Guest Editors
Prof. Dr. Qingjia Chi, Department of Engineering Structure and Mechanics, Wuhan University of Technology, Wuhan 430070, China. qingjia@whut.edu.cn
Summary
Bioinformatics analysis is now widely used in the therapeutic diagnosis and prediction of diseases. It is of great significance for disease gene diagnosis, gene function discovery, protein structure prediction, structure-based drug design, drug synthesis, and pharmaceutical industry, shortening drug development time, and personalized treatment of diseases. However, there is an urgent need for bioinformatics to use artificial intelligence and develop powerful machine learning and deep learning algorithms to improve and build disease diagnosis and prognosis models.
We welcome original research, reviews, and other articles relevant to the bioinformatics study of disease in this special issue. Topics include but may not be limited to:
Prognostic and diagnostic models of disease
Omics sequencing method development
Database construction
Multi-omics data integration
Bulk RNA-seq and single cell RNA-seq
Transcriptome bioinformatics
Bulk RNA-seq and
Proteome bioinformatics
Machine learning and deep learning algorithms in bioinformatics
Epigenetic bioinformatics
Traditional Chinese medicine systems biology and network pharmacology
Disease biomarker identification
Keywords
Bioinformatics, Prognostic Models, Diagnostic Models, Biomarker, Machine Learning, Drug Targets
Published Papers
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Open Access
REVIEW
A comprehensive analysis of the role of molecular docking in the development of anticancer agents against the cell cycle CDK enzyme
PRIYANKA SOLANKI, NISARG RANA, PRAKASH C. JHA, ANU MANHAS
BIOCELL, DOI:10.32604/biocell.2023.026615
（This article belongs to this Special Issue:
Bioinformatics Study of Diseases)
Abstract Cancer is considered one of the most lethal diseases responsible for causing deaths worldwide. Although there
have been many breakthroughs in anticancer development, cancer remains the major cause of death globally. In this
regard, targeting cancer-causing enzymes is one of the efficient therapeutic strategies. Biological functions like cell
cycle, transcription, metabolism, apoptosis, and other depend primarily on cyclin-dependent kinases (CDKs). These
enzymes help in the replication of DNA in the normal cell cycle process, and deregulation in the functioning of any
CDK can cause abnormal cell growth, which leads to cancer. This review is focused on anticancer drug discovery
against…
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Open Access
REVIEW
A comprehensive analysis of the role of molecular docking in the development of anticancer agents against the cell cycle CDK enzyme
PRIYANKA SOLANKI, NISARG RANA, PRAKASH C. JHA, ANU MANHAS
BIOCELL, Vol.47, No.4, pp. 707-729, 2023, DOI:10.32604/biocell.2023.026615
（This article belongs to this Special Issue:
Bioinformatics Study of Diseases)
Abstract Cancer is considered one of the most lethal diseases responsible for causing deaths worldwide. Although there have been many breakthroughs in anticancer development, cancer remains the major cause of death globally. In this regard, targeting cancer-causing enzymes is one of the efficient therapeutic strategies. Biological functions like cell cycle, transcription, metabolism, apoptosis, and other depend primarily on cyclin-dependent kinases (CDKs). These enzymes help in the replication of DNA in the normal cell cycle process, and deregulation in the functioning of any CDK can cause abnormal cell growth, which leads to cancer. This review is focused on anticancer drug discovery against…
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Open Access
REVIEW
Transcriptional factor RUNX1: A potential therapeutic target for fibrotic pulmonary disease
JIA LIU, FAPING WANG, BO YUAN, FENGMING LUO
BIOCELL, Vol.47, No.4, pp. 697-705, 2023, DOI:10.32604/biocell.2023.026148
（This article belongs to this Special Issue:
Bioinformatics Study of Diseases)
Abstract Runt-related transcription factor-1 (RUNX1), also known as the core-binding factor alpha 2 subunit, is closely related to human leukemia. The functions of RUNX1 in modulating cell proliferation, differentiation, and survival in multiple systems have been gradually discovered with the emergence of transgenic mice. RUNX1 is a powerful transcription factor implicated in diverse signaling pathways and cellular mechanisms that participate in lung development and pulmonary diseases. RUNX1 has recently been identified as a target regulator of fibrotic remodeling diseases, particularly in the kidney. However, the role of RUNX1 in pulmonary fibrosis is unclear. Pulmonary fibrosis is characterized by obscure nosogenesis, limited…
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Open Access
ARTICLE
Analysis of the mechanism of aldo-keto reductase dependent cis-platin resistance in HepG2 cells based on transcriptomic and NADH metabolic state
TINGTING SUN, XUE SUN, XIN WANG, RUI GUO, YUANHUA YU, LE GAO
BIOCELL, Vol.47, No.4, pp. 879-889, 2023, DOI:10.32604/biocell.2023.026229
（This article belongs to this Special Issue:
Bioinformatics Study of Diseases)
Abstract Background: Aldo-keto oxidoreductase (AKR) inhibitors could reverse the resistance of several cancer cells to cis-platin, but their role in resistance remains unclear.
