cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.5281/zenodo.16935985
title: Dataset: Activity-Driven Swelling and Dynamics in Segmentally Active Rouse Chains

description: Overview
--------
This dataset contains simulation trajectories for a segmentally active Rouse polymer.
Activity is localized within a single segment of the chain; across subfolders we vary
the location of the active segment by choosing different pairs (f1, f2).

Directory layout
----------------
segmentally_active_polymer/
├─ f1_0.0_f2_0.5/      (2000 CSV trajectories)
│    rgre055_00001.csv, rgre055_00002.csv, ..., rgre055_02000.csv
├─ f1_0.25_f2_0.75/    (2000 CSV trajectories)
│    rgre275_00001.csv, rgre275_00002.csv, ..., rgre275_02000.csv
└─ f1_0.0_f2_1.0/      (2000 CSV trajectories)
     rgre0n5_00001.csv, rgre0n5_00002.csv, ..., rgre0n5_02000.csv

CSV format (columns)
--------------------
Each CSV has four comma-separated columns with a header row:

  time  :  simulation time
  rg  :  squared radius of gyration, R_g^2
  re2  :  squared end-to-end distance, R_e^2
  msd_mid  : squared separation between two points, R_{s1 s2}^2

Note
----
In all files, the observed pair is (s1, s2) = (0.4L, 0.6L).
DOI: 10.15468/dl.8fvuau
title: Occurrence Download

description: A dataset containing 496 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Inula linariifolia"
 ]
}

 The dataset includes 496 records from 48 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039311-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.19653891
title: Raw data (resting-state EEG)

description: Beyond advancing theoretical understanding, the results have practical implications for athlete development, suggesting that EEG markers may serve as objective indicators of attentional and executive capacities relevant to performance.
DOI: 10.6084/m9.figshare.19653891.v1
title: Raw data (resting-state EEG)

description: Beyond advancing theoretical understanding, the results have practical implications for athlete development, suggesting that EEG markers may serve as objective indicators of attentional and executive capacities relevant to performance.
DOI: 10.15468/dl.s6er3q
title: Occurrence Download

description: A dataset containing 6 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lophonetta specularioides",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 6 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039313-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.d8daa5
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Lophonetta specularioides",
 "Country is Germany",
 "HasCoordinate is true"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039312-250811113504898/datasets/export for details.
DOI: 10.15468/dl.ksmf9z
title: Occurrence Download

description: A dataset containing 526 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Convolvulus stachydifolius"
 ]
}

 The dataset includes 526 records from 34 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039316-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5uvvw9
title: Occurrence Download

description: A dataset containing 1332 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Convolvulus betonicifolius"
 ]
}

 The dataset includes 1332 records from 93 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039314-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dwv4at
title: Occurrence Download

description: A dataset containing 57 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cotula australis",
 "Country is Peru",
 "HasCoordinate is true"
 ]
}

 The dataset includes 57 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039315-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hhsmup
title: Occurrence Download

description: A dataset containing 393 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cotula australis",
 "Country is Portugal",
 "HasCoordinate is true"
 ]
}

 The dataset includes 393 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039318-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.5mntqm
title: Occurrence Download

description: A dataset containing 721 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cotula australis",
 "Country is Spain",
 "HasCoordinate is true"
 ]
}

 The dataset includes 721 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039319-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.vrngz6
title: Occurrence Download

description: A dataset containing 36294 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Convolvulus althaeoides"
 ]
}

 The dataset includes 36294 records from 269 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039317-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.a8aq4f
title: Occurrence Download

description: A dataset containing 20294 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry MULTIPOLYGON(((-72.03659 -13.09453,-72.20845 -13.09438,-72.2083 -13.28858,-72.03644 -13.28858,-72.03659 -13.09453)))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Aves",
 "Year 1901-2025"
 ]
}

 The dataset includes 20294 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039320-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.7pjhnr
title: Occurrence Download

description: A dataset containing 3481 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Inula japonica"
 ]
}

