Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
250
datasets available to search
ShareScore release 0.9.0
Dataset results
250 results for “bioinformatics”
M. tuberculosis bioinformatics training data
<p>Training data based on for tutorial on M. tuberculosis variant calling and annotation based on inferred ancestral reference genome of <em>M. tuberculosis</em> combined with NCBI NC_000962.3 annotation in Genbank format and reads from "Use of whole-genome sequencing to distinguish relapse from reinfection in a completed tuberculosis clinical trial".</p>
Supplementary material for "Compounds with antiviral, anti-inflammatory and anticancer activity identified in wine via high resolution mass spectrometry and bioinformatics analyses"
<p>Wine contains a variety of molecules with potential beneficial effects on human health. Our aim was to examine the wine components with high-resolution mass spectrometry including high-resolution tandem mass spectrometry in two wine types made from grapes with or without the fungus <em>Botrytis cinerea</em>, or “noble rot.” For LC-MS/MS analysis, 12 wine samples (7 without and 5 with noble rotting) from 4 different wineries were used and wine components were identified and quantified. Results: 288 molecules were identified in the wines and the amount of 169 molecules was statistically significantly different between the two wine types. A database search was carried out to find the molecules, which were examined in functional studies so far, with high emphasis on molecules with antiviral, anti-inflammatory and anticancer activities. Conclusions: A comprehensive functional dataset related to identified wine components is also provided highlighting the importance of components with potential health benefits.</p>
Data from: Identification of genetic defects in 33 probands with Stargardt disease by WES-based bioinformatics gene panel analysis
Stargardt disease (STGD) is the most common hereditary macular degeneration in juveniles, with loss of central vision occurring in the first or second decade of life. The aim of this study is to identify the genetic defects in 33 probands with Stargardt disease. Clinical data and genomic DNA were collected from 33 probands from unrelated families with STGD. Variants in coding genes were initially screened by whole exome sequencing. Candidate variants were selected from all known genes associated with hereditary retinal dystrophy and then confirmed by Sanger sequencing. Putative pathogenic variants were further validated in available family members and controls. Potential pathogenic mutations were identified in 19 of the 33 probands (57.6%). These mutations were all present in ABCA4, but not in the other four STGD-associated genes or in genes responsible for other retinal dystrophies. Of the 19 probands, ABCA4 mutations were homozygous in one proband and compound heterozygous in 18 probands, involving 28 variants (13 novel and 15 known). Analysis of normal controls and available family members in 12 of the 19 families further support the pathogenicity of these variants. Clinical manifestation of all probands met the diagnostic criteria of STGD. This study provides an overview of a genetic basis for STGD in Chinese patients. Mutations in ABCA4 are the most common cause of STGD in this cohort. Genetic defects in approximately 42.4% of STGD patients await identification in future studies.
Data from: Distribution and bioinformatic analysis of the cerato-platanin protein family in Dikarya
The cerato-platanin family is a group of small cysteine-rich fungal proteins new to science. They usually are abundantly secreted extracellularly and are involved in fungus-host interactions. With the advance of available fungal genome sequences, we performed a genomewide study of the distribution of this family in fungi and analyzed the common characteristics of the protein sequences. A total of 55 fungal genomes, including 27 from Ascomycota and 28 from Basidiomycota, were used. A total of 130 cerato-platanin homolog protein sequences were obtained and analyzed. Our results showed that cerato-platanin homologs existed in both Ascomycota and Basidiomycota but were lost in early branches of jelly fungi as well as in some groups with yeast or yeast-like forms in their life cycle. Homolog numbers varied considerably between Ascomycota and Basidiomycota. Phylogenetic analysis suggested that the ancestor of the Dikarya possessed multiple copies of cerato-platanins, which sorted differently in Ascomycota and Basidiomycota, and that this gene family might have expanded in the Basidiomycota. Almost all homologs contained signal peptide sequences, and the length of mature proteins were mainly 105-134 amino acids. Four cysteines involved in forming two disulfide bridges and signature sequences (CSD or CSN) were highly conserved in most homologs. These results indicated a higher diversity of the cerato-platanin family in Basidiomycota than Ascomycota.
raw data - Bioinformatics analysis reveals the m5C-associated gene DLGAP5 as a prognostic and immunological marker in bladder cancer
Open the record for dataset details and reuse information.
