Biodiversity sequence datasets published in EMBL repositories in 2023 (NFDI4Biodiversity)
Ontology highlight
ABSTRACT:
ORGANISM(S): chionographis japonica Triticum aestivum (wheat) Hordeum vulgare (barley)
SUBMITTER:
PROVIDER: S-BSST1453 | biostudies-other |
SECONDARY ACCESSION(S): PRJEB48627
REPOSITORIES: biostudies-other
Similar Datasets
Project description: Not available
| S-BSST1455 | biostudies-other
Project description:Background:A considerable portion of primary biodiversity data is digitally locked inside published literature which is often stored as pdf files. Large-scale approaches to biodiversity science could benefit from retrieving this information and making it digitally accessible and machine-readable. Nonetheless, the amount and diversity of digitally published literature pose many challenges for knowledge discovery and retrieval. Text mining has been extensively used for data discovery tasks in large quantities of documents. However, text mining approaches for knowledge discovery and retrieval have been limited in biodiversity science compared to other disciplines. New information:Here, we present a novel, open source text mining tool, the Biodiversity Observations Miner (BOM). This web application, written in R, allows the semi-automated discovery of punctual biodiversity observations (e.g. biotic interactions, functional or behavioural traits and natural history descriptions) associated with the scientific names present inside a corpus of scientific literature. Furthermore, BOM enable users the rapid screening of large quantities of literature based on word co-occurrences that match custom biodiversity dictionaries. This tool aims to increase the digital mobilisation of primary biodiversity data and is freely accessible via GitHub or through a web server.
| S-EPMC6344444 | biostudies-literature
Project description:The increasing amount of publicly available research data provides the opportunity to link and integrate data in order to create and prove novel hypotheses, to repeat experiments or to compare recent data to data collected at a different time or place. However, recent studies have shown that retrieving relevant data for data reuse is a time-consuming task in daily research practice. In this study, we explore what hampers dataset retrieval in biodiversity research, a field that produces a large amount of heterogeneous data. In particular, we focus on scholarly search interests and metadata, the primary source of data in a dataset retrieval system. We show that existing metadata currently poorly reflect information needs and therefore are the biggest obstacle in retrieving relevant data. Our findings indicate that for data seekers in the biodiversity domain environments, materials and chemicals, species, biological and chemical processes, locations, data parameters and data types are important information categories. These interests are well covered in metadata elements of domain-specific standards. However, instead of utilizing these standards, large data repositories tend to use metadata standards with domain-independent metadata fields that cover search interests only to some extent. A second problem are arbitrary keywords utilized in descriptive fields such as title, description or subject. Keywords support scholars in a full text search only if the provided terms syntactically match or their semantic relationship to terms used in a user query is known.
| S-EPMC7990268 | biostudies-literature
Project description:Sharing of experimental clinical research data usually happens between individuals or research groups rather than via public repositories, in part due to the need to protect research participant privacy. This approach to data sharing makes it difficult to connect journal articles with their underlying datasets and is often insufficient for ensuring access to data in the long term. Voluntary data sharing services such as the Yale Open Data Access (YODA) and Clinical Study Data Request (CSDR) projects have increased accessibility to clinical datasets for secondary uses while protecting patient privacy and the legitimacy of secondary analyses but these resources are generally disconnected from journal articles-where researchers typically search for reliable information to inform future research. New scholarly journal and article types dedicated to increasing accessibility of research data have emerged in recent years and, in general, journals are developing stronger links with data repositories. There is a need for increased collaboration between journals, data repositories, researchers, funders, and voluntary data sharing services to increase the visibility and reliability of clinical research. Using the journal Scientific Data as a case study, we propose and show examples of changes to the format and peer-review process for journal articles to more robustly link them to data that are only available on request. We also propose additional features for data repositories to better accommodate non-public clinical datasets, including Data Use Agreements (DUAs).
| S-EPMC5793987 | biostudies-literature
Project description:The human microbiome project (HMP) has made it possible to test important ecological theories for arguably the most important ecosystem to human health-the human microbiome. Existing limited number of studies have reported conflicting evidence in the case of the neutral theory; the present study aims to comprehensively test the neutral theory with extensive HMP datasets covering all five major body sites inhabited by the human microbiome. Utilizing 7437 datasets of bacterial community samples, we discovered that only 49 communities (less than 1%) satisfied the neutral theory, and concluded that human microbial communities are not neutral in general. The 49 positive cases, although only a tiny minority, do demonstrate the existence of neutral processes. We realize that the traditional doctrine of microbial biogeography "Everything is everywhere, but the environment selects" first proposed by Baas-Becking resolves the apparent contradiction. The first part of Baas-Becking doctrine states that microbes are not dispersal-limited and therefore are neutral prone, and the second part reiterates that the freely dispersed microbes must endure selection by the environment. Therefore, in most cases, it is the host environment that ultimately shapes the community assembly and tip the human microbiome to niche regime.
| S-EPMC4985628 | biostudies-literature
Project description:With next-generation sequencing, the genomic data available for the characterization of integration sites (IS) has dramatically increased. At present, in a single experiment, several thousand viral integration genome targets can be investigated to define genomic hot spots. In a previous article, we renovated a formal CIS analysis based on a rigid fixed window demarcation into a more stretchy definition grounded on graphs. Here, we present a selection of supporting data related to the graph-based framework (GBF) from our previous article, in which a collection of common integration sites (CIS) was identified on six published datasets. In this work, we will focus on two datasets, ISRTCGD and ISHIV, which have been previously discussed. Moreover, we show in more detail the workflow design that originates the datasets.
