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Advances in Bioinformatics of Human Diseases
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Advances in Bioinformatics of Human Diseases

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Bioinformatics".

Deadline for manuscript submissions: 15 October 2025 | Viewed by 4792

Special Issue Editor

Dr. Hongyan Xu

E-Mail Website
Guest Editor
Department of Population Health Sciences, Augusta University, Augusta, GA 30912-4900, USA
Interests: statistial genetics; genomics; bioinformatics; population genetics; data science
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Bioinformatics is a scientific discipline that involves the use of computers to collect, store, and analyze information about biological data, including DNA and amino acid sequences or annotations about sequences. Bioinformatics is an important discipline for life science research today. The goal of this research branch is to reveal the complexity of genome information structure and the fundamental laws of genetic language, as well as to clarify the structure, function, interaction, and relationship between human proteins and various human diseases, seeking a variety of therapeutic and preventive measures.

Given the significant potential of bioinformatics to understand human disease, this Special Issue invites researchers to publish their work on bioinformatics analysis methods for disease identification, classification, diagnosis, and prognosis that address the current advances in bioinformatics relating to human diseases. If you would like more information about the Special Issue, please feel free to contact us.

Dr. Hongyan Xu
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Genes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • bioinformatics
  • human disease
  • sequencing
  • gene expression analysis
  • analysis methods
  • proteomics analysis
  • metabolomics analysis
  • microbiome analysis

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Published Papers (4 papers)

