Search PubMed⌕ Search

SEARCH · Search PubMed

Results for “Dataset”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,531 records · Page 85Linked to original sources
PubMed2005

Systems-ADME/Tox: resources and network approaches.

The increasing cost of drug development is partially due to our failure to identify undesirable compounds at an early enough stage of development. The application of higher throughput screening methods have resulted in the generation of very large datasets from cells in vitro or from in vivo experiments following the treatment with drugs or known toxins. In recent years the development of systems biology, databases and pathway software has enabled the analysis of the high-throughput data in the context of the whole cell. One of the latest technology paradigms to be applied alongside the existing in vitro and computational models for absorption, distribution, metabolism, excretion and toxicology (ADME/Tox) involves the integration of complex multidimensional datasets, termed toxicogenomics. The goal is to provide a more complete understanding of the effects a molecule might have on the entire biological system. However, due to the sheer complexity of this data it may be necessary to apply one or more different types of computational approaches that have as yet not been fully utilized in this field. The present review describes the data generated currently and introduces computational approaches as a component of ADME/Tox. These methods include network algorithms and manually curated databases of interactions that have been separately classified under systems biology methods. The integration of these disparate tools will result in systems-ADME/Tox and it is important to understand exactly what data resources and technologies are available and applicable. Examples of networks derived with important drug transporters and drug metabolizing enzymes are provided to demonstrate the network technologies.

ATP Binding Cassette Transporter 1↗
PubMed2006

Variable intensity of purifying selection on cytotoxic T-lymphocyte epitopes in hepatitis C virus.

In an analysis of the patterns of nucleotide diversity in 26 datasets providing population-level data on different genomic regions of different hepatitis C virus (HCV) subtypes, known cytotoxic T-lymphocyte (CTL) epitope regions in most cases showed evidence of the occurrence of purifying selection. Two main factors were found to be associated with the strength of purifying selection: (1) purifying selection was stronger in CTL epitopes in non-envelope proteins than in envelope proteins and (2) purifying selection was stronger when the epitope was "matched", i.e., when the described or "canonical" epitope sequence was present unaltered in at least one sequence in the dataset. Of all polymorphic sites, non-synonymous sites in matched CTL epitopes in non-envelope proteins had the lowest gene diversities, implying that these variants are subject to ongoing purifying selection. This in turn suggests that the population frequency of such variants may of be the result of a balance between opposing forces: on the one hand, positive selection favoring escape mutants in hosts that express the presenting MHC molecule and, on the other hand, purifying selection acting, in the absence of the presenting MHC molecule, to reduce the frequency of slightly deleterious variants.

Epitopes, T-Lymphocyte↗
PubMed2026

Whole genome characterisation of Australian and New Zealand OsHV-1 'μVar' like variants over time.

Ostreid herpesvirus 1 (OsHV-1) is a major pathogen of Pacific oysters (Magallana gigas), linked to mass mortality events worldwide and presents a substantial threat to global aquaculture. Since 2010, mortality events have been occurring in Pacific oysters within Australia with the cause being an OsHV-1 microvariant highly similar to OsHV-1 μVar first detected in France, 2008. In this study, fifteen OsHV-1 whole genomes were assembled from Australian and New Zealand mortality events, including twelve newly sequenced genomes and three assembled from public datasets. Whole-genome phylogenetic analyses indicate that Australian and New Zealand OsHV-1 isolates form a distinct clade, separate from European and East Asian genomes, and with moderate regional and temporal divergence across the past 14 years. Across the dataset, multiple biologically relevant mutations were observed in genes of known function, including DNA polymerase, ribonucleotide reductase subunits, and apoptosis-related proteins, though most mutations occurred in uncharacterised genes. These findings highlight the limitations of single-gene typing and support the need for whole-genome approaches in understanding OsHV-1 evolution. Critically, the lack of recent whole-genome data, particularly from East and Southeast Asia, restricts the ability to trace viral origins and detect novel variants, underscoring the need for expanded global OsHV-1 genomic surveillance.

