Hyperplane-Distance-Based Support Vector Machines.

Accurate identification of protein-DNA binding sites is significant for both understanding protein f...

A directed learning strategy integrating multiple omic data improves genomic prediction.

Genomic prediction (GP) aims to construct a statistical model for predicting phenotypes using genome...

Hybrid model for efficient prediction of poly(A) signals in human genomic DNA.

Polyadenylation signals (PAS) are found in most protein-coding and some non-coding genes in eukaryot...

RNA-Protein Binding Sites Prediction via Multi Scale Convolutional Gated Recurrent Unit Networks.

RNA-Protein binding plays important roles in the field of gene expression. With the development of h...

Exon level machine learning analyses elucidate novel candidate miRNA targets in an avian model of fetal alcohol spectrum disorder.

Gestational alcohol exposure causes fetal alcohol spectrum disorder (FASD) and is a prominent cause ...

Enzymatic Weight Update Algorithm for DNA-Based Molecular Learning.

Recent research in DNA nanotechnology has demonstrated that biological substrates can be used for co...

Capsule Network Based Modeling of Multi-omics Data for Discovery of Breast Cancer-Related Genes.

Breast cancer is one of the most common cancers all over the world, which bring about more than 450,...

Machine Learning Based Real-Time Image-Guided Cell Sorting and Classification.

Cell classification based on phenotypical, spatial, and genetic information greatly advances our und...

Identification of Hürthle cell cancers: solving a clinical challenge with genomic sequencing and a trio of machine learning algorithms.

BACKGROUND: Identification of Hürthle cell cancers by non-operative fine-needle aspiration biopsy (F...

DeepHistone: a deep learning approach to predicting histone modifications.

MOTIVATION: Quantitative detection of histone modifications has emerged in the recent years as a maj...

MRCNN: a deep learning model for regression of genome-wide DNA methylation.

BACKGROUND: Determination of genome-wide DNA methylation is significant for both basic research and ...

Predicting DNA Methylation States with Hybrid Information Based Deep-Learning Model.

DNA methylation plays an important role in the regulation of some biological processes. Up to now, w...

Prediction of Long Non-Coding RNAs Based on Deep Learning.

With the rapid development of high-throughput sequencing technology, a large number of transcript se...

ML-DSP: Machine Learning with Digital Signal Processing for ultrafast, accurate, and scalable genome classification at all taxonomic levels.

BACKGROUND: Although software tools abound for the comparison, analysis, identification, and classif...

Analyzing DNA methylation patterns in subjects diagnosed with schizophrenia using machine learning methods.

Schizophrenia is a common mental disorder with high heritability. It is genetically complex and to d...

Seq2seq Fingerprint with Byte-Pair Encoding for Predicting Changes in Protein Stability upon Single Point Mutation.

The engineering of stable proteins is crucial for various industrial purposes. Several machine learn...

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