المؤلفون: Bastian Fromm, Xiangfu Zhong, Marcel Tarbier, Marc R. Friedländer, Michael Hackenberg

المصدر: RNA (New York, N.Y.). 28(6)

مصطلحات موضوعية: MicroRNAs, Computational Biology, Humans, Molecular Sequence Annotation, Databases, Nucleic Acid, Molecular Biology

الوصف: Over the last few years, the number of microRNAs in the human genome has become a controversially debated issue. Several publications reported thousands of putative novel microRNAs not included in the curated microRNA gene database MirGeneDB and the repository miRBase. Recently, by using sequencing of ∼300 human tissues and cell lines, the human RNA atlas, an expanded inventory of human RNA annotations, was published, reporting thousands of putative microRNAs. We, the developers of established microRNA prediction tools and hosts of MirGeneDB, raise concerns about the frequently applied prediction and functional validation strategies, briefly discussing the drawbacks of false positive detections. By means of quantifying well-established biogenesis-derived features, we show that the reported novel microRNAs essentially represent false-positives and argue that the human microRNA complement, at about 550 microRNA genes, is already near complete. Output of available tools must be curated as false predictions will misguide scientists looking for biomarkers or therapeutic targets.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::340242caede05ddc730676d5ef2f8074Test
https://pubmed.ncbi.nlm.nih.gov/35236776Test

المؤلفون: Ke Wang, Yanzhen Lu, Zhifeng Zhao, Chihao Zhang

المصدر: Computational and Mathematical Methods in Medicine
Computational and Mathematical Methods in Medicine, Vol 2021 (2021)

مصطلحات موضوعية: Liver Cirrhosis, Article Subject, General Immunology and Microbiology, Gene Expression Profiling, Applied Mathematics, Computer applications to medicine. Medical informatics, R858-859.7, Computational Biology, Down-Regulation, General Medicine, General Biochemistry, Genetics and Molecular Biology, Up-Regulation, Gene Ontology, Hepatic Encephalopathy, Modeling and Simulation, Humans, Gene Regulatory Networks, RNA, Long Noncoding, Protein Interaction Maps, RNA, Messenger, Databases, Nucleic Acid, human activities, Research Article

الوصف: Backgrounds. Serum long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) interaction network was discovered to exert an important role in liver cirrhosis while little is known in mild hepatic encephalopathy (MHE). Therefore, we aim to systematically evaluate the serum lncRNA-mRNA network and its regulatory mechanism in MHE. Methods. The data of serum mRNAs and lncRNAs were derived from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) were calculated between 11 cirrhotic patients with and without MHE. Next, the biological functions and underlined pathways of DEGs were determined through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Finally, an interactive network between lncRNAs and mRNAs was built, and hub genes were identified, respectively. Results. A total of 64 differentially expressed lncRNAs (dif-lncRNAs) were found between patients with and without MHE, including 30 up- and 34 downregulated genes. 187 differentially expressed mRNAs (dif-mRNAs) were identified, including 84 up- and 103 downregulated genes. Functional enrichment analysis suggested that the regulatory pathways involved in MHE mainly consisted of a series of immune and inflammatory responses. Several hub mRNAs involved in regulatory network were identified, including CCL5, CCR5, CXCR3, CD274, STAT1, CXCR6, and EOMES. In addition, lnc-FAM84B-8 and lnc-SAMD3-1 were found to regulate these above hub genes through building a lncRNA-mRNA network. Conclusion. This is the first study to construct the serum lncRNA-mRNA network in MHE, demonstrating the critical role of lncRNAs in regulating inflammatory and immunological profiles in the developing of MHE, suggesting a latent mechanism in this pathophysiological process.