 The dataset includes 3481 records from 129 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039321-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.2hgbd7
title: Occurrence Download

description: A dataset containing 21565 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Inula montana"
 ]
}

 The dataset includes 21565 records from 367 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039322-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.29975167
title: Dataset and R code for a new method of identifying bacterial shapes using machine learning

description: Accurately identifying genes responsible for specific functions is a cornerstone of biological research, but current methods are often limited to single-species analyses. Here, we present a novel method, called Genomic and Phenotype-based machine learning for Gene Identification (GPGI), that leverages large-scale, cross-species genomic and phenotypic data for functional gene discovery. Using bacterial rod-shape determination as a case study, we demonstrate GPGI's ability to rapidly identify key genes. Our approach uses machine learning to predict bacterial shape from protein structural domain profiles, identifying influential domains whose corresponding genes are selected for experimental validation. Focused gene knockouts in <i>Escherichia coli</i> confirmed the critical roles of two genes, <i>pal</i> and <i>mreB</i>, in maintaining rod-shaped morphology. We further validated GPGI's robustness by demonstrating its consistent performance even with reduced datasets. GPGI thus offers a rapid, accurate, and efficient way to identify multiple key genes associated with complex traits across diverse organisms.
DOI: 10.6084/m9.figshare.29975167.v1
title: Dataset and R code for a new method of identifying bacterial shapes using machine learning

description: Accurately identifying genes responsible for specific functions is a cornerstone of biological research, but current methods are often limited to single-species analyses. Here, we present a novel method, called Genomic and Phenotype-based machine learning for Gene Identification (GPGI), that leverages large-scale, cross-species genomic and phenotypic data for functional gene discovery. Using bacterial rod-shape determination as a case study, we demonstrate GPGI's ability to rapidly identify key genes. Our approach uses machine learning to predict bacterial shape from protein structural domain profiles, identifying influential domains whose corresponding genes are selected for experimental validation. Focused gene knockouts in <i>Escherichia coli</i> confirmed the critical roles of two genes, <i>pal</i> and <i>mreB</i>, in maintaining rod-shaped morphology. We further validated GPGI's robustness by demonstrating its consistent performance even with reduced datasets. GPGI thus offers a rapid, accurate, and efficient way to identify multiple key genes associated with complex traits across diverse organisms.
DOI: 10.15468/dl.gdargw
title: Occurrence Download

description: A dataset containing 14 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Melanitta perspicillata",
 "Country is Germany",
 "HasCoordinate is true"
 ]
}

 The dataset includes 14 records from 3 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039323-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.hgsap6
title: Occurrence Download

description: A dataset containing 93 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cotula australis",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "HasCoordinate is true"
 ]
}

 The dataset includes 93 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039326-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w2ubpd
title: Occurrence Download

description: A dataset containing 2060 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Coprosma pumila"
 ]
}

 The dataset includes 2060 records from 35 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039325-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j6vx7u
title: Occurrence Download

description: A dataset containing 9328 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Coprosma repens"
 ]
}

 The dataset includes 9328 records from 77 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039324-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.x48z9a
title: Occurrence Download

description: A dataset containing 4202 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Coprosma cuneata"
 ]
}

 The dataset includes 4202 records from 25 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039327-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.asqwyu
title: Occurrence Download

description: A dataset containing 1935 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Cotula australis",
 "Country is United States of America",
 "HasCoordinate is true"
 ]
}

 The dataset includes 1935 records from 55 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039328-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.sh4ydz
title: Occurrence Download

description: A dataset containing 201 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Inula grandiflora"
 ]
}

 The dataset includes 201 records from 33 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039330-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.74ptj4
title: Occurrence Download

description: A dataset containing 204 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Polysticta stelleri",
 "Country is Germany",
 "HasCoordinate is true"
 ]
}

