Genome-wide identification, subcellular localization, and expression analysis of the phosphatidyl ethanolamine-binding protein family reveals the candidates involved in flowering and yield regulation of Tartary buckwheat (Fagopyrum tataricum)
PeerJ » Bioinformatics
by Mengping Nie, Li Li, Cailin He, Jing Lu, Huihui Guo, Xiao’an Li, Mi Jiang, Ruiling Zhan, Wenjun Sun, Junjie Yin, Qi Wu
1d ago
Background PEBP (phosphatidyl ethanolamine-binding protein) is widely found in eukaryotes including plants, animals and microorganisms. In plants, the PEBP family plays vital roles in regulating flowering time and morphogenesis and is highly associated to agronomic traits and yields of crops, which has been identified and characterized in many plant species but not well studied in Tartary buckwheat (Fagopyrum tataricum Gaertn.), an important coarse food grain with medicinal value. Methods Genome-wide analysis of FtPEBP gene family members in Tartary buckwheat was performed using bioinformatic ..read more
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Assessing the risk of concurrent mycoplasma pneumoniae pneumonia in children with tracheobronchial tuberculosis: retrospective study
PeerJ » Bioinformatics
by Lin Liu, Jie Jiang, Lei Wu, De miao Zeng, Can Yan, Linlong Liang, Jiayun Shi, Qifang Xie
1d ago
Objective This study aimed to create a predictive model based on machine learning to identify the risk for tracheobronchial tuberculosis (TBTB) occurring alongside Mycoplasma pneumoniae pneumonia in pediatric patients. Methods Clinical data from 212 pediatric patients were examined in this retrospective analysis. This cohort included 42 individuals diagnosed with TBTB and Mycoplasma pneumoniae pneumonia (combined group) and 170 patients diagnosed with lobar pneumonia alone (pneumonia group). Three predictive models, namely XGBoost, decision tree, and logistic regression, were constructed, and ..read more
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Identification and validation of an endoplasmic-reticulum-stress-related gene signature as an effective diagnostic marker of endometriosis
PeerJ » Bioinformatics
by Tao Wang, Mei Ji, Jing Sun
1d ago
Background Endometriosis is one of the most common benign gynecological diseases and is characterized by chronic pain and infertility. Endoplasmic reticulum (ER) stress is a cellular adaptive response that plays a pivotal role in many cellular processes, including malignant transformation. However, whether ER stress is involved in endometriosis remains largely unknown. Here, we aimed to explore the potential role of ER stress in endometriosis, as well as its diagnostic value. Methods We retrieved data from the Gene Expression Omnibus (GEO) database. Data from the GSE7305 and GSE23339 datasets ..read more
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The interaction of InvF-RNAP is mediated by the chaperone SicA in Salmonella sp: an in silico prediction
PeerJ » Bioinformatics
by André B. Farias, Daniel Cortés-Avalos, J. Antonio Ibarra, Ernesto Perez-Rueda
1d ago
In this work we carried out an in silico analysis to understand the interaction between InvF-SicA and RNAP in the bacterium Salmonella Typhimurium strain LT2. Structural analysis of InvF allowed the identification of three possible potential cavities for interaction with SicA. This interaction could occur with the structural motif known as tetratricopeptide repeat (TPR) 1 and 2 in the two cavities located in the interface of the InvF and α-CTD of RNAP. Indeed, molecular dynamics simulations showed that SicA stabilizes the Helix-turn-Helix DNA-binding motifs, i.e., maintaining their proper conf ..read more
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Comprehensive analysis of peroxisome proliferator-activated receptors to predict the drug resistance, immune microenvironment, and prognosis in stomach adenocarcinomas
PeerJ » Bioinformatics
by Qing Jia, Baozhen Li, Xiulian Wang, Yongfen Ma, Gaozhong Li
6d ago
Background Peroxisome proliferator-activated receptors (PPARs) exert multiple functions in the initiation and progression of stomach adenocarcinomas (STAD). This study analyzed the relationship between PPARs and the immune status, molecular mutations, and drug therapy in STAD. Methods The expression profiles of three PPAR genes (PPARA, PPARD and PPARG) were downloaded from The Cancer Genome Atlas (TCGA) dataset to analyze their expression patterns across pan-cancer. The associations between PPARs and clinicopathologic features, prognosis, tumor microenvironment, genome mutation and drug sensit ..read more
