AI Medical Compendium Journal:
GigaScience

Showing 31 to 40 of 69 articles

Accurate and fast clade assignment via deep learning and frequency chaos game representation.

GigaScience
BACKGROUND: Since the beginning of the coronavirus disease 2019 pandemic, there has been an explosion of sequencing of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus, making it the most widely sequenced virus in the history. S...

Defining the characteristics of interferon-alpha-stimulated human genes: insight from expression data and machine learning.

GigaScience
BACKGROUND: A virus-infected cell triggers a signalling cascade, resulting in the secretion of interferons (IFNs), which in turn induces the upregulation of the IFN-stimulated genes (ISGs) that play a role in antipathogen host defence. Here, we condu...

Disease classification for whole-blood DNA methylation: Meta-analysis, missing values imputation, and XAI.

GigaScience
BACKGROUND: DNA methylation has a significant effect on gene expression and can be associated with various diseases. Meta-analysis of available DNA methylation datasets requires development of a specific workflow for joint data processing.

DeePVP: Identification and classification of phage virion proteins using deep learning.

GigaScience
BACKGROUND: Many biological properties of phages are determined by phage virion proteins (PVPs), and the poor annotation of PVPs is a bottleneck for many areas of viral research, such as viral phylogenetic analysis, viral host identification, and ant...

SurvBenchmark: comprehensive benchmarking study of survival analysis methods using both omics data and clinical data.

GigaScience
Survival analysis is a branch of statistics that deals with both the tracking of time and the survival status simultaneously as the dependent response. Current comparisons of survival model performance mostly center on clinical data with classic stat...

A Decade of GigaScience: The Challenges of Gigapixel Pathology Images.

GigaScience
In the last decade, the field of computational pathology has advanced at a rapid pace because of the availability of deep neural networks, which achieved their first successes in computer vision tasks in 2012. An important driver for the progress of ...

Profiling the baseline performance and limits of machine learning models for adaptive immune receptor repertoire classification.

GigaScience
BACKGROUND: Machine learning (ML) methodology development for the classification of immune states in adaptive immune receptor repertoires (AIRRs) has seen a recent surge of interest. However, so far, there does not exist a systematic evaluation of sc...

Benchmarking missing-values approaches for predictive models on health databases.

GigaScience
BACKGROUND: As databases grow larger, it becomes harder to fully control their collection, and they frequently come with missing values. These large databases are well suited to train machine learning models, e.g., for forecasting or to extract bioma...

How to remove or control confounds in predictive models, with applications to brain biomarkers.

GigaScience
BACKGROUND: With increasing data sizes and more easily available computational methods, neurosciences rely more and more on predictive modeling with machine learning, e.g., to extract disease biomarkers. Yet, a successful prediction may capture a con...

Population modeling with machine learning can enhance measures of mental health.

GigaScience
BACKGROUND: Biological aging is revealed by physical measures, e.g., DNA probes or brain scans. In contrast, individual differences in mental function are explained by psychological constructs, e.g., intelligence or neuroticism. These constructs are ...