Methods: We verified the difference of AKR1Cs expression by Western blot, RNA sequencing and qRT-PCR. The differences of AKR1Cs expression were analyzed and inferred. Use Assay of NADH and NAD
+ content to verify the inference. The Docking experience was used to verify the affinity between MPA, MCFLA, MLS and AKR1C3.
Results: Our RNA-seq results showed
de novo NAD biosynthesis-related genes and NAD(P)H-dependent oxidoreductases were significantly upregulated in cis-platin-resistant HepG2 hepatic cancer cells (HepG2-RC cells) compared with HepG2 cells. At least…
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Open Access
ARTICLE
Increased MAD2L2 expression predicts poor clinical outcome in Colon Adenocarcinoma
HAOTONG SUN, HEYING WANG, XIN LI, YANJIE HAO, JUN LING, HUAN WANG, FEIMIAO WANG, FANG XU
BIOCELL, Vol.47, No.3, pp. 607-618, 2023, DOI:10.32604/biocell.2023.026445
（This article belongs to this Special Issue:
Bioinformatics Study of Diseases)
Abstract Background: Colon adenocarcinoma (COAD) is the second leading cause of cancer death worldwide thus,
identification of COAD biomarkers is critical. Mitotic Arrest Deficient 2 Like 2 (
MAD2L2) is a key factor in
mammalian DNA damage repair and is highly expressed in many malignant tumors. This is a comprehensive study
of
MAD2L2 expression, its diagnostic value, prognostic analysis, potential biological function, and impact on the
immune system of patients with COAD.
Methods: Gene expression, clinical relevance, prognostic analysis, diagnostic
value, GO/KEGG cluster analysis, data obtained from TCGA, and bioinformatics statistical analysis were performed
using the R package. Immune responses to
MAD2L2…
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Open Access
ARTICLE
A model based on eight iron metabolism-related genes accurately predicts acute myeloid leukemia prognosis
ZHANSHU LIU, XI HUANG
BIOCELL, Vol.47, No.3, pp. 593-605, 2023, DOI:10.32604/biocell.2023.024148
（This article belongs to this Special Issue:
Bioinformatics Study of Diseases)
Abstract Purpose: Iron metabolism maintains the balance between iron absorption and excretion. Abnormal iron
metabolism can cause numerous diseases, including tumor. This study determined the iron metabolism-related genes
(IMRGs) signature that can predict the prognosis of acute myeloid leukemia (AML). The roles of these genes in the
immune microenvironment were also explored.
Methods: A total of 514 IMRGs were downloaded from the
Molecular Characteristics Database (MSigDB). IMRGs related to AML prognosis were identified using Cox regression
and LASSO analyses and were used to construct the risk score model. AML patients were stratified into high-risk
groups (cluster 1) and low-risk groups (cluster…
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Open Access
ARTICLE
SPP1 and the risk score model to improve the survival prediction of patients with hepatocellular carcinoma based on multiple algorithms and back propagation neural networks
WENLI ZENG, FENG LING, KAINUO DANG, QINGJIA CHI
BIOCELL, Vol.47, No.3, pp. 581-592, 2023, DOI:10.32604/biocell.2023.025957
（This article belongs to this Special Issue:
Bioinformatics Study of Diseases)
Abstract Hepatocellular carcinoma (HCC) is associated with poor prognosis and fluctuations in immune status.