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Deciphering the genomes of motility-deficient mutants of Vibrio alginolyticus 138-2
PeerJ » Bioinformatics
by Kazuma Uesaka, Keita Inaba, Noriko Nishioka, Seiji Kojima, Michio Homma, Kunio Ihara
1w ago
The motility of Vibrio species plays a pivotal role in their survival and adaptation to diverse environments and is intricately associated with pathogenicity in both humans and aquatic animals. Numerous mutant strains of Vibrio alginolyticus have been generated using UV or EMS mutagenesis to probe flagellar motility using molecular genetic approaches. Identifying these mutations promises to yield valuable insights into motility at the protein structural physiology level. In this study, we determined the complete genomic structure of 4 reference specimens of laboratory V. alginolyticus strains ..read more
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Integrating single-cell and bulk sequencing data to identify glycosylation-based genes in non-alcoholic fatty liver disease-associated hepatocellular carcinoma
PeerJ » Bioinformatics
by Zhijia Zhou, Yanan Gao, Longxin Deng, Xiaole Lu, Yancheng Lai, Jieke Wu, Shaodong Chen, Chengzhong Li, Huiqing Liang
1w ago
Background The incidence of non-alcoholic fatty liver disease (NAFLD) associated hepatocellular carcinoma (HCC) has been increasing. However, the role of glycosylation, an important modification that alters cellular differentiation and immune regulation, in the progression of NAFLD to HCC is rare. Methods We used the NAFLD-HCC single-cell dataset to identify variation in the expression of glycosylation patterns between different cells and used the HCC bulk dataset to establish a link between these variations and the prognosis of HCC patients. Then, machine learning algorithms were used to iden ..read more
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The impact of FASTQ and alignment read order on structural variant calling from long-read sequencing data
PeerJ » Bioinformatics
by Kyle J. Lesack, James D. Wasmuth
1w ago
Background Structural variant (SV) calling from DNA sequencing data has been challenging due to several factors, including the ambiguity of short-read alignments, multiple complex SVs in the same genomic region, and the lack of “truth” datasets for benchmarking. Additionally, caller choice, parameter settings, and alignment method are known to affect SV calling. However, the impact of FASTQ read order on SV calling has not been explored for long-read data. Results Here, we used PacBio DNA sequencing data from 15 Caenorhabditis elegans strains and four Arabidopsis thaliana ecotypes to evaluate ..read more
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Exploring the antioxidant potential of chalcogen-indolizines throughout in vitro assays
PeerJ » Bioinformatics
by Cleisson Schossler Garcia, Marcia Juciele da Rocha, Marcelo Heinemann Presa, Camila Simões Pires, Evelyn Mianes Besckow, Filipe Penteado, Caroline Signorini Gomes, Eder João Lenardão, Cristiani Folharini Bortolatto, César Augusto Brüning
1w ago
Reactive oxygen species (ROS) and reactive nitrogen species (RNS) are highly reactive molecules produced naturally by the body and by external factors. When these species are generated in excessive amounts, they can lead to oxidative stress, which in turn can cause cellular and tissue damage. This damage is known to contribute to the aging process and is associated with age-related conditions, including cardiovascular and neurodegenerative diseases. In recent years, there has been an increased interest in the development of compounds with antioxidant potential to assist in the treatment of dis ..read more
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EPI-SF: essential protein identification in protein interaction networks using sequence features
PeerJ » Bioinformatics
by Sovan Saha, Piyali Chatterjee, Subhadip Basu, Mita Nasipuri
1w ago
Proteins are considered indispensable for facilitating an organism’s viability, reproductive capabilities, and other fundamental physiological functions. Conventional biological assays are characterized by prolonged duration, extensive labor requirements, and financial expenses in order to identify essential proteins. Therefore, it is widely accepted that employing computational methods is the most expeditious and effective approach to successfully discerning essential proteins. Despite being a popular choice in machine learning (ML) applications, the deep learning (DL) method is not suggested ..read more
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