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BioMedInformatics, Volume 6, Issue 3

2026 June - 15 articles

Cover Story: Gliomas are highly heterogeneous brain tumors, making accurate classification and treatment selection challenging. We introduce MOHVAE-B, a multi-omics integration framework (TCGA data) for biomarker discovery. It employs a supervised hierarchical variational autoencoder (H-VAE) combined with SHAP-based interpretability to extract influential molecular features. Bayesian Networks then model their conditional dependencies to reveal biological mechanisms. We identified several novel biomarker candidates for glioblastoma, including NACA2, LINC01114, and LINC01558, and AMER2 for low-grade gliomas. This study offers an interpretable approach to uncovering the complex molecular landscape of brain tumors. View this paper
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Articles (15)

  • Article
  • Open Access
1,365 Views
14 Pages

Immunohistochemistry (IHC) is a widely used method for detecting specific proteins in tissue samples, helping diagnose diseases such as cancer. Traditional analysis methods rely heavily on human interpretation, which can lead to inconsistencies. In t...

(This article belongs to the Section Imaging Informatics)
  • Article
  • Open Access
1 Citations
1,205 Views
18 Pages

Lung cancer is the deadliest cause of cancer-related deaths worldwide, and early and accurate detection is key to improving patient outcomes. IQ-OTH/NCCD CT scan images are used in this study to present an optimized computer-aided diagnosis (CAD) fra...

(This article belongs to the Special Issue Integrating Health Informatics and Artificial Intelligence for Advanced Medicine)
  • Tutorial
  • Open Access
3 Citations
2,316 Views
21 Pages

Heterogeneity is central to the credibility, transportability, and clinical interpretation of meta-analytic evidence, yet its assessment is frequently reduced to isolated or misinterpreted statistics. This tutorial provides a clinically oriented fram...

(This article belongs to the Section Medical Statistics and Data Science)
  • Article
  • Open Access
2 Citations
1,463 Views
10 Pages

A Machine Learning and Deep Learning Approach for the Classification of Thyroid Disorders Using Multi-Source Clinical Data

  • Kypros Andreou,
  • Eleftherios Georgakopoulos,
  • Costas Toufexis,
  • Nikos L. Papaloizou and ,
  • Themis P. Exarchos,
  • Panagiotis Vlamos and
  • Marios G. Krokidis
  • + 2 authors+ 0 author

The increasing prevalence of autoimmune thyroid diseases and thyroid cancer highlights the urgent need for improved diagnostic support approaches. Traditional diagnostic methods often rely primarily on biochemical markers or qualitative imaging evalu...

(This article belongs to the Section Applied Biomedical Data Science)
  • Article
  • Open Access
1,265 Views
19 Pages

Electrocardiogram (ECG) arrhythmia classification remains critical for automated cardiac diagnosis, yet feature extraction methods are frequently adopted without systematic comparative evaluation. This study presents a controlled comparative analysis...

(This article belongs to the Topic Machine Learning, Optimization, and Computational Methods in Biomedical Informatics)
  • Article
  • Open Access
761 Views
15 Pages

Causal Graphical Models for Transition from Healthy Vaginal Microbiota to Bacterial Vaginosis in Pregnant Women

  • Maricela García-Avalos,
  • Juana Canul-Reich,
  • Lil María Xibai Rodríguez-Henríquez and
  • Erick Natividad De la Cruz-Hernández

This study developed two Causal Graphical Models (CGMs) to analyze the transitions associated with Bacterial Vaginosis (BV) and to identify key bacterial species at each stage. BV results from an imbalance in the vaginal microbiota, whose composition...

(This article belongs to the Topic Artificial Intelligence and Big Data in Biomedical Engineering)
  • Article
  • Open Access
1,310 Views
24 Pages

Gliomas represent the most prevalent type of brain tumor, with their most aggressive variant, glioblastoma multiforme, associated with high mortality rates. Due to their elevated molecular heterogeneity, accurate classification of gliomas has present...

(This article belongs to the Section Computational Biology and Medicine)
  • Review
  • Open Access
1,034 Views
16 Pages

Role of Artificial Neural Networks in Optimizing Bioconversion of Antiretroviral Drugs: A Review

  • Nelson T. Tsotetsi,
  • Ndiwanga F. Rasifudi,
  • Beauty Magage and
  • Lukhanyo Mekuto

Antiretroviral drugs (ARVDs) remain the cornerstone of HIV/AIDS management, but their therapeutic efficacy and safety are highly influenced by bioconversion processes such as hepatic metabolism and enzymatic transformation. Variability in metabolic p...

(This article belongs to the Special Issue Advances in Structural Bioinformatics and Next-Generation Sequence Analysis for Drug Design)
  • Article
  • Open Access
1,699 Views
19 Pages

Background: Targeting Apolipoprotein E4 (ApoE4) represents a frontier in Alzheimer’s disease therapeutics. This study investigates the therapeutic potential of a nutraceutical panel (Polydatin, trans-resveratrol, luteolin, and PEA) by exploring...

