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294 results for “data discovery”
Data from: Shifting milestones of natural sciences: the ancient Egyptian discovery of Algol's period confirmed
The Ancient Egyptians wrote Calendars of Lucky and Unlucky Days that assigned astronomically influenced prognoses for each day of the year. The best preserved of these calendars is the Cairo Calendar (hereafter CC) dated to 1244–1163 B.C. We have presented evidence that the 2.85 days period in the lucky prognoses of CC is equal to that of the eclipsing binary Algol during this historical era. We wanted to find out the vocabulary that represents Algol in the mythological texts of CC. Here we show that Algol was represented as Horus and thus signified both divinity and kingship. The texts describing the actions of Horus are consistent with the course of events witnessed by any naked eye observer of Algol. These descriptions support our claim that CC is the oldest preserved historical document of the discovery of a variable star. The period of the Moon, 29.6 days, has also been discovered in CC. We show that the actions of Seth were connected to this period, which also strongly regulated the times described as lucky for Heaven and for Earth. Now, for the first time, periodicity is discovered in the descriptions of the days in CC. Unlike many previous attempts to uncover the reasoning behind the myths of individual days, we discover the actual rules in the appearance and behaviour of deities during the whole year.
Data from: Trends in anesthesiology research: a machine learning approach to theme discovery and summarization
Objectives: Traditionally, summarization of research themes and trends within a given discipline was accomplished by manual review of scientific works in the field. However, with the ushering in of the age of "big data", new methods for discovery of such information become necessary as traditional techniques become increasingly difficult to apply due to the exponential growth of document repositories. Our objectives are to develop a pipeline for unsupervised theme extraction and summarization of thematic trends in document repositories, and to test it by applying it to a specific domain. Methods: To that end, we detail a pipeline, which utilizes machine learning and natural language processing for unsupervised theme extraction, and a novel method for summarization of thematic trends, and network mapping for visualization of thematic relations. We then apply this pipeline to a collection of anesthesiology abstracts. Results: We demonstrate how this pipeline enables discovery of major themes and temporal trends in anesthesiology research and facilitates document classification and corpus exploration. Discussion: The relation of prevalent topics and extracted trends to recent events in both anesthesiology, and healthcare in general, demonstrates the pipeline's utility. Furthermore, the agreement between the unsupervised thematic grouping and human-assigned classification validates the pipeline's accuracy and demonstrates another potential use. Conclusion: The described pipeline enables summarization and exploration of large document repositories, facilitates classification, aids in trend identification. A more robust and user-friendly interface will facilitate the expansion of this methodology to other domains. This will be the focus of future work for our group.
Data from: SNP discovery in non-model organisms: strand-bias and base-substitution errors reduce conversion rates
Single nucleotide polymorphisms (SNPs) have become the marker of choice for genetic studies in organisms of conservation, commercial or biological interest. Most SNP discovery projects in nonmodel organisms apply a strategy for identifying putative SNPs based on filtering rules that account for random sequencing errors. Here, we analyse data used to develop 4723 novel SNPs for the commercially important deep-sea fish, orange roughy (Hoplostethus atlanticus), to assess the impact of not accounting for systematic sequencing errors when filtering identified polymorphisms when discovering SNPs. We used SAMtools to identify polymorphisms in a velvet assembly of genomic DNA sequence data from seven individuals. The resulting set of polymorphisms were filtered to minimize 'bycatch'—polymorphisms caused by sequencing or assembly error. An Illumina Infinium SNP chip was used to genotype a final set of 7714 polymorphisms across 1734 individuals. Five predictors were examined for their effect on the probability of obtaining an assayable SNP: depth of coverage, number of reads that support a variant, polymorphism type (e.g. A/C), strand-bias and Illumina SNP probe design score. Our results indicate that filtering out systematic sequencing errors could substantially improve the efficiency of SNP discovery. We show that BLASTX can be used as an efficient tool to identify single-copy genomic regions in the absence of a reference genome. The results have implications for research aiming to identify assayable SNPs and build SNP genotyping assays for nonmodel organisms.
