Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
5.2
2.8
Journals
Genes
Special Issues
Bioinformatics of Human Diseases
share announcement

Bioinformatics of Human Diseases

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

Deadline for manuscript submissions: closed (10 September 2024) | Viewed by 17490

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 the 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, and to clarify the structure, function, interaction and relationship between human proteins and various human diseases, seeking for 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 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

Benefits of Publishing in a Special Issue

  • Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
  • Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
  • External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
  • e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (7 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Editorial

Jump to: Research

3 pages, 126 KiB  
Editorial
Editorial for the Bioinformatics of Human Diseases Special Issue
by Hongyan Xu
Genes 2025, 16(2), 118; https://doi.org/10.3390/genes16020118 - 22 Jan 2025
Viewed by 605
Abstract
Bioinformatics plays an ever-increasing role in revealing the complexity of genomic information and how it is related to the susceptibility and pathophysiology of human diseases [...] Full article
(This article belongs to the Special Issue Bioinformatics of Human Diseases)

Research

Jump to: Editorial

17 pages, 3387 KiB  
Article
RNA Sequencing and Weighted Gene Co-Expression Network Analysis Highlight DNA Replication and Key Genes in Nucleolin-Depleted Hepatoblastoma Cells
by Hannes Steinkellner, Silvia Madritsch, Mara Kluge, Teresa Seipel, Victoria Sarne, Anna Huber, Markus Schosserer, Raimund Oberle, Winfried Neuhaus, Alexander V. Beribisky and Franco Laccone
Genes 2024, 15(12), 1514; https://doi.org/10.3390/genes15121514 - 26 Nov 2024
Cited by 2 | Viewed by 6487
Abstract
Background/objectives: Nucleolin is a major component of the nucleolus and is involved in various aspects of ribosome biogenesis. However, it is also implicated in non-nucleolar functions such as cell cycle regulation and proliferation, linking it to various pathologic processes. The aim of this [...] Read more.
Background/objectives: Nucleolin is a major component of the nucleolus and is involved in various aspects of ribosome biogenesis. However, it is also implicated in non-nucleolar functions such as cell cycle regulation and proliferation, linking it to various pathologic processes. The aim of this study was to use differential gene expression analysis and Weighted Gene Co-expression Network analysis (WGCNA) to identify nucleolin-related regulatory pathways and possible key genes as novel therapeutic targets for cancer, viral infections and other diseases. Methods: We used two different siRNAs to downregulate the expression of nucleolin in a human hepatoblastoma (HepG2) cell line. We carried out RNA-sequencing (RNA-Seq), performed enrichment analysis of the pathways of the differentially expressed genes (DEGs) and identified protein–protein interaction (PPI) networks. Results: Both siRNAs showed high knockdown efficiency in HepG2 cells, resulting in the disruption of the nucleolar architecture and the downregulation of rRNA gene expression, both downstream hallmarks of a loss of nucleolin function. RNA-Seq identified 44 robust DEGs in both siRNA cell models. The enrichment analysis of the pathways of the downregulated genes confirmed the essential role of nucleolin in DNA replication and cell cycle processes. In addition, we identified seven hub genes linked to NCL: MCM6, MCM3, FEN1, MYBL2, MSH6, CDC6 and RBM14; all are known to be implicated in DNA replication, cell cycle progression and oncogenesis. Conclusions: Our findings demonstrate the functional consequences of nucleolin depletion in HepG2 and confirm the importance of nucleolin in DNA replication and cell cycle processes. These data will further enhance our understanding of the molecular and pathologic mechanisms of nucleolin and provide new therapeutic perspectives in disease. Full article
(This article belongs to the Special Issue Bioinformatics of Human Diseases)
►▼ Show Figures

