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Bioinformatics Study of Diseases

Submission Deadline: 31 August 2023 (closed)

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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ARTICLE

Research progress and prospects of nucleic acid isothermal amplification technology
SHUHUI WU, PING XU, XIANGBIN XU, SONG-BAI LIU
BIOCELL, Vol.47, No.11, pp. 2385-2395, 2023, DOI:10.32604/biocell.2023.029687
（This article belongs to this Special Issue: Bioinformatics Study of Diseases)
Abstract Nucleic acid (DNA and RNA) detection and quantification methods play vital roles in molecular biology. With the development of molecular biology, isothermal amplification of DNA/RNA, as a new molecular biology technology, can be amplified under isothermal condition, it has the advantages of high sensitivity, high specificity, and high efficiency, and has been applied in various fields of biotechnology, including disease diagnosis, pathogen detection, food hygiene and safety detection and so on. This paper introduces the progress of isothermal amplification technology, including rolling circle amplification (RCA), nucleic acid sequence-dependent amplification (NASBA), strand displacement amplification (SDA), loop-mediated isothermal amplification (LAMP), helicase-dependent amplification… More >

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Hsa_circ_0036740 in familial adenomatous polyposis: Immune regulation and neutrophil effects in CRC based on high-throughput assay
ZHIWANG LI, HAN YU, YUPING LIU, WEISHENG WU, HAIJING ZENG, EN LI
BIOCELL, Vol.47, No.11, pp. 2409-2422, 2023, DOI:10.32604/biocell.2023.031186
（This article belongs to this Special Issue: Bioinformatics Study of Diseases)
Abstract Familial adenomatous polyposis (FAP) is an autosomal dominant disease with a high probability of becoming cancerous. Many RNAs potentially associated with FAP have not been identified. In this study, a circRNA (circular RNA) expression profile of FAP was established using a circRNA microarray, and differentially expressed circRNAs were verified by RT-qPCR. The effects of hsa_circ_0036740 on the malignant behavior of tumor cells (proliferation, apoptosis, and epithelial mesenchymal transition) and the levels of C3A complement protein expression were evaluated. Moreover, neutrophils were isolated and co-cultured with colorectal cancer cells (CRCs), followed by measurements of MPO-DNA, citrullinated histone H3, interleukin (IL)-1β, IL-6,… More >
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Aryl hydrocarbon receptor nuclear translocator 2 as a prognostic biomarker and immunotherapeutic indicator for clear cell renal cell carcinoma
RENLONG ZHOU, SHUANG LI, XILIN XIAO
BIOCELL, Vol.47, No.11, pp. 2397-2408, 2023, DOI:10.32604/biocell.2023.030281
（This article belongs to this Special Issue: Bioinformatics Study of Diseases)
Abstract Background: In many cancer types, aryl hydrocarbon receptor nuclear translocator 2 (ARNT2) has been found to be associated with tumor cell proliferation and prognosis. However, the role of ARNT2 in clear cell renal cell carcinoma (ccRCC) has not been completely elucidated. In this study, the potential role of ARNT2 in ccRCC development was characterized. Methods: A pan-cancer dataset (TCGA-TARGET-GTEx) was accessed from UCSC Xena Data Browser. ARNT2 expression in normal and tumor samples was compared. Univariate Cox regression was performed to evaluate the prognostic value of ARNT2. Single sample gene set enrichment analysis (ssGSEA) was used to estimate the enrichment… More >

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Identification of EML4 as a key hub gene for endometriosis and its molecular mechanism and potential drug prediction based on the GEO database
XIANBAO FANG, MINGYAN TANG, ZIYANG YU, JIAQI DING, CHONG CUI, HONG ZHANG
BIOCELL, Vol.47, No.9, pp. 2059-2068, 2023, DOI:10.32604/biocell.2023.030565
（This article belongs to this Special Issue: Bioinformatics Study of Diseases)
Abstract Objective: Key genes were screened to analyze molecular mechanisms and their drug targets of endometriosis by applying a bioinformatics approach. Methods: Gene expression profiles of endometriosis and healthy controls were obtained from the Gene Expression Omnibus database. Significant differentially expressed genes were screened using the limma package. Correlation pathways were screened by Spearman correlation analysis on the echinoderm microtubule-associated protein-like 4 (EML4) and enrichment in endometriosis pathways and estimated by the GSVA package. Immune characteristics were assessed by the “ESTIMATE” R package. Potential regulatory pathways were determined by enrichment analysis. The SWISS-MODE website was used in homology modeling with EML4… More >
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Network biology: A promising approach for drug target identification against neurodevelopmental disorders
WAYEZ NAQVI, ANANYA SINGH, PREKSHI GARG, PRACHI SRIVASTAVA
BIOCELL, Vol.47, No.8, pp. 1675-1687, 2023, DOI:10.32604/biocell.2023.029624
（This article belongs to this Special Issue: Bioinformatics Study of Diseases)
Abstract Biological entities are involved in complicated and complex connections; hence, discovering biological information using network biology ideas is critical. In the past few years, network biology has emerged as an integrative and systems-level approach for understanding and interpreting these complex interactions. Biological network analysis is one method for reducing enormous data sets to clinically useful knowledge for disease diagnosis, prognosis, and treatment. The network of biological entities can help us predict drug targets for several diseases. The drug targets identified through the systems biology approach help in targeting the essential biological pathways that contribute to the progression and development of… More >

