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Authors:Klein K; Garkov D, Rütschlin S, et al. First page: baab071 PubDate: Fri, 26 Nov 2021 00:00:00 GMT DOI: 10.1093/database/baab071 Issue No:Vol. 2021, No. 2021 (2021)
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Authors:Klein K; Garkov D, Rütschlin S, et al. First page: baab058 Abstract: AbstractThe human microbiome is largely shaped by the chemical interactions of its microbial members, which includes cross-talk via shared signals or quenching of the signalling of other species. Quorum sensing is a process that allows microbes to coordinate their behaviour in dependence of their population density and to adjust gene expression accordingly. We present the Quorum Sensing Database (QSDB), a comprehensive database of all published sensing and quenching relations between organisms and signalling molecules of the human microbiome, as well as an interactive web interface that allows browsing the database, provides graphical depictions of sensing mechanisms as Systems Biology Graphical Notation diagrams and links to other databases.Database URL: QSDB (Quorum Sensing DataBase) is freely available via an interactive web interface and as a downloadable csv file at http://qsdb.org. PubDate: Fri, 26 Nov 2021 00:00:00 GMT DOI: 10.1093/database/baab058 Issue No:Vol. 2021, No. 2021 (2021)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:Tawfik N; Spruit M. First page: baab070 PubDate: Wed, 24 Nov 2021 00:00:00 GMT DOI: 10.1093/database/baab070 Issue No:Vol. 2021, No. 2021 (2021)
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Authors:Emerson I; Chitluri K. First page: baab066 Abstract: AbstractProtein domains are functional and structural units of proteins. They are responsible for a particular function that contributes to protein’s overall role. Because of this essential role, the majority of the genetic variants occur in the domains. In this study, the somatic mutations across 21 cancer types were mapped to the individual protein domains. To map the mutations to the domains, we employed the whole human proteome to predict the domains in each protein sequence and recognized about 149 668 domains. A novel Perl-API program was developed to convert the protein domain positions into genomic positions, and users can freely access them through GitHub. We determined the distribution of protein domains across 23 chromosomes with the help of these genomic positions. Interestingly, chromosome 19 has more number of protein domains in comparison with other chromosomes. Then, we mapped the cancer mutations to all the protein domains. Around 46–65% of mutations were mapped to their corresponding protein domains, and significantly mutated domains for all the cancer types were determined using the local false discovery ratio (locfdr). The chromosome positions for all the protein domains can be verified using the cross-reference ensemble database.Database URL: https://dcmp.vit.ac.in/ PubDate: Sat, 13 Nov 2021 00:00:00 GMT DOI: 10.1093/database/baab066 Issue No:Vol. 2021, No. 2021 (2021)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:Wu J; Zhao M, Li T, et al. First page: baab076 Abstract: AbstractAs the terminal clinical phenotype of almost all types of cardiovascular diseases, heart failure (HF) is a complex and heterogeneous syndrome leading to considerable morbidity and mortality. Existing HF-related omics studies mainly focus on case/control comparisons, small cohorts of special subtypes, etc., and a large amount of multi-omics data and knowledge have been generated. However, it is difficult for researchers to obtain biological and clinical insights from these scattered data and knowledge. In this paper, we built the Heart Failure Integrated Platform (HFIP) for data exploration, fusion analysis and visualization by collecting and curating existing multi-omics data and knowledge from various public sources and also provided an auto-updating mechanism for future integration. The developed HFIP contained 253 datasets (7842 samples), multiple analysis flow, and 14 independent tools. In addition, based on the integration of existing databases and literature, a knowledge base for HF was constructed with a scoring system for evaluating the relationship between molecular signals and HF. The knowledge base includes 1956 genes and annotation information. The literature mining module was developed to assist the researcher to overview the hotspots and contexts in basic and clinical research. HFIP can be used as a data-driven and knowledge-guided platform for the basic and clinical research of HF.Database URL: http://heartfailure.medical-bigdata.com PubDate: Sat, 13 Nov 2021 00:00:00 GMT DOI: 10.1093/database/baab076 Issue No:Vol. 2021, No. 2021 (2021)