Figure 1

14 pages, 2082 KiB  
Article
Dynamics of SARS-CoV-2 Spike RBD Protein Mutation and Pathogenicity Consequences in Indonesian Circulating Variants in 2020–2022
by Nabiel Muhammad Haykal, Fadilah Fadilah, Beti Ernawati Dewi, Linda Erlina, Aisyah Fitriannisa Prawiningrum and Badriul Hegar
Genes 2024, 15(11), 1468; https://doi.org/10.3390/genes15111468 - 14 Nov 2024
Cited by 2 | Viewed by 1352
Abstract
Background: Since the beginning of the coronavirus disease 2019 (COVID-19) outbreak, dynamic mutations in the receptor-binding domain (RBD) in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein have altered the pathogenicity of the variants of the virus circulating in Indonesia. This [...] Read more.
Background: Since the beginning of the coronavirus disease 2019 (COVID-19) outbreak, dynamic mutations in the receptor-binding domain (RBD) in the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike protein have altered the pathogenicity of the variants of the virus circulating in Indonesia. This research analyzes the mutation trend in various RBD samples from Indonesia published in the Global Initiative on Sharing All Influenza Data (GISAID) database using genomic profiling. Method: Patients in Indonesia infected with SARS-CoV-2, whose samples have been published in genomic databases, were selected for this research. The collected data were processed for analysis following several bioinformatics protocols: visualization into phylogenetic trees, 3D rendering, and the assessment of mutational impact. Results: In Indonesia, there are 25 unique SARS-CoV-2 clades and 318 unique SARS-CoV-2 RBD mutations from the earliest COVID-19 sample to samples collected in 2022, with T478K being the most prevalent RBD mutation and 22B being the most abundant clade. The Omicron variant has a lower docking score, higher protein destabilization, and higher KD than the Delta variant and the original virus. Conclusions: The study findings reveal a decreasing trend in virus pathogenicity as a potential trade-off to increase transmissibility via mutations in RBD over the years. Full article
(This article belongs to the Special Issue Bioinformatics of Human Diseases)
►▼ Show Figures

Figure 1

24 pages, 3052 KiB  
Article
Comparison of B-Cell Lupus and Lymphoma Using a Novel Immune Imbalance Transcriptomics Algorithm Reveals Potential Therapeutic Targets
by Naomi Rapier-Sharman, Sehi Kim, Madelyn Mudrow, Michael T. Told, Lane Fischer, Liesl Fawson, Joseph Parry, Brian D. Poole, Kim L. O’Neill, Stephen R. Piccolo and Brett E. Pickett
Genes 2024, 15(9), 1215; https://doi.org/10.3390/genes15091215 - 17 Sep 2024
Cited by 1 | Viewed by 1902
Abstract
Background/Objectives: Systemic lupus erythematosus (lupus) and B-cell lymphoma (lymphoma) co-occur at higher-than-expected rates and primarily depend on B cells for their pathology. These observations implicate shared inflammation-related B cell molecular mechanisms as a potential cause of co-occurrence. Methods: We consequently implemented a novel [...] Read more.
Background/Objectives: Systemic lupus erythematosus (lupus) and B-cell lymphoma (lymphoma) co-occur at higher-than-expected rates and primarily depend on B cells for their pathology. These observations implicate shared inflammation-related B cell molecular mechanisms as a potential cause of co-occurrence. Methods: We consequently implemented a novel Immune Imbalance Transcriptomics (IIT) algorithm and applied IIT to lupus, lymphoma, and healthy B cell RNA-sequencing (RNA-seq) data to find shared and contrasting mechanisms that are potential therapeutic targets. Results: We observed 7143 significantly dysregulated genes in both lupus and lymphoma. Of those genes, we found 5137 to have a significant immune imbalance, defined as a significant dysregulation by both diseases, as analyzed by IIT. Gene Ontology (GO) term and pathway enrichment of the IIT genes yielded immune-related “Neutrophil Degranulation” and “Adaptive Immune System”, which validates that the IIT algorithm isolates biologically relevant genes in immunity and inflammation. We found that 344 IIT gene products are known targets for established and/or repurposed drugs. Among our results, we found 48 known and 296 novel lupus targets, along with 151 known and 193 novel lymphoma targets. Known disease drug targets in our IIT results further validate that IIT isolates genes with disease-relevant mechanisms. Conclusions: We anticipate the IIT algorithm, together with the shared and contrasting gene mechanisms uncovered here, will contribute to the development of immune-related therapeutic options for lupus and lymphoma patients. Full article
(This article belongs to the Special Issue Bioinformatics of Human Diseases)
►▼ Show Figures