Australia↗
PubMed2005

Classification of bathing water quality based on the parametric calculation of percentiles is unsound.

Analyses of Irish bathing water quality data sets are reported to investigate whether the parametric calculations proposed in the draft Bathing Water Directive are valid. Faecal coliforms (assumed to be Escherichia coli) and faecal streptococci (assumed to be intestinal enterococci) have been analysed separately. It was noted that classifications based on the parametric 95th percentile calculations disagreed with those based on percentage compliance with the standards on 13.8% of occasions. When these disagreements were studied, it was found that the datasets frequently contained many censored data points (Result < 1). Also, the datasets were not log normally distributed on at least 85% of occasions. Both these findings fatally undermine the validity of using a parametric method for calculating 95th percentiles to classify bathing water quality. By contrast the non-parametric Hazen method is a better estimate of true population 95th percentiles, but essentially gives very similar classifications to the percentage compliance approach, fully agreeing on over 95% of occasions. The same is also true when considering 90th percentiles. A series of Monte Carlo studies were also conducted to determine the impact of small numbers. It was ascertained that small sample sizes are very undependable in determining bathing water classification and the parametric method in particular is particularly unreliable. In conclusion, the parametric method for calculating bathing water compliance is so severely and fatally flawed statistically that it should not form the basis of any legislation. The Hazen method gives a better estimate of true 90th or 95th percentiles, though as the resultant classifications agree with percentage compliance so closely it is doubtful that there is any statistical value in using a percentile approach over the long established and well understood percentage compliance approach.

Bathing Beaches↗
PubMed2024

Molecular adaptations in response to exercise training are associated with tissue-specific transcriptomic and epigenomic signatures.

Regular exercise has many physical and brain health benefits, yet the molecular mechanisms mediating exercise effects across tissues remain poorly understood. Here we analyzed 400 high-quality DNA methylation, ATAC-seq, and RNA-seq datasets from eight tissues from control and endurance exercise-trained (EET) rats. Integration of baseline datasets mapped the gene location dependence of epigenetic control features and identified differing regulatory landscapes in each tissue. The transcriptional responses to 8&#xa0;weeks of EET showed little overlap across tissues and predominantly comprised tissue-type enriched genes. We identified sex differences in the transcriptomic and epigenomic changes induced by EET. However, the sex-biased gene responses were linked to shared signaling pathways. We found that many G protein-coupled receptor-encoding genes are regulated by EET, suggesting a role for these receptors in mediating the molecular adaptations to training across tissues. Our findings provide new insights into the mechanisms underlying EET-induced health benefits across organs.

Animals↗
PubMed2024

Meningioma transcriptomic landscape demonstrates novel subtypes with regional associated biology and patient outcome.

Meningiomas, although mostly benign, can be recurrent and fatal. World Health Organization (WHO) grading of the tumor does not always identify high-risk meningioma, and better characterizations of their aggressive biology are needed. To approach this problem, we combined 13 bulk RNA sequencing (RNA-seq) datasets to create a dimension-reduced reference landscape of 1,298 meningiomas. The clinical and genomic metadata effectively correlated with landscape regions, which led to the identification of meningioma subtypes with specific biological signatures. The time to recurrence also correlated with the map location. Further, we developed an algorithm that maps new patients onto this landscape, where the nearest neighbors predict outcome. This study highlights the utility of combining bulk transcriptomic datasets to visualize the complexity of tumor populations. Further, we provide an interactive tool for understanding the disease and predicting patient outcomes. This resource is accessible via the online tool Oncoscape, where the scientific community can explore the meningioma landscape.

Meningioma↗
PubMed2025

In silico generation of synthetic cancer genomes using generative AI.