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الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5cf86fba1e36bad7ef191f9326963c34Test
https://doi.org/10.1155/2021/7777699Test

المؤلفون: Ye Chen, Chenhui Qiu, Wanru Cai

المصدر: Bioengineered
article-version (VoR) Version of Record
Bioengineered, Vol 13, Iss 1, Pp 697-708 (2022)

مصطلحات موضوعية: HSPB1, Respiratory Distress Syndrome, GYPE, Computational Biology, Bioengineering, General Medicine, Applied Microbiology and Biotechnology, T-Lymphocytes, Regulatory, Treg, Jurkat Cells, CD81, RPL22, Gene Expression Regulation, A549 Cells, Sepsis, Humans, ARDS, Databases, Nucleic Acid, TP248.13-248.65, Biotechnology, Research Article, Research Paper

الوصف: Regarding the extremely high mortality caused by sepsis-induced acute respiratory distress syndrome (ARDS), it is urgent to develop new biomarkers of sepsis-induced ARDS for treatment. Here, 532 differential expression genes (DEGs) related to sepsis and 433 DEGs related to sepsis-induced ARDS were screened in the GSE32707 dataset. Compared with sepsis samples, sepsis ARDS samples showed a higher infiltration of activated memory CD4 T cells and naive B cells, but a relatively lower infiltration of CD8 T cells. The pink and green modules which are significantly associated with sepsis-induced ARDS were then screened through co-expression network analysis. Differentially up-regulated GYPE and aberrantly down-regulated HSPB1, were subsequently found in the pink module of ARDS. CD81 and RPL22, two differentially low-expressed genes peculiar to ARDS, were identified in the green module. The function of CD81 was verified at the cellular level, and it was found that the up-regulation of CD81 in A549 could alleviate the LPS-induced injury of A549 cells. More importantly, the overexpressed CD81 can also increase the content of CD4+ CD25+ Foxp3+ Treg in Jurkat cells, and after the co-culture of overexpressed CD81 Jurkat cells with LPS treatment A549 cells, the LPS-induced lung epithelial cell damage can be improved. Overall, four new plasma biomarker candidates were found in sepsis-induced ARDS, and we verified that CD81 may play critical roles in the biological and immunological processes of sepsis-induced ARDS.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::26641bdaa053030555fcc5b1c674c968Test
http://europepmc.org/articles/PMC8805974Test

المؤلفون: Eric W Sayers, Evan E Bolton, J Rodney Brister, Kathi Canese, Jessica Chan, Donald C Comeau, Ryan Connor, Kathryn Funk, Chris Kelly, Sunghwan Kim, Tom Madej, Aron Marchler-Bauer, Christopher Lanczycki, Stacy Lathrop, Zhiyong Lu, Francoise Thibaud-Nissen, Terence Murphy, Lon Phan, Yuri Skripchenko, Tony Tse, Jiyao Wang, Rebecca Williams, Barton W Trawick, Kim D Pruitt, Stephen T Sherry

المصدر: Nucleic Acids Res

مصطلحات موضوعية: Internet, PubMed, 0303 health sciences, National Library of Medicine (U.S.), 030302 biochemistry & molecular biology, Computational Biology, Genomics, United States, 03 medical and health sciences, ComputingMethodologies_PATTERNRECOGNITION, 0302 clinical medicine, Databases, Genetic, Genetics, Humans, Database Issue, Databases, Nucleic Acid, Databases, Protein, 030217 neurology & neurosurgery, Databases, Chemical, Biotechnology, 030304 developmental biology

الوصف: The National Center for Biotechnology Information (NCBI) provides a large suite of online resources for biological information and data, including the GenBank® nucleic acid sequence database and the PubMed® database of citations and abstracts published in life science journals. The Entrez system provides search and retrieval operations for most of these data from 34 distinct databases. The E-utilities serve as the programming interface for the Entrez system. Custom implementations of the BLAST program provide sequence-based searching of many specialized datasets. New resources released in the past year include a new PubMed interface and NCBI datasets. Additional resources that were updated in the past year include PMC, Bookshelf, Genome Data Viewer, SRA, ClinVar, dbSNP, dbVar, Pathogen Detection, BLAST, Primer-BLAST, IgBLAST, iCn3D and PubChem. All of these resources can be accessed through the NCBI home page at https://www.ncbi.nlm.nih.govTest.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::986c142cdbab373f0978eb5ce073e98dTest
https://doi.org/10.1093/nar/gkab1112Test