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Research

27 pages, 6302 KB  
Article
Identification of Key PANoptosis Regulators in Periodontitis and Chronic Obstructive Pulmonary Disease Using Gene Expression and Machine Learning Methods
by Suheyla Kaya, Nail Besli and Ilhan Onaran
Genes 2025, 16(9), 1027; https://doi.org/10.3390/genes16091027 - 29 Aug 2025
Viewed by 598
Abstract
Background: Periodontitis (PD) is a chronic inflammatory disease associated with systemic conditions such as chronic obstructive pulmonary disease (COPD). PANoptosis—a form of regulated cell death integrating pyroptosis, apoptosis, and necroptosis—has been implicated in inflammatory diseases, but its role in PD and its overlap [...] Read more.
Background: Periodontitis (PD) is a chronic inflammatory disease associated with systemic conditions such as chronic obstructive pulmonary disease (COPD). PANoptosis—a form of regulated cell death integrating pyroptosis, apoptosis, and necroptosis—has been implicated in inflammatory diseases, but its role in PD and its overlap with COPD is not well understood. Methods: Gene expression datasets for PD and COPD were retrieved from the Gene Expression Omnibus (GEO). Differentially expressed genes were intersected with 78 PANoptosis-related genes. Functional enrichment (GO, KEGG), protein–protein interaction (PPI) network analysis, and machine learning (XGBoost with ROC curves) identified key regulatory genes. Immune infiltration was evaluated, and drug–gene interactions were analyzed using DGIDB. Results: Seven PANoptosis-related core genes—ACO1, NLRC4, CASP8, HSPA4, IL1B, MEFV, and CYCS—were identified in both PD and COPD. These genes were enriched in pathways involving inflammasomes, apoptosis, and oxidative stress. Immune analysis showed significant differences in B cells, T cells, dendritic cells, and plasma cells. Potential drug targets, including IL1B and CASP8, were identified. Conclusions: This is the first study to link PANoptosis to both PD and COPD. The findings reveal shared molecular mechanisms and suggest PANoptosis-related genes as novel biomarkers and therapeutic targets in chronic inflammatory oral disease. Full article
(This article belongs to the Special Issue Advances in Bioinformatics of Human Diseases)
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18 pages, 10372 KB  
Article
Alternative Splicing of Serum Response Factor Reveals Isoform-Specific Remodeling in Cardiac Diseases
by Sayed Aliul Hasan Abdi, Gohar Azhar, Xiaomin Zhang, Shakshi Sharma, Mohib Hafeez and Jeanne Y. Wei
Genes 2025, 16(8), 947; https://doi.org/10.3390/genes16080947 - 11 Aug 2025
Viewed by 832
Abstract
Background: Alternative splicing is an important mechanism of transcriptomic and proteomic diversity and is progressively involved in cardiovascular disease (CVD) pathogenesis. Serum response factor (SRF), a critical transcription factor in cardiac development and function, may itself undergo splicing regulation, potentially altering its function [...] Read more.
Background: Alternative splicing is an important mechanism of transcriptomic and proteomic diversity and is progressively involved in cardiovascular disease (CVD) pathogenesis. Serum response factor (SRF), a critical transcription factor in cardiac development and function, may itself undergo splicing regulation, potentially altering its function in disease states. Objective: The objective of this study is to identify SRF-associated alternative splicing events in cardiac pathological conditions and examine regulatory interactions with splicing factors using RNA-seq data. Methods: Three human heart RNA-seq databases (PRJNA198165, PRJNA477855, PRJNA678360) were used, comprising various cardiac conditions like non-ischemic cardiomyopathy (NICM), ischemic cardiomyopathy (ICM), dilated cardiomyopathy (DCM), and heart failure with reduced ejection fraction (HFrEF), with and without left ventricular assist device (LVAD) support. Splicing events were identified using the rMATS tool, and correlation analyses were performed between SRF and predicted splicing factors. Functional enrichment of SRF-correlated genes was assessed via Gene Ontology (GO) and KEGG pathways. Results: The skipped exon (SE) events were the predominant splicing type across all datasets. SRF chr6, including (Exon 2, 43,173,847–43,174,113), (Exon 4, 43,176,548–43,176,667), and (Exon 5, 43,178,294-43,178,485), were most frequently involved in SE and mutually exclusive exon (MXE) events across multiple heart failure subtypes. Correlation analysis revealed strong positive associations between SRF and several splicing factors (HNRNPL, HNRNPD, SRSF5, and SRSF8). GO and KEGG analyses revealed enrichment of muscle development, sarcomere structure, lipid metabolism, and immune signaling pathways. Conclusions: Our study shows that SRF is subject to extensive alternative splicing in heart failure, particularly at Exon 2 and Exon 5, suggesting isoform-specific roles in cardiac remodeling. The strong co-expression with specific splicing factors delineates a regulatory axis that may explain the pathological transcriptome in cardiomyopathy. These findings provide a foundation for exploring splicing-based biomarkers and therapeutic targets in cardiac pathology for SRF. Full article
(This article belongs to the Special Issue Advances in Bioinformatics of Human Diseases)
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21 pages, 6501 KB  
Article
Bioinformatics-Driven Identification of Ferroptosis-Related Gene Signatures Distinguishing Active and Latent Tuberculosis
