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Full text 2026

Investigating the Pleiotropic Role of KIF21B in Schizophrenia and Multiple Sclerosis: A Bioinformatics Analysis

Korkmaz ED, Everest E.

<h4>Objective</h4>Genome-wide association studies have identified shared genetic risk loci between schizophrenia (SCZ) and multiple sclerosis (MS), suggesting overlapping biological mechanisms despite distinct clinical presentations. Here, we aimed to characterize the biological plausibility of <i>KIF21B</i> as …

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Bioinformatics Transcriptomics
Full text 2026

Single-cell sequencing and machine learning-based prediction of spliceosome-associated factor 2 may represent potential targets for osteoarthritis

Yang B, Li X, Su Y.

<h4>Background</h4>Osteoarthritis has become a global health challenge due to its complex pathologic mechanisms. Spliceosome-associated factor 2 (SYF2) has been reported in tumors and neurological diseases, but not in studies of osteoarthritis. We employed single-cell sequencing …

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Bioinformatics Single-Cell
Full text 2026

Upregulation of RPLP1 in PBMCs as a screening biomarker for melanoma

Wuttithantawee Y, Wuttithantawee A, Wuttithantawee R, et al.

Early detection of melanoma is essential for improving patient outcomes. This research aimed to identify upregulated gene expression in peripheral blood mononuclear cells (PBMCs) induced by secretory factors derived from melanoma cells. These gene alterations …

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Bioinformatics
Full text 2026

The impact of biologically relevant negative samples on machine learning-based B-cell epitope prediction for Influenza A

Pareja-Barrueto C, Reyes-Suarez J, Del Canto F, et al.

<h4>Motivation</h4>Predicting linear B-cell epitopes remains a major challenge in immunoinformatics, particularly for rapidly evolving viruses such as Influenza A. Many existing predictors rely on heterogeneous training datasets, poorly defined negative samples, or low-interpretability models, which …

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Bioinformatics
Full text 2026

GPTBioInsightor-leveraging large language models for transparent scRAN-seq cell type annotations

Huang S, Šabanović B, Peng Y, et al.

<h4>Motivation</h4>Large language models (LLMs) are rapidly becoming indispensable across the life‑sciences spectrum, from literature mining through clinical decision support to experimental design. Yet, in single‑cell RNA‑sequencing (scRNA‑seq) analysis, most LLM‑enabled tools remain opaque: they output …

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Bioinformatics Single-Cell
Full text 2026

An &lt;i&gt;in silico&lt;/i&gt; bioinformatics framework for prioritizing candidate genes in the coronary no-reflow phenomenon

Rahman FA, Suryono S, Maulana AS, et al.

<b>Background:</b> The coronary no-reflow phenomenon remains a major obstacle to optimal outcomes after primary percutaneous coronary intervention. Its mechanisms are multifactorial and not fully clarified, with genetic components increasingly recognized as important contributors. This study …

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Bioinformatics
Full text 2026

MRDviz: an integrated platform for interactive visualization and joint simulation of minimal residual disease trajectories and associated survival outcomes

Choi K, Zhao K, Mohammad TA, et al.

<h4>Motivation</h4>Minimal residual disease (MRD) assessment has become a powerful tool in modern cancer management, offering early, actionable insights across diverse malignancies and often anticipating clinical events traditionally used to gauge therapeutic response. Beyond quantifying residual …

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Bioinformatics