Data from: Repurposed transcriptomic data facilitate discovery of innate immunity Toll-Like Receptor (TLR) genes across Lophotrochozoa
The growing volume of genomic data from across life represents opportunities for deriving valuable biological information from data that were initially collected for another purpose. Here, we use transcriptomes collected for phylogenomic studies to search for toll-like receptor (TLR) genes in poorly sampled lophotrochozoan clades (Annelida, Mollusca, Brachiopoda, Phoronida, and Entoprocta) and one ecdysozoan clade (Priapulida). TLR genes are involved in innate immunity across animals by recognizing potential microbial infection. They have an extracellular leucine-rich repeat (LRR) domain connected to a transmembrane domain and an intracellular toll/interleukin-1 receptor (TIR) domain. Consequently, these genes are important in initiating a signaling pathway to trigger defense. We found at least one TLR ortholog in all but two taxa examined, suggesting that a broad array of lophotrochozoans may have innate immune systems similar to those observed in vertebrates and arthropods. Comparison to the SMART database confirmed the presence of both the LRR and the TIR protein motifs characteristic of TLR genes. Because we looked at only one transcriptome per species, discovery of TLR genes was limited for most taxa. However, several TRL-like genes that vary in the number and placement of LRR domains were found in phoronids. Additionally, several contigs contained LRR domains but lacked TIR domains, suggesting they were not TLRs. Many of these LRR-containing contigs had other domains (e.g., immunoglobin) and are likely involved in innate immunity.
Data from: Development of an Arabis alpina genomic contig sequence dataset and application to single nucleotide polymorphisms discovery
The alpine plant Arabis alpina is an emerging model in the ecological genomic field which is well-suited to identifying the genes involved in local adaptation in contrasted environmental conditions, a subject which remains poorly understood at molecular level. This paper presents the assembly of a pool of A. alpina genomic fragments using Next Generation Sequencing technologies. These contigs cover 172 Mb of the A. alpina genome (i.e. 50% of the genome) and were shown to contain sequences giving positive hits against 96% of the 458 CEGMA core genes (Core Eukaryotic Genes Mapping Approach), a set of highly conserved eukaryotic genes. Regions presenting high nucleic sequence identity with 77% of the close relative Arabidopsis thaliana's genes were found, with an unbiased distribution across the different functional categories of A. thaliana genes. This new resource was tested using a resequencing assay to identify polymorphic sites. Sixteen samples were successfully analyzed and 127,041 Single Nucleotide Polymorphisms identified. This contig dataset will contribute to improving understanding of the ecology of Arabis alpina, thus constituting an important resource for future ecological genomic studies.
Data from: Discovery of metabolic biomarkers for Duchenne Muscular Dystrophy within a natural history study
Serum metabolite profiling in Duchenne muscular dystrophy (DMD) may enable discovery of valuable molecular markers for disease progression and treatment response. Serum samples from 51 DMD patients from a natural history study and 22 age-matched healthy volunteers were profiled using liquid chromatography coupled to mass spectrometry (LC-MS) for discovery of novel circulating serum metabolites associated with DMD. Fourteen metabolites were found significantly altered (1% false discovery rate) in their levels between DMD patients and healthy controls while adjusting for age and study site and allowing for an interaction between disease status and age. Increased metabolites included arginine, creatine and unknown compounds at m/z of 357 and 312 while decreased metabolites included creatinine, androgen derivatives and other unknown yet to be identified compounds. Furthermore, the creatine to creatinine ratio is significantly associated with disease progression in DMD patients. This ratio sharply increased with age in DMD patients while it decreased with age in healthy controls. Overall, this study yielded promising metabolic signatures that could prove useful to monitor DMD disease progression and response to therapies in the future.
