Genetics

Hercules: a profile HMM-based hybrid error correction algorithm for long reads.

Choosing whether to use second or third generation sequencing platforms can lead to trade-offs between accuracy and read length. Several types of studies require long and accurate reads. In such cases researchers often combine both technologies and the erroneous long reads are corrected using the short reads. Current approaches rely on various graph or alignment based techniques and do not take th...

LncRNAnet: long non-coding RNA identification using deep learning.

MOTIVATION: Long non-coding RNAs (lncRNAs) are important regulatory elements in biological processes. LncRNAs share similar sequence characteristics with messenger RNAs, but they play completely different roles, thus providing novel insights for biological studies. The development of next-generation sequencing has helped in the discovery of lncRNA transcripts. However, the experimental verificatio...

Predicting reservoir hosts and arthropod vectors from evolutionary signatures in RNA virus genomes.

Identifying the animal origins of RNA viruses requires years of field and laboratory studies that stall responses to emerging infectious diseases. Usi...

Identifying patients with familial hypercholesterolemia using data mining methods in the Northern Great Plain region of Hungary.

BACKGROUND AND AIMS: Familial hypercholesterolemia (FH) is one of the most frequent diseases with monogenic inheritance. Previous data indicated that ...

Machine-Assisted Genotype Update System (MAGUS) for Inherited Cardiomyopathies.

A systematic exploration of [Formula: see text] cutoff ranges in machine learning models for protein mutation stability prediction.

Discerning how a mutation affects the stability of a protein is central to the study of a wide range of diseases. Mutagenesis experiments on physical ...

Gene multifunctionality scoring using gene ontology.

Multifunctional genes are important genes because of their essential roles in human cells. Studying and analyzing multifunctional genes can help under...

[Application of machine learning in the CRISPR/Cas9 system].

The third generation of the CRISPR/Cas9-mediated genome fixed-point editing technology has been widely used in the field of gene editing and gene expr...

A deep recurrent neural network discovers complex biological rules to decipher RNA protein-coding potential.

The current deluge of newly identified RNA transcripts presents a singular opportunity for improved assessment of coding potential, a cornerstone of g...

PathwaySplice: an R package for unbiased pathway analysis of alternative splicing in RNA-Seq data.

SUMMARY: Pathway analysis of alternative splicing would be biased without accounting for the different number of exons or junctions associated with ea...

A machine learning approach for somatic mutation discovery.

Variability in the accuracy of somatic mutation detection may affect the discovery of alterations and the therapeutic management of cancer patients. T...

GARFIELD-NGS: Genomic vARiants FIltering by dEep Learning moDels in NGS.

SUMMARY: Exome sequencing approach is extensively used in research and diagnostic laboratories to discover pathological variants and study genetic arc...

Exoskeleton and End-Effector Robots for Upper and Lower Limbs Rehabilitation: Narrative Review.

Recovery of upper and lower limbs function is essential to reach independence in daily activities in patients with upper motor neuron syndrome (UMNS)....

Discovering epistatic feature interactions from neural network models of regulatory DNA sequences.

MOTIVATION: Transcription factors bind regulatory DNA sequences in a combinatorial manner to modulate gene expression. Deep neural networks (DNNs) can...

Towards an accurate and efficient heuristic for species/gene tree co-estimation.

MOTIVATION: Species and gene trees represent how species and individual loci within their genomes evolve from their most recent common ancestors. Thes...

Off-target predictions in CRISPR-Cas9 gene editing using deep learning.

MOTIVATION: The prediction of off-target mutations in CRISPR-Cas9 is a hot topic due to its relevance to gene editing research. Existing prediction me...

DeepDiff: DEEP-learning for predicting DIFFerential gene expression from histone modifications.

MOTIVATION: Computational methods that predict differential gene expression from histone modification signals are highly desirable for understanding h...

A deep neural network approach for learning intrinsic protein-RNA binding preferences.

MOTIVATION: The complexes formed by binding of proteins to RNAs play key roles in many biological processes, such as splicing, gene expression regulat...

Cost function network-based design of protein-protein interactions: predicting changes in binding affinity.

MOTIVATION: Accurate and economic methods to predict change in protein binding free energy upon mutation are imperative to accelerate the design of pr...

[From symptom to syndrome using modern software support].

Diagnosing rare diseases can be challenging for clinicians. This article gives an overview on novel approaches, which enable automated phenotype-drive...