BioToFlow: a corpus annotated with bioinformatics workflows information
<div> <div><em>BioToFlow</em> is a corpus describing bioinformatics workflows in English publications. These annotations are available in the BRAT Rapid Annotation Tool (BRAT) standoff format (https://brat.nlplab.org/standoff.html).</div> <br> <div>This corpus is composed of 52 articles (26 articles related to Nextflow workflows and 26 on Snakemake workflows, randomly selected from PubMed) with a total of 78 419 tokens 27 786 annotated tokens.</div> <div> </div> <h2>Repository organisation</h2> <div> <div> <div> <div>The articles are separated into two directories:</div> <div> <ul> <li>one containing all the articles for the training phases (39) and</li> <li>the other with 13 articles for test.</li> </ul> </div> <br> <h2>Papers</h2> <br>Please cite <em>BioToFlow</em> in any research that uses or extends it :<br> <div> </div> <div> <ul> <li>Sebe, C., Cohen-Boulakia, S., Ferret, O., Névéol, A.: Extracting information in a low-resource setting: Case study on bioinformatics workflows (2024), https://arxiv.org/abs/2411.19295</li> </ul> </div> <div>In this article accepted to IDA 2025 (in English), we present *BioToFlow* and experiments with few shot named entity recognition (NER) using an autoregressive language model, we also use a pre-existing corpus and test integration of workflow knowledge in NER models.</div> <br> <div> </div> <div> <ul> <li>Clémence Sebe, Sarah Cohen-Boulakia, Olivier Ferret, Aurélie Névéol. Extraction d’entités nommées décrivant des chaînes de traitement bioinformatiques dans des articles scientifiques en anglais. 35emes Journées d’Études sur la Parole (JEP 2024) 31eme Conférence sur le Traitement Automatique des Langues Naturelles (TALN 2024) 26eme Rencontre des Étudiants Chercheurs en Informatique pour le Traitement Automatique des Langues (RECITAL 2024), Jul 2024, Toulouse, France. pp.422-434. hal-04623033.</li> </ul> </div> <div>In this article (in French), we present the second version of *BioToFlow*. The new articles are annotated with entities and attributes. We conduct preliminary experiments with NER with a specific focus on the memorization vs. generalization abilities of statistical and rule-based methods.</div> <br><br> <div> <ul> <li>Sebe C., Névéol A., Cohen-Boulakia S. & Gaignard A. (2023). Extraction d’informations sur les workflows scientifiques à partir de la littérature. volume Extraction et Gestion des Connaissances, RNTI-E-39, p. 313.</li> </ul> </div> <div>In this article (in French), we present the first version of the corpus with 24 articles annotated with entities and relations. We show the feasibility of the task of NER.</div> </div> <div> </div> <h2><br>Contact</h2> <div> <div> <ul> <li>Clémence Sebe, clemence.sebe@universite-paris-saclay.fr</li> </ul> </div> <br> <h2>Funding</h2> This work received support from the National Research Agency under the France 2030 program, with reference to ANR-22-PESN-0007.</div> </div> </div> </div>
Semi-artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detection
<p>In the last decade, High-Throughput Sequencing (HTS) has revolutionized biology and medicine. This technology allows the sequencing of huge amount of DNA and RNA fragments at a very low price. In medicine, HTS tests for disease diagnostics are already brought into routine practice. However, the adoption in plant health diagnostics is still limited. One of the main bottlenecks is the lack of expertise and consensus on the standardization of the data analysis. The Plant Health Bioinformatic Network (PHBN) is an Euphresco project aiming to build a community network of bioinformaticians/computational biologists working in plant health. One of the main goals of the project is to develop reference datasets that can be used for validation of bioinformatics pipelines and for standardization purposes.</p> <p>Semi-artificial datasets have been created for this purpose (Datasets 1 to 10). They are composed of a "real" HTS dataset spiked with artificial viral reads. It will allow researchers to adjust their pipeline/parameters as good as possible to approximate the actual viral composition of the semi-artificial datasets. Each semi-artificial dataset allows to test one or several limitations that could prevent virus detection or a correct virus identification from HTS data (<i>i.e.