(This article belongs to the Section Computational Biology and Medicine)
  • Systematic Review
  • Open Access
2,088 Views
15 Pages

Clinical Outcomes of Daratumumab-Containing Regimens in Multiple Myeloma: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

  • Sara O. Elgendy,
  • Mohamed S. Imam,
  • Amal Ali Mohammed Alshehri,
  • Wejdan Zaed Ali Alsufyani and ,
  • Maha Eid Albogami,
  • Sumayyah Abdullah Saeed Almalki,
  • Maya Nammas M. Alkhaldi,
  • Majdolene Wael Abdulfattah Samarkandi,
  • Demah Turki Yaqoub Alibrahim and
  • Rehab M. Abd-Elkareem
  • + 10 authors+ 5 authors

Background: This study examines the clinical efficacy of daratumumab when combined with other therapeutic agents in patients with multiple myeloma, with a focus on key outcomes including overall response, progression-free survival (PFS), and stringen...

(This article belongs to the Topic Myeloma and Leukemia—Challenges and Current Treatment Options: 2nd Edition)
  • Article
  • Open Access
1 Citations
8,899 Views
24 Pages

Efficient Visual Field Sensitivity Estimation via a Lightweight Global Context-Aware CNN Using Standard 2D OCT Thickness Maps

  • Shamsudeen Abdullahi,
  • Yuttapong Jiraraksopakun,
  • Apichai Bhatranand,
  • Anita Manassakorn and ,
  • Sunee Chansangpetch,
  • Kitiya Ratanawongphaibul and
  • Visanee Tantisevi
  • + 2 authors+ 0 author

Glaucoma is a chronic progressive optic neuropathy causing irreversible blindness globally, underscoring the need for reliable diagnostic tools. While visual field (VF) testing remains the clinical standard, it has significant limitations, including...

(This article belongs to the Topic Artificial Intelligence and Big Data in Biomedical Engineering)
  • Article
  • Open Access
1,643 Views
27 Pages

A Computational Framework for Analyzing Calcium Signals Reveals Edema-Induced Transitions in Cardiac Calcium-Handling Dynamics

  • Diana G. Kiseleva,
  • Maria A. Kazakova,
  • Tatiana Yu. Plyusnina,
  • Yuliya V. Markina and
  • Alexander M. Markin

Myocardial edema is associated with cardiac electrical instability, but the cellular mechanisms linking osmotic cell swelling to arrhythmias remain unclear. Hypoosmotic conditions are hypothesized to drive transitions between dynamical regimes (e.g.,...

(This article belongs to the Section Computational Biology and Medicine)
  • Article
  • Open Access
4 Citations
2,215 Views
26 Pages

Early Diagnosis of Blood Disorders via Enhanced Image Preprocessing and Deep Learning Modeling

  • Alpamis Kutlimuratov,
  • Dilshod Eshmurodov,
  • Fotima Tulaganova,
  • Akhmet Utegenov and ,
  • Piratdin Allayarov,
  • Jamshid Khamzaev,
  • Islambek Saymanov and
  • Fazliddin Makhmudov
  • + 3 authors+ 0 author

Background: Accurate and early detection of hematological disorders from microscopic peripheral blood smear images remains a technically challenging task due to inherent imaging limitations, including noise contamination, low contrast, staining varia...

(This article belongs to the Special Issue Integrating Health Informatics and Artificial Intelligence for Advanced Medicine)
  • Article
  • Open Access
1 Citations
1,536 Views
15 Pages

Background: Hemagglutinin (HA) is the primary surface protein of the influenza A virus, determining its subtype and antigenic properties. Traditional subtype classification methods rely on DNA or amino acid sequence analysis, which does not account f...

(This article belongs to the Special Issue AI Frontiers in Computational Protein Engineering and Structural Bioinformatics)
  • Article
  • Open Access
1,947 Views
30 Pages

The EGR1-FOS Transcriptional Axis in Liver Fibrosis: An Integrated Bioinformatic Analysis of Disease Progression and Shared Molecular Signatures in Cirrhosis

  • Youssef Nadir,
  • Hicham Esselmani,
  • Anass Oukhdouch,
  • Habiba Nechchadi and ,
  • Rahma Ennadi,
  • Mohammed Amine Lkousse,
  • Issame Farouk,
  • Mustapha Najimi and
  • Mohamed Merzouki
  • + 4 authors+ 0 author

Background: Liver fibrosis arises from chronic liver injury and remains a major clinical challenge due to its progression toward cirrhosis and hepatocellular carcinoma, as well as the absence of approved antifibrotic therapies. This study aimed to ch...

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BioMedInformatics - ISSN 2673-7426