Understanding how genomic alterations drive cancer is key to advancing precision oncology. To detect these alterations, accurate algorithms are used; however, due to privacy concerns, few deeply sequenced cancer genomes can be shared, limiting benchmarking and representing a major obstacle to the improvement of analytic tools. To address this, we developed OncoGAN, a generative AI model combining adversarial networks and variational autoencoders to create realistic synthetic cancer genomes. Trained on large-scale genomic datasets, OncoGAN accurately reproduces somatic mutations, copy number alterations, and structural variants across cancer types while preserving donors' privacy. The synthetic genomes reflect tumor-specific mutational signatures and positional mutation patterns. Using DeepTumour, we validated the synthetic data's fidelity, showing high concordance between generated and predicted tumors. Moreover, augmenting the training data with synthetic genomes improved DeepTumour's accuracy, underscoring OncoGAN's potential to generate shareable datasets with known ground truths for benchmarking and enhancement of cancer genome analysis tools.

Humans↗
PubMed2025

Streamlining large-scale genomic data management: Insights from the UK Biobank whole-genome sequencing data.

Biobank-scale whole-genome sequencing (WGS) studies are increasingly pivotal in unraveling the genetic bases of diverse health outcomes. However, managing and analyzing these datasets' sheer volume and complexity presents significant challenges. We highlight the annotated genomic data structure (aGDS) format, substantially reducing the WGS data file size while enabling seamless integration of genomic and functional information for comprehensive WGS analyses. The aGDS format yielded 23 chromosome-specific files for the UK Biobank 500k WGS dataset, occupying only 1.10 tebibytes of storage. We develop the vcf2agds toolkit that streamlines the conversion of WGS data from VCF to aGDS format. Additionally, the STAARpipeline equipped with the aGDS files enabled scalable, comprehensive, and functionally informed WGS analysis, facilitating the detection of common and rare coding and noncoding phenotype-genotype associations. Overall, the vcf2agds toolkit and STAARpipeline provide a streamlined solution that facilitates efficient data management and analysis of biobank-scale WGS data across hundreds of thousands of samples.

Humans↗
PubMed2026

Reporting and representation of population descriptors in public RNA-seq databases.

Diverse and globally representative datasets are essential to genomic science and medicine. Here, we analyzed population descriptor metadata from RNA sequencing (RNA-seq) studies in two major public repositories: the Sequence Read Archive (SRA) and the Database of Genotypes and Phenotypes. We examined geographic and economic characteristics of institutions depositing the data and compared SRA-deposited descriptors to empirical estimates of genetic ancestry and to those reported in publications, analyzing trends over time. We found that 55% of RNA-seq samples were deposited by United States (US) institutions and 90% by institutions in high-income countries. Only 3% of SRA samples were associated with population descriptors, and among those with US Census terms, 69% were labeled as White. Among samples with continental descriptors, 56% were labeled as European. Our analyses emphasize widespread bias in the composition of public RNA-seq datasets and, more generally, a lack of consistent and careful reporting of population descriptors needing urgent improvement.

Humans↗
PubMed2026

DeepMASS v.2: An enhanced deep learning platform for large-scale discovery and structural annotation of unknown plant metabolites.

Determining the structures of unknown metabolites remains a fundamental bottleneck in plant metabolomics, as the vast chemical diversity of plant secondary metabolites far exceeds the coverage of existing spectral libraries. Here, we present DeepMASS v.2, a substantially enhanced platform for annotating unknown metabolites from liquid chromatography-tandem mass spectrometry data, designed to address this challenge at scale. DeepMASS v.2 leverages a semantic spectral representation model trained on millions of spectra from GNPS, NIST, and in-house resources. By integrating Spec2Vec-based embeddings with HNSW (hierarchical navigable small world) graph retrieval and a unified chemical space defined by molecular fingerprints, DeepMASS v.2 identifies structurally related neighbors of unknown spectra and ranks candidate structures according to their proximity to the predicted structural neighborhoods within chemical space. Benchmarking against Critical Assessment of Small Molecule Identification datasets and a curated natural product collection demonstrated that DeepMASS v.2 outperforms state-of-the-art in silico annotation tools, including SIRIUS, CFM-ID, MetFrag, and MS-Finder. Importantly, DeepMASS v.2 maintains strong performance for metabolites absent from spectral libraries, highlighting its capacity to annotate genuinely unknown compounds. Application of DeepMASS v.2 to large-scale plant metabolomics datasets demonstrated its ability to expand accessible metabolome coverage. Implemented as an intuitive web platform, DeepMASS v.2 provides the community with a scalable, interpretable, and high-throughput solution for structural annotation, enabling more comprehensive characterization of plant chemical diversity and accelerating natural product discovery in molecular plant science. The DeepMASS v.2 web server is publicly available at http://deepmass.cn.