المؤلفون: Ruoyao Lin, Jia-Yu Chen, Jun Hu, Qingxi Hu, Yongli Zhou, Liang Chen, Huichao Geng, Xiang-Dong Fu, Zhihao Huang, Xiaoming Zhong

المصدر: Nucleic Acids Research, vol 50, iss D1
Nucleic Acids Research

مصطلحات موضوعية: Transcription, Genetic, AcademicSubjects/SCI00010, Datasets as Topic, Context (language use), Genomics, Biology, Genome, Genomic Instability, Resource (project management), Cell Line, Tumor, Neoplasms, Protein Interaction Mapping, Genetics, Database Issue, Humans, Gene Regulatory Networks, Set (psychology), Internet, Chromosome Mapping, Computational Biology, Molecular Sequence Annotation, DNA, Multiple species, Data science, HEK293 Cells, RNA, Nervous System Diseases, R-Loop Structures, Databases, Nucleic Acid, Software

الوصف: R-loops play versatile roles in many physiological and pathological processes, and are of great interest to scientists in multiple fields. However, controversy about their genomic localization and incomplete understanding of their regulatory network raise great challenges for R-loop research. Here, we present R-loopBase (https://rloopbase.nju.edu.cnTest) to tackle these pressing issues by systematic integration of genomics and literature data. First, based on 107 high-quality genome-wide R-loop mapping datasets generated by 11 different technologies, we present a reference set of human R-loop zones for high-confidence R-loop localization, and spot conservative genomic features associated with R-loop formation. Second, through literature mining and multi-omics analyses, we curate the most comprehensive list of R-loop regulatory proteins and their targeted R-loops in multiple species to date. These efforts help reveal a global regulatory network of R-loop dynamics and its potential links to the development of cancers and neurological diseases. Finally, we integrate billions of functional genomic annotations, and develop interactive interfaces to search, visualize, download and analyze R-loops and R-loop regulators in a well-annotated genomic context. R-loopBase allows all users, including those with little bioinformatics background to utilize these data for their own research. We anticipate R-loopBase will become a one-stop resource for the R-loop community.

وصف الملف: application/pdf

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4f18daa4caebc008999e0f3f1aecdfe7Test
https://doi.org/10.1093/nar/gkab1103Test

المؤلفون: Xuping Jiang, Guangsheng Li, Lili Xiao, Zhijuan Lu, Xumei Jiang

المصدر: BioMed Research International
BioMed Research International, Vol 2021 (2021)

مصطلحات موضوعية: Genetic Markers, Article Subject, Geo database, Computational biology, General Biochemistry, Genetics and Molecular Biology, law.invention, law, microRNA, Humans, Medicine, KEGG, Gene, Polymerase chain reaction, Oligonucleotide Array Sequence Analysis, Gene expression omnibus, General Immunology and Microbiology, Signal Pathways, business.industry, Computational Biology, Parkinson Disease, General Medicine, MicroRNAs, Gene Ontology, Potential difference, Case-Control Studies, Databases, Nucleic Acid, business, Research Article, Signal Transduction

الوصف: Objective. This study is set out to explore the potential difference of miR in PD through GEO data and provide diagnostic indicators for clinical practice. Methods. In this study, differential miR was screened through the Gene Expression Omnibus (GEO) database, 68 PD patients treated in our hospital from May 2017 to March 2018 were collected as the research group (RG), and 50 normal subjects who underwent physical examination in our hospital during the same period were collected as the control group (CG). Quantitative real-time polymerase chain reaction (qRT-PCR) was used to detect the expression and diagnostic value of miR-374a-5p in serum of patients. The potential target genes of miR-374a-5p were predicted, and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Ontology Consortium (GO) were carried out. Results. GEO2R analysis revealed that 193 miRs are expressed differentially, of which 78 were highly expressed and 115 were poorly expressed. The miR-374a-5p expression in the serum of the RG was reduced markedly and had a diagnostic value. Targetscan and miRDB online websites were used to predict their target genes, with 415 common target genes. miR-374a-5p may participate in 27 functional pathways and 8 signal pathways. Conclusion. miR-335-5p has low expression in PD and is expected to be a potential diagnostic indicator.

