A Curated, Comprehensive Database of Plasmid Sequences.
Ontology highlight
ABSTRACT:
SUBMITTER: Brooks L
PROVIDER: S-EPMC6318356 | biostudies-literature | 2019 Jan
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:The PharmacoGenomic Mutation Database (PGMD) is a comprehensive manually curated pharmacogenomics database. Two major sources of PGMD data are peer-reviewed literature and Food and Drug Administration (FDA) and European Medicines Agency (EMA) drug labels. PGMD curators capture information on exact genomic location and sequence changes, on resulting phenotype, drugs administered, patient population, study design, disease context, statistical significance and other properties of reported pharmacogenomic variants. Variants are annotated into functional categories on the basis of their influence on pharmacokinetics, pharmacodynamics, efficacy or clinical outcome. The current release of PGMD includes over 117 000 unique pharmacogenomic observations, covering all 24 disease superclasses and nearly 1400 drugs. Over 2800 genes have associated pharmacogenomic variants, including genes in proximity to intergenic variants. PGMD is optimized for use in annotating next-generation sequencing data by providing genomic coordinates for all covered variants, including Single Nucleotide Polymorphisms (SNPs), insertions, deletions, haplotypes, diplotypes, Variable Number Tandem Repeats (VNTR), copy number variations and structural variations.
| S-EPMC4819767 | biostudies-literature
Project description:The ability to decode antigen specificities encapsulated in the sequences of rearranged T-cell receptor (TCR) genes is critical for our understanding of the adaptive immune system and promises significant advances in the field of translational medicine. Recent developments in high-throughput sequencing methods (immune repertoire sequencing technology, or RepSeq) and single-cell RNA sequencing technology have allowed us to obtain huge numbers of TCR sequences from donor samples and link them to T-cell phenotypes. However, our ability to annotate these TCR sequences still lags behind, owing to the enormous diversity of the TCR repertoire and the scarcity of available data on T-cell specificities. In this paper, we present VDJdb, a database that stores and aggregates the results of published T-cell specificity assays and provides a universal platform that couples antigen specificities with TCR sequences. We demonstrate that VDJdb is a versatile instrument for the annotation of TCR repertoire data, enabling a concatenated view of antigen-specific TCR sequence motifs. VDJdb can be accessed at https://vdjdb.cdr3.net and https://github.com/antigenomics/vdjdb-db.
| S-EPMC5753233 | biostudies-literature
Project description:Discoveries over the recent decade have demonstrated the unexpected diversity of telomere DNA motifs in nature. However, currently available resources, 'Telomerase database' and 'Plant rDNA database', contain just fragments of all relevant literature published over decades of telomere research as they have a different primary focus and limited updates. To fill this gap, we gathered data about telomere DNA sequences from a thorough literature screen as well as by analysing publicly available NGS data, and we created TeloBase (http://cfb.ceitec.muni.cz/telobase/) as a comprehensive database of information about telomere motif diversity. TeloBase is supplemented by internal taxonomy utilizing popular on-line taxonomic resources that enables in-house data filtration and graphical visualisation of telomere DNA evolutionary dynamics in the form of heat tree plots. TeloBase avoids overreliance on administrators for future data updates by having a simple form and community-curation system for application and approval, respectively, of new telomere sequences by users, which should ensure timeliness of the database and topicality. To demonstrate TeloBase utility, we examined telomere motif diversity in species from the fungal genus Aspergillus, and discovered (TTTATTAGGG)n sequence as a putative telomere motif in the plant family Chrysobalanaceae. This was bioinformatically confirmed by analysing template regions of identified telomerase RNAs.
| S-EPMC10767889 | biostudies-literature
Project description:RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. The website has been subject to continuous improvements focusing on text and sequence similarity searches as well as genome browsing functionality. All RNAcentral data is provided for free and is available for browsing, bulk downloads, and programmatic access at http://rnacentral.org/.