by Rakesh Arya, Hemlata Shakya, Viplov Kumar Biswas, Gyanendra Kumar, Sumendra Yogarayan, Harish Kumar Shakya and Jong-Joo Kim
Genes 2025, 16(6), 716; https://doi.org/10.3390/genes16060716 - 18 Jun 2025
Viewed by 1054
Abstract
Background: Tuberculosis (TB) remains a major global public health challenge, and diagnosing it can be difficult due to issues such as distinguishing active TB from latent TB infection (LTBI), as well as the sample collection process, which is often time-consuming and lacks sensitivity [...] Read more.
Background: Tuberculosis (TB) remains a major global public health challenge, and diagnosing it can be difficult due to issues such as distinguishing active TB from latent TB infection (LTBI), as well as the sample collection process, which is often time-consuming and lacks sensitivity and specificity. Ferroptosis is emerging as an important factor in TB pathogenesis; however, its underlying molecular mechanisms are not fully understood. Thus, there is a critical need to establish ferroptosis-related diagnostic biomarkers for tuberculosis (TB). Methods: This study aimed to identify and validate potential ferroptosis-related genes in TB infection while enhancing clinical diagnostic accuracy through bioinformatics-driven gene identification. The microarray expression profile dataset GSE28623 from the Gene Expression Omnibus (GEO) database was used to identify ferroptosis-related differentially expressed genes (FR-DEGs) associated with TB. Subsequently, these genes were used for immune cell infiltration, Gene Set Enrichment Analysis (GSEA), functional enrichment and correlation analyses. Hub genes were identified using Weighted Gene Co-expression Network Analysis (WGCNA) and validated in independent datasets GSE37250, GSE39940, GSE19437, and GSE31348. Results: A total of 21 FR-DEGs were identified. Among them, four hub genes (ACSL1, PARP9, TLR4, and ATG3) were identified as diagnostic biomarkers. These biomarkers were enriched in immune-response related pathways and were validated. Immune cell infiltration, GSEA, functional enrichment and correlation analyses revealed that multiple immune cell types could be activated by FR-DEGs. Throughout anti-TB therapy, the expression of the four hub gene signatures significantly decreased in patients cured of TB. Conclusions: In conclusion, ferroptosis plays a key role in TB pathogenesis. These four hub gene signatures are linked with TB treatment effectiveness and show promise as biomarkers for differentiating TB from LTBI. Full article
(This article belongs to the Special Issue Advances in Bioinformatics of Human Diseases)
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18 pages, 24028 KB  
Article
Retinol-Binding Protein 4 as a Biomarker in Cancer: Insights from a Pan-Cancer Analysis of Expression, Immune Infiltration, and Methylation
by Jia Zhao, Yaxin Liu, Lingqin Zhou and Yi Liu
Genes 2025, 16(2), 150; https://doi.org/10.3390/genes16020150 - 25 Jan 2025
Cited by 2 | Viewed by 1549
Abstract
Background: Retinol-binding protein 4 (RBP4) is primarily recognized for its role in retinoid transport, but has recently been implicated in cancer progression and prognosis. However, a comprehensive pan-cancer analysis of RBP4’s expression, prognostic significance, and functional associations across various cancers is lacking. Methods: [...] Read more.
Background: Retinol-binding protein 4 (RBP4) is primarily recognized for its role in retinoid transport, but has recently been implicated in cancer progression and prognosis. However, a comprehensive pan-cancer analysis of RBP4’s expression, prognostic significance, and functional associations across various cancers is lacking. Methods: We conducted a pan-cancer analysis of RBP4 using data from public databases. RBP4 expression levels were examined in 33 tumor types, and correlations with clinical outcomes, immune cell infiltration, DNA methylation, and gene mutations were assessed. Enrichment analyses of RBP4 and its co-expressed genes were performed to explore associated biological pathways. Additionally, in vitro experiments were conducted to assess the effects of RBP4 on cell migration and proliferation. Results: RBP4 showed differential expression between tumor and normal tissues, with downregulation in 21 cancer types and upregulation in 6. High expression levels of RBP4 were associated with poor overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) in specific cancers, notably in BRCA, HNSC, and STAD, whereas it was a favorable prognostic factor in cancers such as KIRP and MESO. RBP4 expression was also associated with immune cell infiltration, particularly with CD4+ Th2 cells and immune checkpoint genes. DNA methylation analysis suggested that the methylation of RBP4 may play a role in its regulatory mechanisms across cancer types. Enrichment analyses revealed that RBP4 and its co-expressed genes are involved in metabolism-related pathways and immune regulation. Functional assays indicated that RBP4 knockdown promoted tumor cell migration and proliferation. Conclusions: This study provides a comprehensive pan-cancer analysis of RBP4, identifying its prognostic potential and possible involvement in tumor immunity and metabolism. Our findings suggest that RBP4 could serve as a novel biomarker and therapeutic target in cancer, although further experimental studies are required to elucidate its precise mechanisms in specific cancer types. Full article
(This article belongs to the Special Issue Advances in Bioinformatics of Human Diseases)
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