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الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b432a7349a197d849f008e29ff17fed5Test
https://doi.org/10.1155/2021/8171236Test

المؤلفون: Yi-Ping Phoebe Chen, Annette McGrath, Noorul Amin

المصدر: IEEE/ACM Transactions on Computational Biology and Bioinformatics. 18:2795-2801

مصطلحات موضوعية: RNA, Untranslated, Sequence Analysis, RNA, Computer science, Applied Mathematics, Feature extraction, Univariate, FASTA format, Computational Biology, Feature selection, computer.software_genre, Machine Learning, Set (abstract data type), Exploratory data analysis, Identification (information), Genetics, Data mining, Databases, Nucleic Acid, computer, Algorithms, Software, Selection (genetic algorithm), Biotechnology

الوصف: Non-coding RNA (ncRNA) is involved in many biological processes and diseases in all species. Many ncRNA datasets exist that provide a sequential representation of data that best suits biomedical purposes. However, for ncRNA identification and analysis, statistical learning methods require hidden numerical features from the data. The extraction of hidden features, their analysis, and usage of a suitable set of features is crucial towards any statistical learning methods performance. Furthermore, a wealth of sequence intrinsic features has been proposed for ncRNA identification. Therefore, a systematic review and selection of these features are warranted. First, fasta format sequence datasets are generated from RNACentral representing many ncRNA types across a number of species. Next, a features dataset is created per fasta dataset consisting of 17 most frequently reported sequence intrinsic features. The features dataset is available from the FexRNA platform developed as part of this work. In addition, the features datasets are explored and analysed in terms of statistical information, univariate and bivariate analysis. For the feature selection (FS), a two-fold hierarchal FS framework based on majority voting and correlation is proposed and evaluated. Therefore, the FexRNA platform provides a useful platform for information about ncRNA features datasets, features analysis, and selection.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::90c73505fa9a2eb542c30001de2433d9Test
https://doi.org/10.1109/tcbb.2021.3057128Test

المؤلفون: Xin Wu, Tianyu Cui, Haibo Zhu, Hongyan Lin, Huasong Lu, Guanghao Liu, Yanting Ke, Kongfa Hu, Xin Han, Hao Fu, Jun He, Yehan Guo, Xiaoyang Zhao, Jiayi Zheng, Huaguo Shao, Lin Ning, Xiaopei Shen, Wenlin Li, Dong Wang

المصدر: Nucleic Acids Research

مصطلحات موضوعية: Organelles, Internet, AcademicSubjects/SCI00010, Cellular functions, RNA-Binding Proteins, RNA, Molecular Sequence Annotation, Saccharomyces cerevisiae, Computational biology, Plants, Biology, Phase Transition, Eukaryotic Cells, Phase (matter), Genetics, Database Issue, Animals, Humans, Databases, Nucleic Acid, Software, Function (biology)

الوصف: Liquid-liquid phase separation (LLPS) partitions cellular contents, underlies the formation of membraneless organelles and plays essential biological roles. To date, most of the research on LLPS has focused on proteins, especially RNA-binding proteins. However, accumulating evidence has demonstrated that RNAs can also function as ‘scaffolds’ and play essential roles in seeding or nucleating the formation of granules. To better utilize the knowledge dispersed in published literature, we here introduce RNAPhaSep (http://www.rnaphasep.cnTest), a manually curated database of RNAs undergoing LLPS. It contains 1113 entries with experimentally validated RNA self-assembly or RNA and protein co-involved phase separation events. RNAPhaSep contains various types of information, including RNA information, protein information, phase separation experiment information and integrated annotation from multiple databases. RNAPhaSep provides a valuable resource for exploring the relationship between RNA properties and phase behaviour, and may further enhance our comprehensive understanding of LLPS in cellular functions and human diseases.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cfb7be3a02c1594f28ed72e7890a7bd0Test
https://doi.org/10.1093/nar/gkab985Test

المؤلفون: Shiyong Liu, Sen Liu, Xu Hong, Xiaoxue Tong, Juan Xie, Xudong Liu, Jinfang Zheng, Qi Song