Data from: Discovery and exploitation of a natural ecological trap for a mosquito disease vector
Ecological traps occur due to a mismatch between a habitat's attractiveness and quality, wherein organisms show preference for low-quality habitats over other available high-quality habitats. Our previous research identified leaf litter from common blackberry (Rubus allegheniensis) as a natural ecological trap for an important vector for West Nile virus (Culex pipiens), attracting mosquitoes to oviposit in habitats deleterious to the survival of their larvae. Here we demonstrate that manipulation of leaf litter in stormwater catch basins, an important source of disease vector mosquitoes in urban environments, can increase Cx. pipiens oviposition but reduce survival. In a series of experiments designed to elucidate the mechanisms that explain the attractive and lethal properties of this native plant, behavioral bioassays suggest that oviposition site selection by Cx. pipiens is mediated primarily by chemical cues as leaves decompose. However, we also show that juvenile mosquito survival mainly is related to the suitability of the bacterial community in the aquatic habitat for mosquito nutritional needs, which does not appear to create a cue that influences oviposition choice. This mismatch between oviposition cues and drivers of larval habitat quality may account for the ecological trap phenomenon detected in this study. Our findings provide new insights into potential mechanistic pathways by which ecological traps may occur in nature and proof-of-concept for a new 'attract-and-kill' tool for mosquito control.
Data for "The increase in prevalence of natural products through the drug discovery process"
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Supplementary material 2 from: Xiudan W, Luan L, Yang Z (2024) Discovery of a new species of Synergus (Hymenoptera, Cynipidae, Synergini) based on morphology and molecular data. ZooKeys 1193: 81-94. https://doi.org/10.3897/zookeys.1193.105756
appendix S2
Supplementary material 1 from: Xiudan W, Luan L, Yang Z (2024) Discovery of a new species of Synergus (Hymenoptera, Cynipidae, Synergini) based on morphology and molecular data. ZooKeys 1193: 81-94. https://doi.org/10.3897/zookeys.1193.105756
appendix S1
Figure 1 from: Xiudan W, Luan L, Yang Z (2024) Discovery of a new species of Synergus (Hymenoptera, Cynipidae, Synergini) based on morphology and molecular data. ZooKeys 1193: 81-94. https://doi.org/10.3897/zookeys.1193.105756
Figure 1 Maximum-likelihood tree derived from COI sequences of 45 species of Synergus from the EP, with 1000 bootstrap replicates. Numbers on nodes are SH-aLRT and bootstrap values.
Figures 2-9 from: Xiudan W, Luan L, Yang Z (2024) Discovery of a new species of Synergus (Hymenoptera, Cynipidae, Synergini) based on morphology and molecular data. ZooKeys 1193: 81-94. https://doi.org/10.3897/zookeys.1193.105756
Figures 2-9 Synergus dilatatus sp. nov. 2 general habitus (♀) 3 general habitus (♂) 4 antenna (♀) 5 antenna (♂) 6 head in anterior view (♀) 7 head in anterior view (♂) 8 head in dorsal view (♀) 9 head in lateral view (♀).
Figures 10-17 from: Xiudan W, Luan L, Yang Z (2024) Discovery of a new species of Synergus (Hymenoptera, Cynipidae, Synergini) based on morphology and molecular data. ZooKeys 1193: 81-94. https://doi.org/10.3897/zookeys.1193.105756
Figures 10-17 Synergus dilatatus sp. nov. 10 head in posterior view (♀) 11 mesosoma in lateral view (♀) 12 mesosoma in dorsal view (♀) 13 propodeum in dorsal view (♀) 14 metasoma in lateral view (♀) 15 metasoma in lateral view (♂) 16 fore wing (♀) 17 fore wing (♂).
