Genetics

Next-generation drug repurposing using human genetics and network biology.

Drug repurposing has attracted increased attention, especially in the context of drug discovery rates that remain too low despite a recent wave of approvals for biological therapeutics (e.g. gene therapy). These new biological entities-based treatments have high costs that are difficult to justify for small markets that include rare diseases. Drug repurposing, involving the identification of singl...

Prognostic factors of Rapid symptoms progression in patients with newly diagnosed parkinson's disease.

Tracking symptoms progression in the early stages of Parkinson's disease (PD) is a laborious endeavor as the disease can be expressed with vastly different phenotypes, forcing clinicians to follow a multi-parametric approach in patient evaluation, looking for not only motor symptomatology but also non-motor complications, including cognitive decline, sleep problems and mood disturbances. Being neu...

Pilot Study to Establish a Novel Five-Gene Biomarker Panel for Predicting Lymph Node Metastasis in Patients With Early Stage Endometrial Cancer.

In the United States and Europe, endometrial endometrioid carcinoma (EEC) is the most prevalent gynecologic malignancy. Lymph node metastasis (LNM) i...

Artificial Intelligence for Cardiac Imaging-Genetics Research.

Cardiovascular conditions remain the leading cause of mortality and morbidity worldwide, with genotype being a significant influence on disease risk. ...

Incorporating biological structure into machine learning models in biomedicine.

In biomedical applications of machine learning, relevant information often has a rich structure that is not easily encoded as real-valued predictors. ...

Integrating Computational Methods to Investigate the Macroecology of Microbiomes.

Studies in microbiology have long been mostly restricted to small spatial scales. However, recent technological advances, such as new sequencing metho...

Prediction of pathological complete response to neoadjuvant chemotherapy in breast cancer using a deep learning (DL) method.

BACKGROUND: The aim of the study was to develop a deep learning (DL) algorithm to evaluate the pathological complete response (pCR) to neoadjuvant che...

Characterizing Protein-Ligand Binding Using Atomistic Simulation and Machine Learning: Application to Drug Resistance in HIV-1 Protease.

Over the past several decades, atomistic simulations of biomolecules, whether carried out using molecular dynamics or Monte Carlo techniques, have pro...

Integrated Hypothalamic Transcriptome Profiling Reveals the Reproductive Roles of mRNAs and miRNAs in Sheep.

Early studies have provided a wealth of information on the functions of microRNAs (miRNAs). However, less is known regarding their functions in the hy...

Machine learning workflows to estimate class probabilities for precision cancer diagnostics on DNA methylation microarray data.

DNA methylation data-based precision cancer diagnostics is emerging as the state of the art for molecular tumor classification. Standards for choosing...

VAMPr: VAriant Mapping and Prediction of antibiotic resistance via explainable features and machine learning.

Antimicrobial resistance (AMR) is an increasing threat to public health. Current methods of determining AMR rely on inefficient phenotypic approaches,...

Gait characteristics and clinical relevance of hereditary spinocerebellar ataxia on deep learning.

BACKGROUND: Deep learning has always been at the forefront of scientific research. It has also been applied to medical research. Hereditary spinocereb...

pVACtools: A Computational Toolkit to Identify and Visualize Cancer Neoantigens.

Identification of neoantigens is a critical step in predicting response to checkpoint blockade therapy and design of personalized cancer vaccines. Thi...

R/PY-SUMMA: An R/Python Package for Unsupervised Ensemble Learning for Binary Classification Problems in Bioinformatics.

The increasing availability of complex data in biology and medicine has promoted the use of machine learning in classification tasks to address import...

A Multiple-Instance Learning-Based Convolutional Neural Network Model to Detect the Mutation in the Histopathology Images of Glioma Tissues.

Robust Prediction of Single and Multiple Point Protein Mutations Stability Changes.

Accurate prediction of protein stability changes resulting from amino acid substitutions is of utmost importance in medicine to better understand whic...

Polymorphism Is Associated with Impaired Oral Clearance of Gliclazide in Healthy Chinese.

BACKGROUND: Previous studies suggest gliclazide is metabolised primarily by CYP2C19 rather than CYP2C9, unlike other sulphonylureas. and polymorphis...

DNA is not an ontologically distinctive developmental cause.

In this article I critically evaluate the thesis that DNA is an ontologically distinctive developmental cause. I shall critically analyse different ve...

The sweet detection of rolling circle amplification: Glucose-based electrochemical genosensor for the detection of viral nucleic acid.

Herein, an isothermal padlock probe-based assay for the simple and portable detection of pathogens coupled with a glucose oxidase (GOx)-based electroc...

Prediction of IDH and TERT promoter mutations in low-grade glioma from magnetic resonance images using a convolutional neural network.

Identification of genotypes is crucial for treatment of glioma. Here, we developed a method to predict tumor genotypes using a pretrained convolutiona...