| S-EPMC4874583 | biostudies-literature
Project description:BackgroundMultiple myeloma is a cancer which has a high occurrence rate and causes great injury to people worldwide. In recent years, many studies reported the effects of miRNA on the appearance of multiple myeloma. However, due to the differences of samples and sequencing platforms, a large number of inconsistent results have been generated among these studies, which limited the cure of multiple myeloma at the miRNA level.MethodsWe performed meta-analyses to identify the key miRNA biomarkers which could be applied on the treatment of multiple myeloma. The key miRNAs were determined by overlap comparisons of seven datasets in multiple myeloma. Then, the target genes for key miRNAs were predicted by the software TargetScan. Additionally, functional enrichments and binding TFs were investigated by DAVID database and Tfacts database, respectively.ResultsFirstly, comparing the normal tissues, 13 miRNAs were differently expressed miRNAs (DEMs) for at least three datasets. They were considered as key miRNAs, with 12 up-regulated (hsa-miR-106b, hsa-miR-125b, hsa-miR-130b, hsa-miR-138, hsa-miR-15b, hsa-miR-181a, hsa-miR-183, hsa-miR-191, hsa-miR-19a, hsa-miR-20a, hsa-miR-221 and hsa-miR-25) and one down-regulated (hsa-miR-223). Secondly, functional enrichment analyses indicated that target genes of the upregulated miRNAs were mainly transcript factors and enriched in transcription regulation. Besides, these genes were enriched in multiple pathways: the cancer signal pathway, insulin signal metabolic pathway, cell binding molecules, melanin generation, long-term regression and P53 signaling pathway. However, no significant enrichment was found for target genes of the down-regulated genes. Due to the distinct regulation function, four miRNAs (hsa-miR-19a has-miR-221 has-miR25 and has-miR223) were ascertained as the potential prognostic and diagnostic markers in MM. Thirdly, transcript factors analysis unveiled that there were 148 TFs and 60 TFs which bind target genes of the up-regulated miRNAs and target genes of the down-regulated miRNAs, respectively. They respectively generated 652 and 139 reactions of TFs and target genes. Additionally, 50 (31.6%) TFs were shared, while higher specificity was found in TFs of target genes for the upregulated miRNAs.DiscussionsTogether, our findings provided the key miRNAs which affected occurrence of multiple myeloma and regulation function of these miRNAs. It is valuable for the prognosis and diagnosis of multiple myeloma.
| S-EPMC5289111 | biostudies-literature
Project description:BackgroundBiological sequences are increasing rapidly and exponentially worldwide. Nucleotide sequence databases play an important role in providing meaningful genomic information on a variety of biological organisms.ResultsThe getSequenceInfo software tool allows to access sequence information from various public repositories (GenBank, RefSeq, and the European Nucleotide Archive), and is compatible with different operating systems (Linux, MacOS, and Microsoft Windows) in a programmatic way (command line) or as a graphical user interface. getSequenceInfo or gSeqI v1.0 should help users to get some information on queried sequences that could be useful for specific studies (e.g. the country of origin/isolation or the release date of queried sequences). Queries can be made to retrieve sequence data based on a given kingdom and species, or from a given date. This program allows the separation between chromosomes and plasmids (or other genetic elements/components) by arranging each component in a given folder. Some basic statistics are also performed by the program (such as the calculation of GC content for queried assemblies). An empirically designed nucleotide ratio is calculated using nucleotide information in order to tentatively provide a "NucleScore" for studied genome assemblies. Besides the main gSeqI tool, other additional tools have been developed to perform various tasks related to sequence analysis.ConclusionThe aim of this study is to democratize the use of public repositories in programmatic ways, and to facilitate sequence data analysis in a pedagogical perspective. Output results are available in FASTA, FASTQ, Excel/TSV or HTML formats. The program is freely available at: https://github.com/karubiotools/getSequenceInfo . getSequenceInfo and supplementary tools are partly available through the recently released Galaxy KaruBioNet platform ( http://calamar.univ-ag.fr/c3i/galaxy_karubionet.html ).
| S-EPMC9264741 | biostudies-literature
Project description:Rare variants are collectively numerous and may underlie a considerable proportion of complex disease risk. However, identifying genuine rare variant associations is challenging due to small effect sizes, presence of technical artefacts, and heterogeneity in population structure. We hypothesize that rare variant burden over a large number of genes can be combined into a predictive rare variant genetic risk score (RVGRS). We propose a method (RV-EXCALIBER) that leverages summary-level data from a large public exome sequencing database (gnomAD) as controls and robustly calibrates rare variant burden to account for the aforementioned biases. A calibrated RVGRS strongly associates with coronary artery disease (CAD) in European and South Asian populations by capturing the aggregate effect of rare variants through a polygenic model of inheritance. The RVGRS identifies 1.5% of the population with substantial risk of early CAD and confers risk even when adjusting for known Mendelian CAD genes, clinical risk factors, and a common variant genetic risk score.
| S-EPMC8494733 | biostudies-literature
Project description:Annotation of features, such as introns, exons and protein coding regions in GenBank/EMBL/DDBJ entries is now standardized through use of the Features Table (FT) language. The essence of the FT language is described by the relation 'expression-->sequence', meaning that each FT expression evaluates to a sequence. For example, the expression M74750:1..50 evaluates to the first 50 bases of the sequence with accession number M74750. Because FT is intrinsic to the database definition, it can serve as a software- and platform-independent lingua franca for sequence manipulation. The XYLEM package makes it possible to create and manipulate sequence datasets using FT expressions. FEATURES is a program that resolves FT expressions into their corresponding sequences. Annotated features can be retrieved either by feature key or by expression. Even unannotated portions of a sequence can be retrieved by user-generated FT expressions. Applications of the FT language include retrieval of subsequences from large sequence entries, generation of chromosome models or artificial DNA constructs, and representation of restriction maps or mutants.
| S-EPMC310486 | biostudies-literature