Metabolomics↗
PubMed2004

Exploring the characteristics of sequence elements in proximal promoters of human genes.

Central to reconstruction of cis-regulatory networks is identification and classification of naturally occurring transcription factor-binding sites according to the genes that they control. We have examined salient characteristics of 9-mers that occur in various orders and combinations in the proximal promoters of human genes. In evaluations of a dataset derived with respect to experimentally defined transcription initiation sites, in some cases we observed a clear correspondence of highly ranked 9-mers with protein-binding sites in genomic DNA. Evaluations of the larger dataset, derived with respect to the 5' end of human ESTs, revealed that a subset of the highly ranked 9-mers corresponded to sites for several known transcription factor families (including CREB, ETS, EGR-1, SP1, KLF, MAZ, HIF-1, and STATs) that play important roles in the regulation of vertebrate genes. We identified several highly ranked CpG-containing 9-mers, defining sites for interactions with the CREB and ETS families of proteins, and identified potential target genes for these proteins. The results of the studies imply that the CpG-containing transcription factor-binding sites regulate the expression of genes with important roles in pathways leading to cell-type-specific gene expression and pathways controlled by the complex networks of signaling systems.

5' Untranslated Regions↗
PubMed2006

Comprehensive repertoire and phylogenetic analysis of the G protein-coupled receptors in human and mouse.

Understanding differences in the repertoire of orthologous gene pairs is vital for interpretation of pharmacological and physiological experiments if conclusions are conveyed between species. Here we present a comprehensive dataset for G protein-coupled receptors (GPCRs) in both human and mouse with a phylogenetic road map. We performed systematic searches applying several search tools such as BLAST, BLAT, and Hidden Markov models and searches in literature data. We aimed to gather a full-length version of each human or mouse GPCR in only one copy referring to a single chromosomal position. Moreover, we performed detailed phylogenetic analysis of the transmembrane regions of the receptors to establish accurate orthologous pairs. The results show the identity of 495 mouse and 400 human functional nonolfactory GPCRs. Overall, 329 of the receptors are found in one-to-one orthologous pairs, while 119 mouse and 31 human receptors originate from species-specific expansions or deletions. The average percentage similarity of the orthologue pairs is 85%, while it varies between the main GRAFS families from an average of 59 to 94%. The orthologous pairs for the lipid-binding GPCRs had the lowest levels of conservation, while the biogenic amines had highest levels of conservation. Moreover, we searched for expressed sequence tags (ESTs) and identified more than 17,000 ESTs matching GPCRs in mouse and human, providing information about their expression patterns. On the whole, this is the most comprehensive study of the gene repertoire that codes for human and mouse GPCRs. The datasets are available for downloading.

Animals↗
PubMed2004

Phylogenetic analysis of the nuclear alcohol dehydrogenase (Adh) gene family in Carex section Acrocystis (Cyperaceae) and combined analyses of Adh and nuclear ribosomal ITS and ETS sequences for inferring species relationships.

We analyzed sequence variation for the alcohol dehydrogenase (Adh) gene family in Carex section Acrocystis (Cyperaceae) to reconstruct Adh gene trees for Acrocystis species and to characterize the structure of the Adh gene family in Carex. Two Adh loci were included with ITS and ETS sequences in a combined Bayesian inference analysis of Carex section Acrocystis to gain a better understanding of species relationships in the section. In addition, we comment on how the results presented here contribute to our knowledge of the birth-death process of the Adh gene family in angiosperms. It appears that the structure of the Adh gene family in Carex is complex with possibly six loci present in the gene family. Additionally, variation among Acrocystis species within loci is quite low, and there is little phylogenetic resolution in the individual datasets. Bayesian inference analysis of the combined ITS, ETS, Adh1, and Adh2 datasets resulted in a moderately well-supported phylogenetic hypothesis of relationships in the section which is discussed in relation to previous hypotheses of relationships.

