Allergy & Immunology

A Multi-Omics Interpretable Machine Learning Model Reveals Modes of Action of Small Molecules.

High-throughput screening and gene signature analyses frequently identify lead therapeutic compounds...

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 mole...

Multifactorial Deep Learning Reveals Pan-Cancer Genomic Tumor Clusters with Distinct Immunogenomic Landscape and Response to Immunotherapy.

PURPOSE: Tumor genomic features have been of particular interest because of their potential impact o...

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

Identification of neoantigens is a critical step in predicting response to checkpoint blockade thera...

A modern approach to identifying and characterizing child asthma and wheeze phenotypes based on clinical data.

'Asthma' is a complex disease that encapsulates a heterogeneous group of phenotypes and endotypes. R...

Machine Learning Characterization of COPD Subtypes: Insights From the COPDGene Study.

COPD is a heterogeneous syndrome. Many COPD subtypes have been proposed, but there is not yet consen...

Vitamin D and Serum Immunoglobulin E Levels in Allergic Rhinitis: A Case-control Study from Pakistan.

Introduction Allergic rhinitis (AR) is the most common non-infectious rhinitis and is associated wit...

Membranous Nephropathy with Rapid Progression.

We report a 49-year-old man with microscopic hematuria, subnephrotic proteinuria, and rapidly progre...

Artificial intelligence approaches using natural language processing to advance EHR-based clinical research.

The wide adoption of electronic health record systems in health care generates big real-world data t...

The doctor will see you now: How machine learning and artificial intelligence can extend our understanding and treatment of asthma.

High-Throughput Prediction of MHC Class I and II Neoantigens with MHCnuggets.

Computational prediction of binding between neoantigen peptides and major histocompatibility complex...

Identification of Catecholamine Neurotransmitters Using a Fluorescent Electronic Tongue.

Catecholamine neurotransmitters, specifically, dopamine (DA), epinephrine (EP), and norepinephrine (...

Machine learning for the detection of early immunological markers as predictors of multi-organ dysfunction.

The immune response to major trauma has been analysed mainly within post-hospital admission settings...

Absolute quantitation of high abundant Fc-glycopeptides from human serum IgG-1.

Absolute quantitation of IgG-1 Fc-glycosylation, which is crucial for the clinical practice of glyco...

In vitro selection of DNA aptamers and their integration in a competitive voltammetric biosensor for azlocillin determination in waste water.

The uncontrolled usage of veterinary antibiotics has led to their widespread pollution in waterways ...

Classifying T cell activity in autofluorescence intensity images with convolutional neural networks.

The importance of T cells in immunotherapy has motivated developing technologies to improve therapeu...

Efficient expression of EpEX in the cytoplasm of using thioredoxin fusion protein.

Recombinant epithelial cell adhesion molecule extracellular domain (EpEX) has a high potential as a ...

Machine learning approach to single nucleotide polymorphism-based asthma prediction.

Machine learning (ML) is poised as a transformational approach uniquely positioned to discover the h...

The use of natural language processing to identify vaccine-related anaphylaxis at five health care systems in the Vaccine Safety Datalink.

PURPOSE: The objective was to develop a natural language processing (NLP) algorithm to identify vacc...

Inverse association between infection and childhood asthma in Greece: a case-control study.

INTRODUCTION: infection is a well-established etiological factor for a variety of diseases such as ...

A gastric cancer LncRNAs model for MSI and survival prediction based on support vector machine.

BACKGROUND: Recent studies have shown that long non-coding RNAs (lncRNAs) play a crucial role in the...