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Molecular dynamics-driven exploration of peptides targeting SARS-CoV-2, with special attention on ACE2, S protein, M^pro, and PL^pro: A review
MOHAMAD ZULKEFLEE SABRI, JOANNA BOJARSKA, FAI-CHU WONG, TSUN-THAI CHAI
BIOCELL, Vol.47, No.8, pp. 1727-1742, 2023, DOI:10.32604/biocell.2023.029272
（This article belongs to this Special Issue: Bioinformatics Study of Diseases)
Abstract Molecular dynamics (MD) simulation is a computational technique that analyzes the movement of a system of particles over a given period. MD can provide detailed information about the fluctuations and conformational changes of biomolecules at the atomic level over time. In recent years, MD has been widely applied to the discovery of peptides and peptide-like molecules that may serve as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) inhibitors. This review summarizes recent advances in such explorations, focusing on four protein targets: angiotensin-converting enzyme 2 (ACE2), spike protein (S protein), main protease (M^pro), and papain-like protease (PL^pro). These four proteins are… More >
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Exploring the attenuation mechanisms of Dalbergia odorifera leaves extract on cerebral ischemia-reperfusion based on weighted gene co-expression network analysis
JINFANG HU, JIANGEN AO, LONGSHENG FU, YAOQI WU, FENG SHAO, TIANTIAN XU, MINGJIN JIANG, SHAOFENG XIONG, YANNI LV
BIOCELL, Vol.47, No.7, pp. 1611-1622, 2023, DOI:10.32604/biocell.2023.028684
（This article belongs to this Special Issue: Bioinformatics Study of Diseases)
Abstract Background: The attenuation function of Dalbergia odorifera leaves on cerebral ischemia-reperfusion (I/R) is little known. The candidate targets for the Chinese herb were extracted from brain tissues through the high-affinity chromatography. The molecular mechanism of D. odorifera leaves on cerebral I/R was investigated. Methods: Serial affinity chromatography based on D. odorifera leaves extract (DLE) affinity matrices were applied to find specific binding proteins in the brain tissues implemented on C57BL/6 mice by intraluminal middle cerebral artery occlusion for 1 h and reperfusion for 24 h. Specific binding proteins were subjected to mass-spectrometry to search for the differentially expressed proteins between… More >

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A novel prognostic gene signature, nomogram and immune landscape based on tanshinone IIA drug targets for hepatocellular carcinoma: Comprehensive bioinformatics analysis and in vitro experiments
BOWEN PENG, YUN GE, GANG YIN
BIOCELL, Vol.47, No.7, pp. 1519-1535, 2023, DOI:10.32604/biocell.2023.027026
（This article belongs to this Special Issue: Bioinformatics Study of Diseases)
Abstract Background: Tanshinone IIA, one of the main ingredients of Danshen, is used to treat hepatocellular carcinoma (HCC). However, potential targets of the molecule in the therapy of HCC are unknown. Methods: In this study, we collected the tanshinone IIA targets from public databases for investigation. We screened differentially expressed genes (DEGs) across HCC and normal tissues using mRNA expression profiles from The Cancer Genome Atlas (TCGA). Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression models were used to identify and construct the prognostic gene signature. Results: Finally, we discovered common genes across tanshinone IIA… More >

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Bioinformatic analysis of lncRNA-associated competing endogenous RNA regulatory networks in synovial tissue of temporomandibular joint osteoarthritis
CHUYAO WANG, CHUAN LU, LUXIANG ZOU, DONGMEI HE
BIOCELL, Vol.47, No.6, pp. 1293-1306, 2023, DOI:10.32604/biocell.2023.028199
（This article belongs to this Special Issue: Bioinformatics Study of Diseases)
Abstract Background: Temporomandibular joint osteoarthritis (TMJOA) is an end-stage disease that seriously affects the patients’ quality of life. Molecular insights in advancing our understanding of TMJOA are the need of the hour. Methods: We performed RNA high-throughput sequencing and bioinformatics analysis of differentially expressed (DE) long non-coding RNA (lncRNAs), microRNAs (miRNAs), and messenger RNA (mRNAs) in human synovial TMJOA tissues. Firstly, synovium samples of TMJOA patients and non-TMJOA controls were collected for highthroughput sequencing of lncRNAs, miRNAs, and mRNAs. We then performed biological function analysis of the top 100 mRNAs with more than 2-fold differential expression, and their upstream regulated miRNAs… More >