</i> low viral concentration, new viral species, non-complete genome).</p> <p>Eight artificial datasets only composed of viral reads (no background data) have also been created (Datasets 11 to 18). Each dataset consists of a mix of several isolates from the same viral species showing different frequencies. The viral species were selected to be as divergent as possible. These datasets can be used to test haplotype reconstruction software, the goal being to reconstruct all the isolates present in a dataset.</p> <p><span>A GitLab repository (<a href="https://gitlab.com/ilvo/VIROMOCKchallenge">https://gitlab.com/ilvo/VIROMOCKchallenge</a>) is available and provides a complete description of the composition of each dataset, the methods used to create them and their goals.</span></p>
Introduction to data analysis in bioinformatics
<p>A data set for the CENTURI session "Introduction to data analysis in bioinformatics"</p>
Data to reproduce bioinformatics analysis of "Morphoregulatory ADD3 underlies glioblastoma growth and formation of tumor-tumor connections"
Open the record for dataset details and reuse information.
CPXV reads with SNPs for bioinformatics course
<p>Four samples with CPXV reads for bioinformatics course (mapping and variant calling).</p>
Bioinformatics workflow for the detection of eQTL in the cattle genome using Nextflow DSL2
<p>The <em>in silico</em> detection of expression quantitative trait loci (eQTL) demands high throughput processing from hundreds of samples, which is often a challenge to handle and run such large datasets. In order to focus on the core analysis, it is convenient to have simple coding and hassle-free installation of different software tools required for the bioinformatics workflow. In this context, the newly available technologies like workflow managers and software containers enabled to develop workflows with less complexity. In this study, we developed an eQTL bioinformatics pipeline with the workflow manager Nextflow and docker container software, for coding and installing the required software tools. This workflow can be portable to a different computer environment, and the results are reproducible. We tested the functionality of our workflow with a sample dataset and the runtime estimates from this demo run will provide important information in planning future analyses with much larger datasets.</p>
Data from: Identification of genetic defects in 33 probands with Stargardt disease by WES-based bioinformatics gene panel analysis
Open the record for dataset details and reuse information.
Semi-artificial datasets as a resource for validation of bioinformatics pipelines for plant virus detection
Open the record for dataset details and reuse information.
metabarcoding data for: Benchmark of bioinformatics tools for fast and accurate species identification from environmental DNA metabarcoding
Open the record for dataset details and reuse information.
Data from: Distribution and bioinformatic analysis of the cerato-platanin protein family in Dikarya
Open the record for dataset details and reuse information.
Data from: SSR_pipeline: a bioinformatic infrastructure for identifying microsatellites from paired-end Illumina high-throughput DNA sequencing data
Open the record for dataset details and reuse information.
Data from: The new bioinformatics: integrating ecological data from the gene to the biosphere
Open the record for dataset details and reuse information.
Data from: Novel traits, flower symmetry, and transcriptional autoregulation: new hypotheses from bioinformatic and experimental data
Open the record for dataset details and reuse information.
LSU Bioinformatics Workshop course materials
Open the record for dataset details and reuse information.
Transcriptome sequencing and bioinformatics analysis of gastrocnemius muscle in type 2 diabetes mellitus rats
GEO Series GSE268372. Rattus norvegicus. 6 samples. Type: Expression profiling by high throughput sequencing.
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.