Figure 1

15 pages, 2577 KiB  
Article
In Silico Exploration of AHR-HIF Pathway Interplay: Implications for Therapeutic Targeting in ccRCC
by Francesco Gregoris, Giovanni Minervini and Silvio C. E. Tosatto
Genes 2024, 15(9), 1167; https://doi.org/10.3390/genes15091167 - 5 Sep 2024
Cited by 2 | Viewed by 1536
Abstract
The oxygen-sensing pathway is a crucial regulatory circuit that defines cellular conditions and is extensively exploited in cancer development. Pathogenic mutations in the von Hippel–Lindau (VHL) tumour suppressor impair its role as a master regulator of hypoxia-inducible factors (HIFs), leading to constitutive HIF [...] Read more.
The oxygen-sensing pathway is a crucial regulatory circuit that defines cellular conditions and is extensively exploited in cancer development. Pathogenic mutations in the von Hippel–Lindau (VHL) tumour suppressor impair its role as a master regulator of hypoxia-inducible factors (HIFs), leading to constitutive HIF activation and uncontrolled angiogenesis, increasing the risk of developing clear cell renal cell carcinoma (ccRCC). HIF hyperactivation can sequester HIF-1β, preventing the aryl hydrocarbon receptor (AHR) from correctly activating gene expression in response to endogenous and exogenous ligands such as TCDD (dioxins). In this study, we used protein–protein interaction networks and gene expression profiling to characterize the impact of VHL loss on AHR activity. Our findings reveal specific expression patterns of AHR interactors following exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) and in ccRCC. We identified several AHR interactors significantly associated with poor survival rates in ccRCC patients. Notably, the upregulation of the androgen receptor (AR) and retinoblastoma-associated protein (RB1) by TCDD, coupled with their respective downregulation in ccRCC and association with poor survival rates, suggests novel therapeutic targets. The strategic activation of the AHR via selective AHR modulators (SAhRMs) could stimulate its anticancer activity, specifically targeting RB1 and AR to reduce cell cycle progression and metastasis formation in ccRCC. Our study provides comprehensive insights into the complex interplay between the AHR and HIF pathways in ccRCC pathogenesis, offering novel strategies for targeted therapeutic interventions. Full article
(This article belongs to the Special Issue Bioinformatics of Human Diseases)
►▼ Show Figures

Figure 1

14 pages, 4342 KiB  
Article
Identification of Autophagy-Related Biomarkers and Diagnostic Model in Alzheimer’s Disease
by Wei Xu, Xi Su, Jing Qin, Ye Jin, Ning Zhang and Shasha Huang
Genes 2024, 15(8), 1027; https://doi.org/10.3390/genes15081027 - 5 Aug 2024
Cited by 1 | Viewed by 2109
Abstract
Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease. Its accurate pathogenic mechanisms are incompletely clarified, and effective therapeutic treatments are still inadequate. Autophagy is closely associated with AD and plays multiple roles in eliminating harmful aggregated proteins and maintaining cell homeostasis. This [...] Read more.
Alzheimer’s disease (AD) is the most prevalent neurodegenerative disease. Its accurate pathogenic mechanisms are incompletely clarified, and effective therapeutic treatments are still inadequate. Autophagy is closely associated with AD and plays multiple roles in eliminating harmful aggregated proteins and maintaining cell homeostasis. This study identified 1191 differentially expressed genes (DEGs) based on the GSE5281 dataset from the GEO database, intersected them with 325 autophagy-related genes from GeneCards, and screened 26 differentially expressed autophagy-related genes (DEAGs). Subsequently, GO and KEGG enrichment analysis was performed and indicated that these DEAGs were primarily involved in autophagy–lysosomal biological process. Further, eight hub genes were determined by PPI construction, and experimental validation was performed by qRT-PCR on a SH-SY5Y cell model. Finally, three hub genes (TFEB, TOMM20, GABARAPL1) were confirmed to have potential application for biomarkers. A multigenic prediction model with good predictability (AUC = 0.871) was constructed in GSE5281 and validated in the GSE132903 dataset. Hub gene-targeted miRNAs closely associated with AD were also retrieved through the miRDB and HDMM database, predicting potential therapeutic agents for AD. This study provides new insights into autophagy-related genes in brain tissues of AD patients and offers more candidate biomarkers for AD mechanistic research as well as clinical diagnosis. Full article
(This article belongs to the Special Issue Bioinformatics of Human Diseases)
►▼ Show Figures