Alcohol Dehydrogenase↗
PubMed2005

A phylogeny of cycads (Cycadales) inferred from chloroplast matK gene, trnK intron, and nuclear rDNA ITS region.

Phylogenetic relationships among the three families and 12 living genera of cycads were reconstructed by distance and parsimony criteria using three markers: the chloroplast matK gene, the chloroplast trnK intron and the nuclear ITS/5.8S rDNA sequence. All datasets indicate that Cycadaceae (including only the genus Cycas) is remotely related to other cycads, in which Dioon was resolved as the basal-most clade, followed by Bowenia and a clade containing the remaining nine genera. Encephalartos and Lepidozamia are closer to each other than to Macrozamia. The African genus Stangeria is embedded within the New World subfamily Zamiodeae. Therefore, Bowenia is an unlikely sister to Stangeria, contrary to the view that they form the Stangeriaceae. The generic status of Dyerocycas and Chigua is unsupportable as they are paraphyletic with Cycas and the Zamia, respectively. Nonsense mutations in the matK gene and indels in the other two datasets lend evidence to reinforce the above conclusions. According to the phylogenies, the past geography of the genera of cycads and the evolution of character states are hypothesized and discussed. Within the suborder Zamiieae, Stangeria, and the tribe Zamieae evolved significantly faster than other genera. The matK gene and ITS/5.8S region contain more useful information than the trnK intron in addressing phylogeny. Redelimitations of Zamiaceae, Stangeriaceae, subfamily Encephalartoideae and subtribe Macrozamiineae are necessary.

Chloroplasts↗
PubMed2005

Phylogenetic analyses reveal deeply divergent species lineages in the genus Sphaerobolus (Phallales: Basidiomycota).

Phylogenetic analyses of 27 artillery fungus (Sphaerobolus sp.) isolates were conducted to identify species boundaries in the genus Sphaerobolus. Multiple gene genealogies inferred from maximum likelihood, Bayesian, and maximum-parsimony analyses of sequence data from individual loci (mtSSU, ITS, EF 1-alpha, and LSU) and a combined dataset (mtSSU, ITS, and EF 1-alpha) concordantly indicate the existence of three deeply divergent lineages in the genus Sphaerobolus, each representing a phylogenetic species. These three phylogenetic species correspond to two known species: Sphaerobolus iowensis and Sphaerobolus stellatus, and a newly discovered species. Suprageneric phylogenetic analyses of the mtSSU and LSU datasets containing representatives of related genera of the gomphoid-phalloid clade of Homobasidiomycetes suggested that the undescribed taxon likely is more closely related to S. stellatus than to S. iowensis.

Base Sequence↗
PubMed2005

A preliminary phylogeny of the Pentatomomorpha (Hemiptera: Heteroptera) based on nuclear 18S rDNA and mitochondrial DNA sequences.

Pentatomomorpha is the second suborder in size only to Cimicomorpha in Heteroptera. However, the phylogenetic relationships among members of the suborder are not well established. Sequences from partial nuclear ribosomal 18S gene and mitochondrial COX1 gene were analyzed separately and in combination to generate a preliminary molecular phylogeny of Pentatomomorpha based on 40 species representing 17 putative families. Analyses of the combined sequence data provided a better-resolved and more robust hypothesis of Pentatomomorpha phylogeny than did separate analyses of the individual genes. The phylogenies were mostly congruent with morphological studies. Results strongly supported the monophyly of the infraorder Pentatomomorpha, and the placement of Aradoidea as sister to Trichophora. The monophyletic Trichophora was grouped into two major lineages, one being the superfamily Pentatomoidea, and the other comprising Lygaeoidea, Coreoidea, and Pyrrhocoroidea. The analysis of the ML and ME trees of combined dataset supported the monophyletic Pentatomoidea. In all analysis the Pyrrhocoroidea was polyphyletic; the monophyletic Lygaeoidea was supported only in the analysis of ME tree, and Coreoidea was polyphyletic except in the MP tree of combined dataset. The molecular and morphylogical data both indicated that the family Coreoidae should be revised subsequently. Our phylogenetic results suggested that the COX1 segment alone might not be an optimal molecular marker for the phylogeny of Pentatomomorpha.