 The dataset includes 204 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039331-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.265xpk
title: Occurrence Download

description: A dataset containing 719 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Coprosma ernodeoides"
 ]
}

 The dataset includes 719 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039332-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.nu5k6c
title: Occurrence Download

description: A dataset containing 1178 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Corchorus fascicularis"
 ]
}

 The dataset includes 1178 records from 74 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039333-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3ex859
title: Occurrence Download

description: A dataset containing 206599 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Impatiens parviflora"
 ]
}

 The dataset includes 206599 records from 829 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0039192-250811113504898/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xcc636
title: Occurrence Download

description: A dataset containing 3814339 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Mexico",
 "Geometry POLYGON((-99.99096 15.50117,-94.43697 15.50117,-94.43697 18.46502,-99.99096 18.46502,-99.99096 15.50117))"
 ]
}

 The dataset includes 3814339 records from 1453 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012334-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.7910/dvn/2igg4z
title: Replication Data for: Targeting Genomic Alterations and Cancer Signaling with Integrative Multi-Omics, Deep Learning and Network Biology in Medical Oncology

description: Multiple genetic and epigenetic alterations characterize tumor progression and define hallmarks of cancer. It may result in dysregulation of growth factors, regulatory proteins, cell adhesion molecules, and molecules of immune system driven by alterations in the expression profile of tumor suppressor genes and oncogenes that may vary among different cancer types. Importantly, patients with the same cancer type respond differently to available cancer treatments, likely due to tumor-specific DNA, RNA, and proteins, indicating the need for patient-specific treatment options. Precision oncology has evolved as a form of cancer therapy that is focused on genetic and molecular profiling of tumors to identify specific molecular alterations involved in carcinogenesis for tailored individualized cancer treatment. Advances in high-throughput technologies, that include next-generation sequencing, have enabled gene expression profiling, providing detailed molecular characterization of various tumors. Moreover, the application of multiomic technologies, including genomics, proteomics, metabolomics, and single-cell multiomics, constitutes a novel approach for the identification and quantification of a comprehensive set of biological molecules to study how they translate into cellular functions and tissue pathologies. Integration and analysis of various multiomic sequencing data are crucial in this regard, as they can reveal critical molecular changes, such as cancer-driving mutations, post-translational modifications, gene fusions, amplifications, and alterations in signaling networks within tumors. Furthermore, the role of computational techniques such as artificial intelligence and deep learning, in analyzing complex data and identifying patterns of disease development for better outcomes is now well established in precision medicine. Additionally, AI-powered multi-omics and network biology have been harnessed to integrate and analyze biological data through networks, which may prove crucial in solving key problems facing precision oncology. This article aims to briefly explain the foundations and frontiers of precision oncology in the context of cutting-edge developments in tools and techniques associated with it, and try to assess its scope and importance in achieving the intended goals over time.
DOI: 10.57967/hf/7542
title: TreeOfLife-10M
DOI: 10.57967/hf/1972
title: TreeOfLife-10M
DOI: 10.15468/dl.g3kaj5
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Scardinius erythrophthalmus",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1835",
 "Year is less than or equal to 1839"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012357-260108223611665/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.57906/jj2j-zw28
title: Wealth and Assets Survey - Great Britain
DOI: 10.5281/zenodo.17926121
title: Genetically Targeted Antifungal Therapeutics: A CRISPR-dCas9--RNAi Hybrid Framework with Dual-Gene Targeting, Evolutionary Escape Modeling, Bayesian Inference, Stochastic Simulations, and In Vitro/In Vivo Validation Protocols

