Ontology highlight
ABSTRACT:
PROVIDER: PRJEB26399 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:The purpose of this work was to describe a computational and analytical methodology for profiling small RNA by high-throughput sequencing. The datasets here were used to assess the reproducibility of small RNA datasets produced using Illumina sequencing-by-synthesis technology (SBS). We analyzed the reproducibility of small RNA SBS datasets by comparing libraries generated for biological replicates (rep1 and rep2) and technical replicates (rep2 and rep3).
2009-06-02 | E-GEOD-14694 | biostudies-arrayexpress
Project description:In recent years genomic and proteomic technologies have been employed in a combined effort to extrapolate key clinical and biological information of complex diseases such as cancer. Most integrative studies employ DNA and/or RNA sequencing technologies coupled to mass spectrometry-derived information to achieve deep information extraction levels, resulting in massive experimental efforts. In this context the employment of data independent acquisition (DIA) methods, which generally do not rely on fractionation, has seldom been tested. In this study, we evaluated the ability of DIA and data dependent acquisition (DDA) MS in determining key biological features of a set of 21 breast cancer tissues for whose RNA-sequencing data was also collected. We evaluated how proteomic data layers matched RNA analysis-derived genomic information, their degree of consensus, and their discrepancies.
2021-04-26 | PXD018830 | Pride
Project description:In recent years genomic and proteomic technologies have been employed in a combined effort to extrapolate key clinical and biological information of complex diseases such as cancer. Most integrative studies employ DNA and/or RNA sequencing technologies coupled to mass spectrometry-derived information to achieve deep information extraction levels, resulting in massive experimental efforts. In this context the employment of data independent acquisition (DIA) methods, which generally do not rely on fractionation, has seldom been tested. In this study, we evaluated the ability of DIA and data dependent acquisition (DDA) MS in determining key biological features of a set of 21 breast cancer tissues for whose RNA-sequencing data was also collected. We evaluated how proteomic data layers matched RNA analysis-derived genomic information, their degree of consensus, and their discrepancies.
2021-04-26 | PXD021394 | Pride
Project description:In this study we developed metaproteomics based methods for quantifying taxonomic composition of microbiomes (microbial communities). We also compared metaproteomics based quantification to other quantification methods, namely metagenomics and 16S rRNA gene amplicon sequencing. The metagenomic and 16S rRNA data can be found in the European Nucleotide Archive (Study number: PRJEB19901). For the method development and comparison of the methods we analyzed three types of mock communities with all three methods. The communities contain between 28 to 32 species and strains of bacteria, archaea, eukaryotes and bacteriophage. For each community type 4 biological replicate communities were generated. All four replicates were analyzed by 16S rRNA sequencing and metaproteomics. Three replicates of each community type were analyzed with metagenomics. The "C" type communities have same cell/phage particle number for all community members (C1 to C4). The "P" type communities have the same protein content for all community members (P1 to P4). The "U" (UNEVEN) type communities cover a large range of protein amounts and cell numbers (U1 to U4). We also generated proteomic data for four pure cultures to test the specificity of the protein inference method. This data is also included in this submission.
2017-05-12 | PXD006118 | Pride
Project description:Nowadays, given the globalization as well as the numerous technological developments and innovations that govern the food market, consumer’s expectations, regarding the food they eat, have increased and the information they receive should be at least reliable. This proof-of- concept study is the first analysis of potato tuber tissue using integrated multi-omics approaches across genome-wide DNA methylation, RNA sequencing and quantitative proteomics to obtain the molecular portrait of famous PGI potatoes of Naxos island. Furthermore, we used metagenomics analysis in order to discriminate potato tubers produced in diverse PGI regions based on the distinct microbiological patterns. Hence, we reveal key molecular factors related to harvest and post-harvest through the dynamics of causal models.
2023-03-11 | PXD035074 | Pride
Project description:Microbiome sequencing model is a Named Entity Recognition (NER) model that identifies and annotates microbiome nucleic acid sequencing method or platform in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with sequencing metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications
2022-02-21 | MODEL2202170012 | BioModels