Figure 1

16 pages, 451 KiB  
Article
Investigating the Influence of ANTXR2 Gene Mutations on Protective Antigen Binding for Heightened Anthrax Resistance
by Chamalapura Ashwathama Archana, Yamini Sri Sekar, Kuralayanapalya Puttahonnappa Suresh, Saravanan Subramaniam, Ningegowda Sagar, Swati Rani, Jayashree Anandakumar, Rajan Kumar Pandey, Nagendra Nath Barman and Sharanagouda S. Patil
Genes 2024, 15(4), 426; https://doi.org/10.3390/genes15040426 - 28 Mar 2024
Cited by 3 | Viewed by 2645
Abstract
Bacillus anthracis is the bacterium responsible for causing the zoonotic disease called anthrax. The disease presents itself in different forms like gastrointestinal, inhalation, and cutaneous. Bacterial spores are tremendously adaptable, can persist for extended periods and occasionally endanger human health. The Anthrax Toxin [...] Read more.
Bacillus anthracis is the bacterium responsible for causing the zoonotic disease called anthrax. The disease presents itself in different forms like gastrointestinal, inhalation, and cutaneous. Bacterial spores are tremendously adaptable, can persist for extended periods and occasionally endanger human health. The Anthrax Toxin Receptor-2 (ANTXR2) gene acts as membrane receptor and facilitates the entry of the anthrax toxin into host cells. Additionally, mutations in the ANTXR2 gene have been linked to various autoimmune diseases, including Hyaline Fibromatosis Syndrome (HFS), Ankylosing Spondylitis (AS), Juvenile Hyaline Fibromatosis (JHF), and Infantile Systemic Hyalinosis (ISH). This study delves into the genetic landscape of ANTXR2, aiming to comprehend its associations with diverse disorders, elucidate the impacts of its mutations, and pinpoint minimal non-pathogenic mutations capable of reducing the binding affinity of the ANTXR2 gene with the protective antigen. Recognizing the pivotal role of single-nucleotide polymorphisms (SNPs) in shaping genetic diversity, we conducted computational analyses to discern highly deleterious and tolerated non-synonymous SNPs (nsSNPs) in the ANTXR2 gene. The Mutpred2 server determined that the Arg465Trp alteration in the ANTXR2 gene leads to altered DNA binding (p = 0.22) with a probability of a deleterious mutation of 0.808; notably, among the identified deleterious SNPs, rs368288611 (Arg465Trp) stands out due to its significant impact on altering the DNA-binding ability of ANTXR2. We propose these SNPs as potential candidates for hypertension linked to the ANTXR2 gene, which is implicated in blood pressure regulation. Noteworthy among the tolerated substitutions is rs200536829 (Ala33Ser), recognized as less pathogenic; this highlights its potential as a valuable biomarker, potentially reducing side effects on the host while also reducing binding with the protective antigen protein. Investigating these SNPs holds the potential to correlate with several autoimmune disorders and mitigate the impact of anthrax disease in humans. Full article
(This article belongs to the Special Issue Bioinformatics of Human Diseases)
►▼ Show Figures

Graphical abstract

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-7
Back to TopTop