description: This study delineates a state-of-the-art framework for Genetically Targeted Antifungal Therapeutics (GTAT), fusing CRISPR-dCas9 with RNAi for dual-gene silencing of \textit{ERG11} and \textit{FKS1} in \textit{Candida albicans}. The architecture integrates probabilistic evolutionary escape modeling via Poisson processes, Gillespie stochastic simulations incorporating fitness costs and population bottlenecks, and a hierarchical Bayesian framework for parameter inference on mRNA decay kinetics using numerical ODE solutions for enhanced mathematical precision. Synthetic data illustrate the model, yielding posterior means of bioavailability \(\hat{\phi} = 0.61\) (95\% HDI: [0.52, 0.70]) and silencing efficiency \(\hat{\eta} = 1.15~\mathrm{h}^{-1}\) (95\% HDI: [0.92, 1.38]), predicting 98.7\% knockdown at 12 hours (95\% HDI: [97.2\%, 99.4\%]). Limitations of synthetic data are transparently addressed, with detailed protocols for RT-qPCR in clinical isolates, cytotoxicity in HepG2/HEK293 cells, off-target RNA-seq, and extension to in vivo murine candidiasis models. The model further incorporates nuclease kinetics, macrophage clearance via Michaelis-Menten approximations, TLR-mediated immune modulation by PEGylated chitosan-lipid nanoparticles (CLNPs), and quantitative systems pharmacology (QSP) integration for translational PK/PD predictions. Dual-targeting suppresses escape probability from \(2.4 \times 10^{-3}\) to \(5.8 \times 10^{-6}\), with Gillespie simulations affirming resilience under varying population dynamics and selection pressures. Hypotheses are falsifiable, reproducible, and anchored in fungal genomics, systems pharmacology, evolutionary dynamics, and immunology, positioning GTAT as a paradigm-shifting platform for precision antimicrobials amid escalating resistance, informed by recent advances in CRISPR-Cas fungal applications and RNAi delivery.
DOI: 10.5281/zenodo.18260604
title: Genetically Targeted Antifungal Therapeutics: A CRISPR-dCas9--RNAi Hybrid Framework with Dual-Gene Targeting, Evolutionary Escape Modeling, Bayesian Inference, Stochastic Simulations, and In Vitro/In Vivo Validation Protocols

description: This study delineates a state-of-the-art framework for Genetically Targeted Antifungal Therapeutics (GTAT), fusing CRISPR-dCas9 with RNAi for dual-gene silencing of \textit{ERG11} and \textit{FKS1} in \textit{Candida albicans}. The architecture integrates probabilistic evolutionary escape modeling via Poisson processes, Gillespie stochastic simulations incorporating fitness costs and population bottlenecks, and a hierarchical Bayesian framework for parameter inference on mRNA decay kinetics using numerical ODE solutions for enhanced mathematical precision. Synthetic data illustrate the model, yielding posterior means of bioavailability \(\hat{\phi} = 0.61\) (95\% HDI: [0.52, 0.70]) and silencing efficiency \(\hat{\eta} = 1.15~\mathrm{h}^{-1}\) (95\% HDI: [0.92, 1.38]), predicting 98.7\% knockdown at 12 hours (95\% HDI: [97.2\%, 99.4\%]). Limitations of synthetic data are transparently addressed, with detailed protocols for RT-qPCR in clinical isolates, cytotoxicity in HepG2/HEK293 cells, off-target RNA-seq, and extension to in vivo murine candidiasis models. The model further incorporates nuclease kinetics, macrophage clearance via Michaelis-Menten approximations, TLR-mediated immune modulation by PEGylated chitosan-lipid nanoparticles (CLNPs), and quantitative systems pharmacology (QSP) integration for translational PK/PD predictions. Dual-targeting suppresses escape probability from \(2.4 \times 10^{-3}\) to \(5.8 \times 10^{-6}\), with Gillespie simulations affirming resilience under varying population dynamics and selection pressures. Hypotheses are falsifiable, reproducible, and anchored in fungal genomics, systems pharmacology, evolutionary dynamics, and immunology, positioning GTAT as a paradigm-shifting platform for precision antimicrobials amid escalating resistance, informed by recent advances in CRISPR-Cas fungal applications and RNAi delivery.