المصدر: RNA Biol

مصطلحات موضوعية: Models, Molecular, Structural alignment, Computational Biology, RNA, Cell Biology, Computational biology, Structural classification, Biology, G-Quadruplexes, Structure-Activity Relationship, RNA Databases, Cluster Analysis, Nucleic Acid Conformation, Nucleic acid structure, Databases, Nucleic Acid, Global structure, Molecular Biology, Algorithms, Software, Research Paper

الوصف: The three-dimensional (3D) structure of RNA usually plays an important role in the recognition with RNA-binding protein. Along with the discovering of RNAs, several RNA databases are developed to study the functions of RNA based on sequence, secondary structure, local 3D structural motif and global structure. Based on RNA function and structure, different RNAs are classified and stored in SCOR and DARTS, respectively. The classification of RNA structures is useful in RNA structure prediction and function annotation. However, the SCOR and DARTS are not updated any more. In this study, we present an RNA classification database RR3DD based on RNA fold with the global 3D structural similarity. The RR3DD includes 13,601 RNA chains from PDB and mmCIF format structures which are classified into 780 RNA folds. The RNA chains from PDB and mmCIF format structures are aligned and clustered into 675 and 220 RNA folds, respectively. By analysing the RNA structure in RR3DD, we find that there are 11 clusters with more than 50 members. These clusters include rRNAs, riboswitches, tRNAs and so on. By mapping RR3DD into Rfam, we found that some RNAs without annotation by Rfam can be annotated through structural alignment. For example, we analysed tRNAs and found that tRNA were successfully grouped in RR3DD for which Rfam did not classify them into one family. Finally, we provide a web interface of RR3DD offering functions of browsing RR3DD, annotating RNA 3D structure and finding templates for RNA homology modelling.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a8b68af84d2b61827b171b9ab919291dTest
https://doi.org/10.1080/15476286.2021.1989200Test

المؤلفون: Zirui Zhu, Rui Huang, Baojun Huang

المصدر: Exp Biol Med (Maywood)

مصطلحات موضوعية: Male, Bioinformatics analysis, Endogeny, Computational biology, Gastric carcinoma, Biology, Disease-Free Survival, General Biochemistry, Genetics and Molecular Biology, Stomach Neoplasms, Circular RNA, medicine, Humans, RNA, Messenger, RNA, Neoplasm, Gene, Original Research, Gene Expression Profiling, RNA, Cancer, RNA, Circular, medicine.disease, Gene Expression Regulation, Neoplastic, Survival Rate, MicroRNAs, Female, Databases, Nucleic Acid, Software

الوصف: Gastric cancer (GC) remains one of the most prevalent types of malignancies worldwide, and also one of the most reported lethal tumor-related diseases. Circular RNAs (circRNAs) have been certified to be trapped in multiple aspects of GC pathogenesis. Yet, the mechanism of this regulation is mostly undefined. This research is designed to discover the vital circRNA-microRNA (miRNA)-messenger RNA (mRNA) regulatory network in GC. Expression profiles with diverse levels including circRNAs, miRNAs, and mRNAs were all determined using microarray public datasets from Gene Expression Ominous (GEO). The differential circRNAs expressions were recognized against the published robust rank aggregation algorithm. Besides, a circRNA-based competitive endogenous RNA (ceRNA) interaction network was visualized via Cytoscape software (version 3.8.0). Functional and pathway enrichment analysis associated with differentially expressed targeted mRNAs were conducted using Cytoscape and an online bioinformatics database. Furthermore, an interconnected protein–protein interaction association network which consisted of 51 mRNAs was predicted, and hub genes were screened using STRING and CytoHubba. Then, several hub genes were chosen to explore their expression associated with survival rate and clinical stage in GEPIA and Kaplan-Meier Plotter databases. Finally, a carefully designed circRNA-related ceRNA regulatory subnetwork including four circRNAs, six miRNAs, and eight key hub genes was structured using the online bioinformatics tool.

الوصول الحر: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8b45c8cf8cfa057f79c2b8b6e11b6b71Test
https://doi.org/10.1177/15353702211048757Test