| S-EPMC5210518 | biostudies-literature
Project description:BACKGROUND:Sigma (?) receptors are accepted as a particular receptor class consisting of two subtypes: sigma-1 (?1) and sigma-2 (?2). The two receptor subtypes have specific drug actions, pharmacological profiles and molecular characteristics. The ?2 receptor is overexpressed in several tumor cell lines, and its ligands are currently under investigation for their role in tumor diagnosis and treatment. The ?2 receptor structure has not been disclosed, and researchers rely on ?2 receptor radioligand binding assay to understand the receptor's pharmacological behavior and design new lead compounds. DESCRIPTION:Here we present the sigma-2 Receptor Selective Ligands Database (S2RSLDB) a manually curated database of the ?2 receptor selective ligands containing more than 650 compounds. The database is built with chemical structure information, radioligand binding affinity data, computed physicochemical properties, and experimental radioligand binding procedures. The S2RSLDB is freely available online without account login and having a powerful search engine the user may build complex queries, sort tabulated results, generate color coded 2D and 3D graphs and download the data for additional screening. CONCLUSION:The collection here reported is extremely useful for the development of new ligands endowed of ?2 receptor affinity, selectivity, and appropriate physicochemical properties. The database will be updated yearly and in the near future, an online submission form will be available to help with keeping the database widely spread in the research community and continually updated. The database is available at http://www.researchdsf.unict.it/S2RSLDB. GRAPHICAL ABSTRACT:
| S-EPMC5250622 | biostudies-literature
Project description:Recent advances in the proteomics field have allowed a series of high throughput experiments to be conducted on chloroplast samples, and the data are available in several public databases. However, the accurate localization of many chloroplast proteins often remains hypothetical. This is especially true for envelope proteins. We went a step further into the knowledge of the chloroplast proteome by focusing, in the same set of experiments, on the localization of proteins in the stroma, the thylakoids, and envelope membranes. LC-MS/MS-based analyses first allowed building the AT_CHLORO database (http://www.grenoble.prabi.fr/protehome/grenoble-plant-proteomics/), a comprehensive repertoire of the 1323 proteins, identified by 10,654 unique peptide sequences, present in highly purified chloroplasts and their subfractions prepared from Arabidopsis thaliana leaves. This database also provides extensive proteomics information (peptide sequences and molecular weight, chromatographic retention times, MS/MS spectra, and spectral count) for a unique chloroplast protein accurate mass and time tag database gathering identified peptides with their respective and precise analytical coordinates, molecular weight, and retention time. We assessed the partitioning of each protein in the three chloroplast compartments by using a semiquantitative proteomics approach (spectral count). These data together with an in-depth investigation of the literature were compiled to provide accurate subplastidial localization of previously known and newly identified proteins. A unique knowledge base containing extensive information on the proteins identified in envelope fractions was thus obtained, allowing new insights into this membrane system to be revealed. Altogether, the data we obtained provide unexpected information about plastidial or subplastidial localization of some proteins that were not suspected to be associated to this membrane system. The spectral counting-based strategy was further validated as the compartmentation of well known pathways (for instance, photosynthesis and amino acid, fatty acid, or glycerolipid biosynthesis) within chloroplasts could be dissected. It also allowed revisiting the compartmentation of the chloroplast metabolism and functions.
| S-EPMC2877971 | biostudies-literature
Project description:Mitotic catastrophe (MC) is a form of programmed cell death induced by mitotic process disorders, which is very important in tumor prevention, development, and drug resistance. Because rapidly increased data for MC is vigorously promoting the tumor-related biomedical and clinical study, it is urgent for us to develop a professional and comprehensive database to curate MC-related data. Mitotic Catastrophe Database (MCDB) consists of 1214 genes/proteins and 5014 compounds collected and organized from more than 8000 research articles. Also, MCDB defines the confidence level, classification criteria, and uniform naming rules for MC-related data, which greatly improves data reliability and retrieval convenience. Moreover, MCDB develops protein sequence alignment and target prediction functions. The former can be used to predict new potential MC-related genes and proteins, and the latter can facilitate the identification of potential target proteins of unknown MC-related compounds. In short, MCDB is such a proprietary, standard, and comprehensive database for MC-relate data that will facilitate the exploration of MC from chemists to biologists in the fields of medicinal chemistry, molecular biology, bioinformatics, oncology and so on. The MCDB is distributed on http://www.combio-lezhang.online/MCDB/index_html/.
| S-EPMC8546929 | biostudies-literature
Project description:A systematic literature review was conducted to identify Hershberger bioassays for ∼3200 chemicals including those used to validate the OECD/US EPA guideline assay, US EPA's chemicals screened for endocrine activity, and the library of chemicals run in US EPA 's ToxCast in vitro assays. For 134 chemicals that met pre-defined criteria, experimental results were extracted into a database used to characterize uncertainty in results and evaluate the concordance of the Hershberger assay with other in vivo rodent studies that measure androgen-responsive endpoints. Of 25 chemicals tested in >1 Hershberger study, 28% had disagreements between studies (i.e. ≥1 positive and ≥1 negative study), and of the 65 chemicals tested in Hershberger studies and other in vivo studies with androgen-responsive endpoints, 43% indicated disagreements, though in some cases these may be explained by differences in study designs or physiology of the animal model. Ultimately, 49 chemicals were identified with reproducible androgen pathway responses confirmed in ≥2 in vivo rodent studies that could be considered reference chemicals useful for validating alternative methods.
| S-EPMC6711601 | biostudies-literature
Project description:Anti-Microbial Peptide Database version 1 (AMPDB v1) is a meticulously curated resource that aims to address the limitations of existing databases in the field of antimicrobial research. We have utilized the latest technology and put our best efforts into adding all relevant tools to cater to the needs of our users. AMPDB v1 is a derived database, built upon information gathered from the available resources and boasts a significant size of 59,122 entries which are classified into 88 classes. All the information in this resource was curated manually. Sequence alignment and protein feature calculation tools were integrated into the database in the form of web applications, to make them easy to use, quick, and responsive in real-time. We have included multiple types of browsing and searching options to enhance the user experience, from simple text search to a completely customizable advanced search page with intuitive options that let the user combine multiple options together to make a powerful search query. The database is accessible by a web browser at https://bblserver.org.in/ampdb/ .
| S-EPMC10587344 | biostudies-literature