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Authors:Dziurzyński M; Decewicz P, Iskra M, et al. First page: baab073 Abstract: AbstractThe genus Prototheca houses unicellular, achlorophyllous, yeast-like algae, widely distributed in the environment. Protothecae are the only known plants that have repeatedly been reported to infect vertebrates, including humans. Although rare, protothecosis can be clinically demanding, with an unpredictable and treatment-resistant behavior. Accurate identification of Prototheca species relies upon DNA sequence-based typing of the mitochondrially encoded CYTB gene. However, no bioinformatic tool for the processing and analyzing of protothecal sequence data exists. Moreover, currently available sequence databases suffer from a limited number of records and lack of or flawed sequence annotations, making Prototheca identification challenging and often inconclusive. This report introduces the Prototheca-ID, a user-friendly, web-based application providing fast and reliable speciation of Prototheca isolates. In addition, the application offers the users the possibility of depositing their sequences and associated metadata in a fully open Prototheca-ID database, developed to enhance research integrity and quality in the field of Protothecae and protothecosis.Database URL: The Prototheca-ID application is available at https://prototheca-id.org PubDate: Sat, 13 Nov 2021 00:00:00 GMT DOI: 10.1093/database/baab073 Issue No:Vol. 2021, No. 2021 (2021)
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Authors:Nowis K; Jackowiak P, Figlerowicz M, et al. First page: baab074 Abstract: AbstractCircular RNAs (circRNAs) are a large class of noncoding RNAs with functions that, in most cases, remain unknown. Recent genome-wide analysis of circRNAs using RNA-Seq has revealed that circRNAs are abundant and some of them conserved in plants. Furthermore, it has been shown that the expression of circRNAs in plants is regulated in a tissue-specific manner. Arabidopsis thaliana circular RNA database is a new resource designed to integrate and standardize the data available for circRNAs in a model plant A. thaliana, which is currently the best-characterized plant in terms of circRNAs. The resource integrates all applicable publicly available RNA-seq datasets. These datasets were subjected to extensive reanalysis and curation, yielding results in a unified format. Moreover, all data were normalized according to our optimized approach developed for circRNA identification in plants. As a result, the database accommodates circRNAs identified across organs and seedlings of wild-type A. thaliana and its single-gene knockout mutants for genes related to splicing. The database provides free access to unified data and search functionalities, thus enabling comparative analyses of A. thaliana circRNAs between organs, variants and studies for the first time.Database URLhttps://plantcircrna.ibch.poznan.pl/ PubDate: Thu, 11 Nov 2021 00:00:00 GMT DOI: 10.1093/database/baab074 Issue No:Vol. 2021, No. 2021 (2021)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:Akiyama S; Higaki S, Ochiya T, et al. First page: baab072 Abstract: AbstractMicroRNAs (miRNAs) are small non-coding RNAs shown to regulate gene expression by binding to complementary transcripts. Genetic variants, including single-nucleotide polymorphisms and short insertions/deletions, contribute to traits and diseases by influencing miRNA expression. However, the association between genetic variation and miRNA expression remains to be elucidated. Here, by using genotype data and miRNA expression data from 3448 Japanese serum samples, we developed a computational pipeline to systematically identify genome-wide miRNA expression quantitative trait loci (miR-eQTLs). Not only did we identify a total of 2487 cis-miR-eQTLs and 3 155 773 trans-miR-eQTLs at a false discovery rate of <0.05 in six dementia types (Alzheimer’s disease, dementia with Lewy bodies, vascular dementia, frontotemporal lobar degeneration, normal-pressure hydrocephalus and mild cognitive impairment) and all samples, including those from patients with other types of dementia, but also we examined the commonality and specificity of miR-eQTLs among dementia types. To enable data searching and downloading of these cis- and trans-eQTLs, we developed a user-friendly database named JAMIR-eQTL, publicly available at https://www.jamir-eqtl.org/. This is the first miR-eQTL database designed for dementia types. Our integrative and comprehensive resource will contribute to understanding the genetic basis of miRNA expression as well as to the discovery of deleterious mutations, particularly in dementia studies.Database URL: https://www.jamir-eqtl.org/ PubDate: Wed, 03 Nov 2021 00:00:00 GMT DOI: 10.1093/database/baab072 Issue No:Vol. 2021, No. 2021 (2021)
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