PiTE: TCR-epitope Binding Affinity Prediction Pipeline using Transformer-based Sequence Encoder.

Accurate prediction of TCR binding affinity to a target antigen is important for development of immunotherapy strategies. Recent computational methods were built on various deep neural networks and used the evolutionary-based distance matrix BLOSUM to embed amino acids of TCR and epitope sequences to numeric values. A pre-trained language model of amino acids is an alternative embedding method where each amino acid in a peptide is embedded as a continuous numeric vector.

ATM-TCR: TCR-Epitope Binding Affinity Prediction Using a Multi-Head Self-Attention Model.

TCR-epitope pair binding is the key component for T cell regulation. The ability to predict whether a given pair binds is fundamental to understanding the underlying biology of the binding mechanism as well as developing T-cell mediated immunotherapy approaches. The advent of large-scale public databases containing TCR-epitope binding pairs enabled the recent development of computational prediction methods for TCR-epitope binding.

A mixture model to detect edges in sparse co-expression graphs with an application for comparing breast cancer subtypes.

We develop a method to recover a gene network's structure from co-expression data, measured in terms of normalized Pearson's correlation coefficients between gene pairs. We treat these co-expression measurements as weights in the complete graph in which nodes correspond to genes. To decide which edges exist in the gene network, we fit a three-component mixture model such that the observed weights of 'null edges' follow a normal distribution with mean 0, and the non-null edges follow a mixture of two lognormal distributions, one for positively- and one for negatively-correlated pairs.

Multiview Cluster Analysis Identifies Variable Corticosteroid Response Phenotypes in Severe Asthma.

Corticosteroids (CSs) are the most effective asthma therapy, but responses are heterogeneous and systemic CSs lead to long-term side effects. Therefore, an improved understanding of the contributing factors in CS responses could enhance precision management. Although several factors have been associated with CS responsiveness, no integrated/cluster approach has yet been undertaken to identify differential CS responses.

Phosphoproteomic Analysis of the Amygdala Response to Adolescent Glucocorticoid Exposure Reveals G-Protein Coupled Receptor Kinase 2 as a Target for Reducing Motivation for Alcohol.

Early life stress is associated with risk for developing alcohol use disorders (AUDs) in adulthood. Though the neurobiological mechanisms underlying this vulnerability are not well understood, evidence suggests that aberrant glucocorticoid and noradrenergic system functioning play a role. The present study investigated the long-term consequences of chronic exposure to elevated glucocorticoids during adolescence on the risk of increased alcohol-motivated behavior, and on amygdalar function in adulthood.

Ethnic variability in the allelic distribution of pharmacogenes between Korean and other populations.

Objective: We examined the differences in allele frequencies for pharmacogenes among the Korean (KOR), Chinese (CHB), Japanese (JPT), Caucasian (CEU), and Nigerian (YRI) populations.

Methods: Fifty-seven pharmacogenes were selected from the imputed Korean Association REsource and HapMap databases. Minor allele frequencies were analyzed using the sample size-modified single nucleotide polymorphism-specific fixation index (FST) and the χ-test with Bonferroni's correction.