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Genetic algorithm-optimized backpropagation neural network establishes a diagnostic prediction model for diabetic nephropathy: Combined machine learning and experimental validation in mice
WEI LIANG, ZONGWEI ZHANG, KEJU YANG, HONGTU HU, QIANG LUO, ANKANG YANG, LI CHANG, YUANYUAN ZENG
BIOCELL, Vol.47, No.6, pp. 1253-1263, 2023, DOI:10.32604/biocell.2023.027373
（This article belongs to this Special Issue: Bioinformatics Study of Diseases)
Abstract Background: Diabetic nephropathy (DN) is the most common complication of type 2 diabetes mellitus and the main cause of end-stage renal disease worldwide. Diagnostic biomarkers may allow early diagnosis and treatment of DN to reduce the prevalence and delay the development of DN. Kidney biopsy is the gold standard for diagnosing DN; however, its invasive character is its primary limitation. The machine learning approach provides a non-invasive and specific criterion for diagnosing DN, although traditional machine learning algorithms need to be improved to enhance diagnostic performance. Methods: We applied high-throughput RNA sequencing to obtain the genes related to DN tubular… More >

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Proteomics analysis provides novel biomarkers and therapeutic target candidates in the treatment of the Huang-Pu-Tong-Qiao formula in an AD rat model
QIAN CHEN, XIN LEI, GUANHUA HU, YAN WANG, ZHENGQING FANG, GUOQUAN WANG, HANG SONG, SHU YE, BIAO CAI
BIOCELL, Vol.47, No.6, pp. 1265-1277, 2023, DOI:10.32604/biocell.2023.028811
（This article belongs to this Special Issue: Bioinformatics Study of Diseases)
Abstract Background: Huang-Pu-Tong-Qiao formula (HPTQ), a traditional Chinese herbal formula, has a variety of pharmacological effects. It has been used to treat Alzheimer’s disease (AD) for decades. This study aimed to screen differentially expressed proteins in the hippocampus of AD model rats treated with HPTQ. Proteomic studies of the effects of HPTQ on AD are key to understanding the therapeutic mechanisms of HPTQ and identifying potential therapeutic targets. Methods: We hence used the isobaric tags for relative and absolute quantification (ITRAQ) approach to investigate the differentially expressed proteins in the hippocampus of AD model rats before and after HPTQ administration and… More >

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A broad overview of genotype imputation: Standard guidelines, approaches, and future investigations in genomic association studies
MIRKO TRECCANI, ELENA LOCATELLI, CRISTINA PATUZZO, GIOVANNI MALERBA
BIOCELL, Vol.47, No.6, pp. 1225-1241, 2023, DOI:10.32604/biocell.2023.027884
（This article belongs to this Special Issue: Bioinformatics Study of Diseases)
Abstract The advent of genomic big data and the statistical need for reaching significant results have led genome-wide association studies to be ravenous of a huge number of genetic markers scattered along the whole genome. Since its very beginning, the so-called genotype imputation served this purpose; this statistical and inferential procedure based on a known reference panel opened the theoretical possibility to extend association analyses to a greater number of polymorphic sites which have not been previously assayed by the used technology. In this review, we present a broad overview of the genotype imputation process, showing the most known methods and… More >

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Prognosis and immunological role of HLA-DMA in lung adenocarcinoma
QIN YU, CHEN CHEN, HAIYAN ZHANG, JIN CHEN, JUNKANG SHEN, JUN YAN
BIOCELL, Vol.47, No.6, pp. 1279-1292, 2023, DOI:10.32604/biocell.2023.027553
（This article belongs to this Special Issue: Bioinformatics Study of Diseases)
Abstract Background: HLA-DMA presents pathogen-derived antigens to CD4+ and CD8+ T cells, respectively, and plays a significant part in initiating the immune response. So far, the impact of HLA expression on the prognosis of BC cells is controversial, because few studies have shown that the expressions of some HLA genes are related to the improvement of the survival rate. Up till now, however, the relationship between HLA-DMA and LUAD has not yet been assessed. Methods: We analyzed the TCGA database and assessed the prognostic value of HLA-DMA in LUAD. We conducted the Kruskal–Wallis and Wilcoxon signed-rank test and utilized logistic regression… More >

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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… More >

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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… More >

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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… More >

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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… More >

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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… More >

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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… More >

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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… More >

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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… More >

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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.… More >

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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.… More >

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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… More >

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Bioinformatics Study of Diseases

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