Animals↗
PubMed2005

New insights into the phylogeny of fig pollinators using Bayesian analyses.

The interaction between figs and fig pollinators is one of the most species-specific mutualisms. Recently, phylogenies of both partners based on molecular data provided insights into a wide spectrum of co-evolutionary questions. However, for the phylogeny of fig pollinators, there are some discrepancies between different studies and left some relationships unresolved, especially for deep nodes. The phylogenetic uncertainties of pollinators prohibit our further understanding of the history of the mutualism. Here, we present phylogenetic analyses of a larger COI sequence dataset that includes previously published datasets and our sequences from 20 species using Bayesian method and maximum parsimony. The analyses using different methods share similar topologies. Bayesian analyses provide high level of confidence for most internal nodes in terms of posterior probability. This study also clarifies some discrepancies between previous studies. After rooting with Tetrapus, other pollinators split into two clades. Wiebesia and Blastophaga are at basal positions in respective clade. Ceratosolen is not monophyletic because Kradibia and Liporrhopalum fall inside this group. Three subgenera of Ceratosolen: subgen. Ceratosolen, subgen. Rothropus, and subgen. Strepitus are not supported. Therefore, Ceratosolen is suggested to be re-divided into three groups. Urostigma pollinators (including Dolichoris and Blastophaga psenes) are clustered together. The monophylies of Wiebesia, Blastophaga, Dolichoris are not supported in this analysis. This study also provides a new framework for re-evaluating character evolution and re-inspecting the definition of some genera.

Animals↗
PubMed2006

Evolution of mitochondrial relationships and biogeography of Palearctic green toads (Bufo viridis subgroup) with insights in their genomic plasticity.

Taxa involving three bisexually reproducing ploidy levels make green toads a unique amphibian system. We put a cytogenetic dataset from Central Asia in a molecular framework and apply phylogenetic and demographic methods to data from the entire Palearctic range. We study the mitochondrial relationships of diploids to infer their phylogeography and the maternal ancestry of polyploids. Control regions (and tRNAs between ND1 and ND2 in representatives) characterize a deeply branched assemblage of twelve haplotype groups, diverged since the Lower Miocene. Polyploidy has evolved several times: Central Asian tetraploids (B. oblongus, B. pewzowi) have at least two maternal origins. Intriguingly, the mitochondrial ancestor of morphologically distinctive, sexually reproducing triploid taxa (B. pseudoraddei) from Karakoram and Hindukush represents a different lineage. We report another potential case of bisexual triploid toads (B. zugmayeri). Identical d-loops in diploids and tetraploids from Iran and Turkmenistan, which differ in morphology, karyotypes and calls, suggest multiple origins and retained polymorphism and/or hybridization. A similar system involves diploids, triploids and tetraploids from Kyrgyzstan and Kazakhstan where green toads exemplify vertebrate genomic plasticity. A new form from Sicily and its African sister species (B. boulengeri) allow internal calibration and divergence time estimates for major clades. The subgroup may have originated in Eurasia rather than Africa since the earliest diverged lineages (B. latastii, B. surdus) and earliest fossils occur in Asia. We delineate ranges, contact and hybrid zones. Phylogeography, including one of the first non-avian datasets from Central Asian high mountains, reflects Quaternary climate and glaciation.

Africa, Northern↗