Although studies have found that secreted phosphoprotein 1 (SPP1) is involved in HCC progression, its independent
prognostic value and immune-mediated role remain unclear. Using The Cancer Genome Atlas and Gene Expression
Omnibus data, we found that low expression of SPP1 is significantly associated with improved survival of HCC
patients and that SPP1 expression is correlated with clinical characteristics. Univariate and multivariate Cox
regression confirmed that SPP1 is an independent prognostic factor of HCC. Subsequently, we found that T cell CD4
memory-activated monocytes, M0 macrophages, and resting mast…
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Open Access
ARTICLE
dbSCI: A manually curated database of SARS-CoV-2 inhibitors for COVID-19
QIANG WANG, GUO ZHAO, LONGXIANG XIE, XUAN LI, XIXI YU, QIONGSHAN LI, BAOPING ZHENG, ZULIPINUER WUSIMAN, XIANGQIAN GUO
BIOCELL, Vol.47, No.2, pp. 367-371, 2023, DOI:10.32604/biocell.2023.025310
（This article belongs to this Special Issue:
Bioinformatics Study of Diseases)
Abstract Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the pathogen of the ongoing coronavirus disease 2019 (COVID-19) global pandemic. Here, by centralizing published cell-based experiments, clinical trials, and virtual drug screening data from the NCBI PubMed database, we developed a database of SARS-CoV-2 inhibitors for COVID-19, dbSCI, which includes 234 SARS-CoV-2 inhibitors collected from publications based on cell-based experiments, 81 drugs of COVID-19 in clinical trials and 1305 potential SARS-CoV-2 inhibitors from bioinformatics analyses. dbSCI provides four major functions: (1) search the drug target or its inhibitor for SARS-CoV-2, (2) browse target/inhibitor information collected from cell experiments, clinical trials, and…
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Open Access
ARTICLE
A pan-cancer analysis of the biological function and clinical value of BTLA in tumors
XIANGLAI JIANG, JIN HE, YONGFENG WANG, JIAHUI LIU, XIANGYANG LI, XIANGUI HE, HUI CAI
BIOCELL, Vol.47, No.2, pp. 351-366, 2023, DOI:10.32604/biocell.2023.025157
（This article belongs to this Special Issue:
Bioinformatics Study of Diseases)
Abstract B and T-lymphocyte attenuator (BTLA) plays an immunosuppressive role by inhibiting T- and B-cell functions. BTLA is associated with a variety of diseases, especially cancer immunity. However, the function of BTLA in various cancers and its clinical prognostic value have still not been comprehensively analyzed. This study aimed to identify the relationship between BTLA and cancer from the perspectives of differences in BTLA expression, its clinical value, immune infiltration, and the correlation with immune-related genes in various cancers. Data regarding mRNA expression, miRNA expression, lncRNA expression, and clinical data of patients of 33 existing cancers were collected from the TCGA…
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Open Access
ARTICLE
Prognostic model for prostate cancer based on glycolysis-related genes and non-negative matrix factorization analysis
ZECHAO LU, FUCAI TANG, HAOBIN ZHOU, ZEGUANG LU, WANYAN CAI, JIAHAO ZHANG, ZHICHENG TANG, YONGCHANG LAI, ZHAOHUI HE
BIOCELL, Vol.47, No.2, pp. 339-350, 2023, DOI:10.32604/biocell.2023.023750
（This article belongs to this Special Issue:
Bioinformatics Study of Diseases)
Abstract Background: Establishing an appropriate prognostic model for PCa is essential for its effective treatment. Glycolysis is a vital energy-harvesting mechanism for tumors. Developing a prognostic model for PCa based on glycolysis-related genes is novel and has great potential.
Methods: First, gene expression and clinical data of PCa patients were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), and glycolysis-related genes were obtained from the Molecular Signatures Database (MSigDB). Gene enrichment analysis was performed to verify that glycolysis functions were enriched in the genes we obtained, which were used in non-negative matrix factorization (NMF) to identify clusters.…
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Open Access
REVIEW
Review on microbial metabolomics of probiotics and pathogens: Methodologies and applications
XIN MENG, XUE LI, LIANRONG YANG, RUI YIN, LEHUI QI, QI GUO
BIOCELL, Vol.47, No.1, pp. 91-107, 2023, DOI:10.32604/biocell.2023.024310
（This article belongs to this Special Issue:
Bioinformatics Study of Diseases)
Abstract In recent years, microbial metabolomics, a new field that has attracted wide attention, provides a map of metabolic pathways and clarifies the interaction mechanism between microorganisms and hosts. Many microorganisms are found in the human intestine, oral cavity, vagina, etc. Probiotics could maintain the good health of the host, while pathogens and an imbalance of bacterial flora lead to a series of diseases of the body and mind. Metabolomics is a science for qualitative and quantitative analysis of all metabolites in an organism or biological system, which could provide key information to understand the related metabolic pathways and associated changes.…
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Open Access
ARTICLE
ABCC8 is correlated with immune cell infiltration and overall survival in lower grade glioma
LIPING GONG, MING JIA
BIOCELL, Vol.47, No.1, pp. 109-123, 2023, DOI:10.32604/biocell.2023.024620
（This article belongs to this Special Issue:
Bioinformatics Study of Diseases)
Abstract ATP binding cassette subfamily C member 8 (ABCC8) encodes a protein regulating the ATP-sensitive
potassium channel. Whether the level of ABCC8 mRNA in lower grade glioma (LGG) correlates with immune cell
infiltration and patient outcomes has not been evaluated until now. Comparisons of ABCC8 expression between
different tumors and normal tissues were evaluated by exploring publicly available datasets. The association between
ABCC8 and tumor immune cell infiltration, diverse gene mutation characteristics, tumor mutation burden (TMB),
and survival in LGG was also investigated in several independent datasets. Pathway enrichment analysis was
conducted to search for ABCC8-associated signaling pathways. Through an online…
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