Variable heavy (VH) and variable light (VL) chain pairing is a critical determinant of antibody diversity, stability, and antigen-binding specificity. Identifying productive VH - VL combinations experimentally is labor-intensive and costly, motivatin...
Embedding is the key step in single-cell Hi-C (scHi-C) analysis which relies on capturing biological meaningful heterogeneity at various levels of genome architecture. To understand the strength and limitations of existing tools in various applicatio...
This study establishes a novel framework for systematically evaluating the moral reasoning capabilities of large language models (LLMs) as they increasingly integrate into critical societal domains. Current assessment methodologies lack the precision...
Journal of chemical information and modeling
Sep 25, 2025
The rapid emergence of drug resistance in viral infections represents a significant global health challenge, threatening the efficacy of treatments for multiple diseases. Machine learning models have emerged as valuable tools for predicting antiviral...
BACKGROUND: Adaptive sampling is an emerging technology to enrich target reads while depleting unwanted reads during real-time nanopore sequencing. The application of different algorithms has spawned various tools for the determination of read reject...
Journal of the American College of Surgeons
Sep 16, 2025
BACKGROUND: Because of technical limitations inherent to logistic regression, NSQIP benchmarking has historically risk adjusted for procedure using only 1 principal CPT code among other predictors. This has the potential to create bias (favorable or ...
Journal of chemical information and modeling
Sep 11, 2025
Protein-nucleic acid interactions are fundamental to biological processes and biotechnology, yet their computational prediction lags behind protein structure or protein-protein interaction modeling. This study introduces ProNASet, a benchmark data se...
Journal of cancer research and clinical oncology
Sep 10, 2025
PURPOSE: The study aims to compare the treatment recommendations generated by four leading large language models (LLMs) with those from 21 sarcoma centers' multidisciplinary tumor boards (MTBs) of the sarcoma ring trial in managing complex soft tissu...
In radiomics, feature selection methods are primarily used to eliminate redundant features and identify relevant ones. Feature projection methods, such as principal component analysis (PCA), are often avoided due to concerns that recombining features...
The evolution of Large Language Models (LLMs) has significantly advanced artificial intelligence, driving innovation across various applications. Their continued development relies on a deep understanding of their capabilities and limitations. This i...
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