Genetics

Rapid diagnosis of hereditary haemolytic anaemias using automated rheoscopy and supervised machine learning.

Application of machine learning algorithm and modified high resolution DNA melting curve analysis for molecular subtyping of Salmonella isolates from various epidemiological backgrounds in northern Thailand.

Food poisoning from consumption of food contaminated with non-typhoidal Salmonella spp. is a global ...

Evaluation of marker selection methods and statistical models for chronological age prediction based on DNA methylation.

In forensic investigation, retrieving biological information from DNA evidence is a promising field ...

Metabolomics, machine learning and immunohistochemistry to predict succinate dehydrogenase mutational status in phaeochromocytomas and paragangliomas.

Phaeochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumours with a hereditary back...

Detection of COVID-19 Infection from Routine Blood Exams with Machine Learning: A Feasibility Study.

The COVID-19 pandemia due to the SARS-CoV-2 coronavirus, in its first 4 months since its outbreak, h...

Synthesis Success Calculator: Predicting the Rapid Synthesis of DNA Fragments with Machine Learning.

The synthesis and assembly of long DNA fragments has greatly accelerated synthetic biology and biote...

Predicting haplogroups using a versatile machine learning program (PredYMaLe) on a new mutationally balanced 32 Y-STR multiplex (CombYplex): Unlocking the full potential of the human STR mutation rate spectrum to estimate forensic parameters.

We developed a new mutationally well-balanced 32 Y-STR multiplex (CombYplex) together with a machine...

Use of Chou's 5-steps rule to predict the subcellular localization of gram-negative and gram-positive bacterial proteins by multi-label learning based on gene ontology annotation and profile alignment.

To date, many proteins generated by large-scale genome sequencing projects are still uncharacterized...

Denoising DNA Encoded Library Screens with Sparse Learning.

DNA-encoded libraries (DELs) are large, pooled collections of compounds in which every library membe...

Solo: Doublet Identification in Single-Cell RNA-Seq via Semi-Supervised Deep Learning.

Single-cell RNA sequencing (scRNA-seq) measurements of gene expression enable an unprecedented high-...

Epigenome-based splicing prediction using a recurrent neural network.

Alternative RNA splicing provides an important means to expand metazoan transcriptome diversity. Con...

Artificial intelligence-based collaborative filtering method with ensemble learning for personalized lung cancer medicine without genetic sequencing.

In personalized medicine, many factors influence the choice of compounds. Hence, the selection of su...

A fully automated deep learning pipeline for high-throughput colony segmentation and classification.

Adenine auxotrophy is a commonly used non-selective genetic marker in yeast research. It allows inve...

Enhancer recognition and prediction during spermatogenesis based on deep convolutional neural networks.

MOTIVATION: enhancers play an important role in the regulation of gene expression during spermatogen...

Integrating spatial gene expression and breast tumour morphology via deep learning.

Spatial transcriptomics allows for the measurement of RNA abundance at a high spatial resolution, ma...

Hereditary disease prediction in eukaryotic DNA: an adaptive signal processing approach.

Hereditary disease prediction in eukaryotic DNA using signal processing approaches is an incredible ...

Enhanced Integrated Gradients: improving interpretability of deep learning models using splicing codes as a case study.

Despite the success and fast adaptation of deep learning models in biomedical domains, their lack of...

A Knowledge-Based Machine Learning Approach to Gene Prioritisation in Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis is a neurodegenerative disease of the upper and lower motor neurons re...

KAML: improving genomic prediction accuracy of complex traits using machine learning determined parameters.

Advances in high-throughput sequencing technologies have reduced the cost of genotyping dramatically...

Unsupervised generative and graph representation learning for modelling cell differentiation.

Using machine learning techniques to build representations from biomedical data can help us understa...

Use of Machine Learning and Artificial Intelligence to predict SARS-CoV-2 infection from Full Blood Counts in a population.

Since December 2019 the novel coronavirus SARS-CoV-2 has been identified as the cause of the pandemi...