Genetics

gammaBOriS: Identification and Taxonomic Classification of Origins of Replication in Gammaproteobacteria using Motif-based Machine Learning.

The biology of bacterial cells is, in general, based on information encoded on circular chromosomes....

Combination Strategies for Immune-Checkpoint Blockade and Response Prediction by Artificial Intelligence.

The therapeutic concept of unleashing a pre-existing immune response against the tumor by the applic...

Dendrite P systems.

It was recently found that dendrites are not just a passive channel. They can perform mixed computat...

Opening the Black Box: Interpretable Machine Learning for Geneticists.

Because of its ability to find complex patterns in high dimensional and heterogeneous data, machine ...

Fold-Change-Specific Enrichment Analysis (FSEA): Quantification of Transcriptional Response Magnitude for Functional Gene Groups.

Gene expression profiling data contains more information than is routinely extracted with standard a...

What kind of novelties can machine learning possibly generate? The case of genomics.

A comparative study of machine learning and deep learning algorithms to classify cancer types based on microarray gene expression data.

Cancer classification is a topic of major interest in medicine since it allows accurate and efficien...

PredDBP-Stack: Prediction of DNA-Binding Proteins from HMM Profiles using a Stacked Ensemble Method.

DNA-binding proteins (DBPs) play vital roles in all aspects of genetic activities. However, the iden...

Random forest machine learning algorithm predicts virologic outcomes among HIV infected adults in Lausanne, Switzerland using electronically monitored combined antiretroviral treatment adherence.

Machine Learning (ML) can improve the analysis of complex and interrelated factors that place adhere...

Predicting the short-term success of human influenza virus variants with machine learning.

Seasonal influenza viruses are constantly changing and produce a different set of circulating strain...

Biohorology and biomarkers of aging: Current state-of-the-art, challenges and opportunities.

The aging process results in multiple traceable footprints, which can be quantified and used to esti...

Machine learning and clinical epigenetics: a review of challenges for diagnosis and classification.

BACKGROUND: Machine learning is a sub-field of artificial intelligence, which utilises large data se...

The International Conference on Intelligent Biology and Medicine 2019 (ICIBM 2019): computational methods and applications in medical genomics.

In this editorial, we briefly summarized the International Conference on Intelligent Biology and Med...

Deep learning-based cancer survival prognosis from RNA-seq data: approaches and evaluations.

BACKGROUND: Recent advances in kernel-based Deep Learning models have introduced a new era in medica...

A fast conformal predictive system with regularized extreme learning machine.

A conformal predictive system(CPS) is based on the learning framework of conformal prediction, which...

Machine learning, the kidney, and genotype-phenotype analysis.

With biomedical research transitioning into data-rich science, machine learning provides a powerful ...

Meta-Analysis Based on Nonconvex Regularization.

The widespread applications of high-throughput sequencing technology have produced a large number of...

Development of a Bioinformatics Framework for Identification and Validation of Genomic Biomarkers and Key Immunopathology Processes and Controllers in Infectious and Non-infectious Severe Inflammatory Response Syndrome.

Sepsis is defined as dysregulated host response caused by systemic infection, leading to organ failu...

Where medical education meets artificial intelligence: 'Does technology care?'.

'COLD' TECHNOLOGIES AND 'WARM' HANDS-ON MEDICINE NEED TO WALK HAND-IN-HAND: Technologies, such as de...

Estimating gene expression from DNA methylation and copy number variation: A deep learning regression model for multi-omics integration.

Gene expression analysis plays a significant role for providing molecular insights in cancer. Variou...

Brain MRI analysis using a deep learning based evolutionary approach.

Convolutional neural network (CNN) models have recently demonstrated impressive performance in medic...