COVID-19

Uncovering Thousands of New Peptides with Sequence-Mask-Search Hybrid Peptide Sequencing Framework.

Typical analyses of mass spectrometry data only identify amino acid sequences that exist in reference databases. This restricts the possibility of discovering new peptides such as those that contain uncharacterized mutations or originate from unexpected processing of RNAs and proteins. peptide sequencing approaches address this limitation but often suffer from low accuracy and require extensive v...

Detection of malaria parasites in dried human blood spots using mid-infrared spectroscopy and logistic regression analysis.

BACKGROUND: Epidemiological surveys of malaria currently rely on microscopy, polymerase chain reaction assays (PCR) or rapid diagnostic test kits for Plasmodium infections (RDTs). This study investigated whether mid-infrared (MIR) spectroscopy coupled with supervised machine learning could constitute an alternative method for rapid malaria screening, directly from dried human blood spots.

Making Sense of Pharmacovigilance and Drug Adverse Event Reporting: Comparative Similarity Association Analysis Using AI Machine Learning Algorithms in Dogs and Cats.

Drug-associated adverse events cause approximately 30 billion dollars a year of added health care expense, along with negative health outcomes includi...

Interpretation of Compound Activity Predictions from Complex Machine Learning Models Using Local Approximations and Shapley Values.

In qualitative or quantitative studies of structure-activity relationships (SARs), machine learning (ML) models are trained to recognize structural pa...

Integrating joint feature selection into subspace learning: A formulation of 2DPCA for outliers robust feature selection.

Since the principal component analysis and its variants are sensitive to outliers that affect their performance and applicability in real world, sever...

Optimized CRISPR guide RNA design for two high-fidelity Cas9 variants by deep learning.

Highly specific Cas9 nucleases derived from SpCas9 are valuable tools for genome editing, but their wide applications are hampered by a lack of knowle...

Machine-Learning Prediction of Tumor Antigen Immunogenicity in the Selection of Therapeutic Epitopes.

Current tumor neoantigen calling algorithms primarily rely on epitope/major histocompatibility complex (MHC) binding affinity predictions to rank and ...

Cortical Tracking of Surprisal during Continuous Speech Comprehension.

Speech comprehension requires rapid online processing of a continuous acoustic signal to extract structure and meaning. Previous studies on sentence c...

Monitoring bioactive and total antibody concentrations for continuous process control by surface plasmon resonance spectroscopy.

Monoclonal antibodies have become an increasingly important part of fundamental research and medical applications. To meet the high market demand for ...

Artificial intelligence and avian influenza: Using machine learning to enhance active surveillance for avian influenza viruses.

Influenza A viruses are one of the most significant viral groups globally with substantial impacts on human, domestic animal and wildlife health. Wild...

Neural-network classification of cardiac disease from P cardiovascular magnetic resonance spectroscopy measures of creatine kinase energy metabolism.

BACKGROUND: The heart's energy demand per gram of tissue is the body's highest and creatine kinase (CK) metabolism, its primary energy reserve, is com...

Cytokeratin-Supervised Deep Learning for Automatic Recognition of Epithelial Cells in Breast Cancers Stained for ER, PR, and Ki-67.

Immunohistochemistry (IHC) of ER, PR, and Ki-67 are routinely used assays in breast cancer diagnostics. Determination of the proportion of stained cel...

Single T Cell Sequencing Demonstrates the Functional Role of TCR Pairing in Cell Lineage and Antigen Specificity.

Although structural studies of individual T cell receptors (TCRs) have revealed important roles for both the α and β chain in directing MHC and antige...

Mechanistic interpretation of non-coding variants for discovering transcriptional regulators of drug response.

BACKGROUND: Identification of functional non-coding variants and their mechanistic interpretation is a major challenge of modern genomics, especially ...

Region-of-interest undersampled MRI reconstruction: A deep convolutional neural network approach.

Compressive sensing enables fast magnetic resonance imaging (MRI) reconstruction with undersampled k-space data. However, in most existing MRI reconst...

Use of Social Robots in Mental Health and Well-Being Research: Systematic Review.

BACKGROUND: Technology-assisted clinical interventions are increasingly common in the health care field, often with the proposed aim to improve access...

Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans.

We aim at segmenting a wide variety of organs, including tiny targets (e.g., adrenal gland), and neoplasms (e.g., pancreatic cyst), from abdominal CT ...

A New Nonlinear Sparse Component Analysis for a Biologically Plausible Model of Neurons.

It is known that brain can create a sparse representation of the environment in both sensory and mnemonic forms (Olshausen & Field, 2004). Such sparse...

Recurrent transform learning.

Recurrent neural networks (RNN) model time series by feeding back the representation from the previous time instant as an input for the current instan...

Predicting toxicity of chemicals: software beats animal testing.

We created earlier a large machine-readable database of 10,000 chemicals and 800,000 associated studies by natural language processing of the public p...