(DATA) Integrated Computational Biophysics Approach for Drug Discovery against Nipah Virus
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Genomic reference data for calculating conditional & conjuncational false discovery rates with cfdr.pleio
<p><strong>Background</strong></p> <p>This data set provides genomic reference information extracted from the 1000 Genomes Project for calculating conditional and conjunctional false discovery rates for genetic variants that are pleiotropic for pairs of phenotypes.</p> <ol> <li>genref.zip is preprocessed information that can be directly used with the R package cfdr.pleio, available from github<br> </li> <li>genref_rawdata.zip contains raw data downloaded from the 1000 Genome projects. You only need to download this if you want to re-create or modify the preprocessed reference data from above. The original code for creating the preprocessed data is available from github.</li> </ol> <p><strong>Usage </strong></p> <p>See the instructions at the two named github repositories for details.</p> <p><strong>Credit</strong></p> <p>The code for generating the preprocessed reference data as well as some auxiliary information were forked from the MATLAB package <a href="https://github.com/precimed/pleiofdr">pleiofdr</a></p> <p>The original concept of the conditional and conjunctional FDR were described in <a href="https://doi.org/10.1371/journal.pgen.1003455">Andreassen et al. (2013)</a>. For a recent overview of methods and applications, see <a href="https://doi.org/10.1007/s00439-019-02060-2">Smeland et al. (2019).</a></p> <p> </p>
Data from: "RAD Sequencing for SNP Discovery in Two Populations of Bighorn Sheep (Ovis canadensis)" in Genomic Resources Notes accepted 1 April 2013 - 31 May 2013
In this work we present the development of a large set of single nucleotide polymorphisms (SNPs) discovered in two populations of bighorn sheep (Ovis canadensis). To do so we used restriction-site associated DNA (RAD) sequencing of four individuals from each population. Through alignment of reads to the domestic sheep (Ovis aries) genome we discovered >83,000 SNPs, of which >38,000 are suitable for assays such as an Illumina SNP chip. These loci will allow for fine-mapping of loci associated with horn size, and examination of the consequences of the genetic rescue including mapping genes underling differences in life-history characteristics.
ChEMBL Data for 'Achieving Well-Informed Decision-Making in Drug Discovery: A Comprehensive Calibration Study using Neural Network-Based Structure-Activity Models'
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data for deep learning large-scale drug discovery and repurposing
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Data from: Fusion transcript discovery in formalin-fixed paraffin-embedded human breast cancer tissues reveals a link to tumor progression
The identification of gene fusions promises to play an important role in personalized cancer treatment decisions. Many rare gene fusion events have been identified in fresh frozen solid tumors from common cancers employing next-generation sequencing technology. However the ability to detect transcripts from gene fusions in RNA isolated from formalin-fixed paraffin-embedded (FFPE) tumor tissues, which exist in very large sample repositories for which disease outcome is known, is still limited due to the low complexity of FFPE libraries and the lack of appropriate bioinformatics methods. We sought to develop a bioinformatics method, named gFuse, to detect fusion transcripts in FFPE tumor tissues. An integrated, cohort based strategy has been used in gFuse to examine single-end 50 base pair (bp) reads generated from FFPE RNA-Sequencing (RNA-Seq) datasets employing two breast cancer cohorts of 136 and 76 patients. In total, 118 fusion events were detected transcriptome-wide at base-pair resolution across the 212 samples. We selected 77 candidate fusions based on their biological relevance to cancer and supported 61% of these using TaqMan assays. Direct sequencing of 19 of the fusion sequences identified by TaqMan confirmed them. Three unique fused gene pairs were recurrent across the 212 patients with 6, 3, 2 individuals harboring these fusions respectively. We show here that a high frequency of fusion transcripts detected at the whole transcriptome level correlates with poor outcome (P<0.0005) in human breast cancer patients. This study demonstrates the ability to detect fusion transcripts as biomarkers from archival FFPE tissues, and the potential prognostic value of the fusion transcripts detected.
Data for thesis: Online Discovery and Model-to-Model Comparison of DCR Models from Event Streams
<p>This is the collection of data referenced in the Thesis</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.