cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15156/bio/sh0180966.10fu
title: SH0180966.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0180967.10fu
title: SH0180967.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0180968.10fu
title: SH0180968.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0180969.10fu
title: SH0180969.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0180970.10fu
title: SH0180970.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0180971.10fu
title: SH0180971.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0180972.10fu
title: SH0180972.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15156/bio/sh0180973.10fu
title: SH0180973.10FU

description: UNITE provides a unified way for delimiting, identifying, communicating, and working with DNA-based Species Hypotheses (SH). All fungal ITS sequences in the international nucleotide sequence databases are clustered to approximately the species level by applying a set of dynamic distance values (<0.5 - 3.0%). All species hypotheses are given a unique, stable name in the form of a DOI, and their taxonomic and ecological annotations are verified through distributed, web-based third-party annotation efforts. SHs are connected to a taxon name and its classification as far as possible (phylum, class, order, etc.) by taking into account identifications for all sequences in the SH. An automatically or manually designated sequence is chosen to represent each such SH. These sequences are released (https://unite.ut.ee/repository.php) for use by the scientific community in, for example, local sequence similarity searches and next-generation sequencing analysis pipelines. The system and the data are updated automatically as the number of public fungal ITS sequences grows.
DOI: 10.15468/dl.dgdxdp
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Troglodytes troglodytes (Linnaeus, 1758)",
 "Year is 82",
 "Country is Netherlands"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008906-241107131044228/datasets/export for details.
DOI: 10.15468/dl.eef2tw
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Dendrocopos major (Linnaeus, 1758)",
 "Year is 82",
 "Country is Netherlands"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008907-241107131044228/datasets/export for details.
DOI: 10.15468/dl.jspvaf
title: Occurrence Download

description: A dataset containing 5242 species occurrences available in GBIF matching the query:
{
 "and" : [
 "BasisOfRecord is Human Observation",
 "TaxonKey is Potamidae"
 ]
}

 The dataset includes 5242 records from 21 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008908-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.8yezkf
title: Occurrence Download

description: A dataset containing 164458 species occurrences available in GBIF matching the query:
{
 "and" : [
 "OccurrenceStatus is Present",
 "TaxonKey is Helminthotheca echioides (L) Holub"
 ]
}

 The dataset includes 164458 records from 1822 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0008859-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.xjxh3a
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Persea obscura Lorea-Hern.)",
 "BasisOfRecord is one of (Human Observation, Observation, Living Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Continent is North America"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016099-250127130748423/datasets/export for details.
DOI: 10.5281/zenodo.14811320
title: test

description: 描述
DOI: 10.5281/zenodo.14811321
title: test

description: 描述
DOI: 10.15468/dl.9y8gej
title: Occurrence Download

description: A dataset containing 294 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Opuntia depressa Rose"
 ]
}

 The dataset includes 294 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016100-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.876drt
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Persea pallescens (Mez) Lorea-Hern.)",
 "BasisOfRecord is one of (Human Observation, Observation, Living Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Continent is North America"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016102-250127130748423/datasets/export for details.
DOI: 10.15468/dl.4jeqpy
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Persea podadenia S.F.Blake)",
 "BasisOfRecord is one of (Human Observation, Observation, Living Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Continent is North America"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016105-250127130748423/datasets/export for details.
DOI: 10.15468/dl.n55exh
title: Occurrence Download

description: A dataset containing 74 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Year is greater than or equal to 1981",
 "Year is less than or equal to 2010",
 "HasCoordinate is true",
 "Country is United Kingdom of Great Britain and Northern Ireland",
 "VerbatimScientificName is Polytrichastrum sexangulare",
 "BasisOfRecord is Human Observation",
 "CoordinateUncertaintyInMeters is less than or equal to 1000"
 ]
}

 The dataset includes 74 records from 4 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016106-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.yuh6ka
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Persea purpusii L.E.Kopp)",
 "BasisOfRecord is one of (Human Observation, Observation, Living Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Continent is North America"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016108-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jgxnkh
title: Occurrence Download

description: A dataset containing 826 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Ecuador",
 "TaxonKey is Harpia harpyja (Linnaeus, 1758)"
 ]
}

 The dataset includes 826 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016109-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.he7m6u
title: Occurrence Download

description: A dataset containing 0 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Persea rufescens Lundell)",
 "BasisOfRecord is one of (Human Observation, Observation, Living Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Continent is North America"
 ]
}

 The dataset includes 0 records from 0 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016110-250127130748423/datasets/export for details.
DOI: 10.15468/dl.6utj86
title: Occurrence Download

description: A dataset containing 259 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Persea schiedeana Nees)",
 "BasisOfRecord is one of (Human Observation, Observation, Living Specimen)",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "Continent is North America"
 ]
}

 The dataset includes 259 records from 6 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0016114-250127130748423/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.14291774
title: FractiScope Live Demo Deep Dives

description: Welcome to the FractiScope Live Demonstration Deep Dives Repository

Thank you for visiting this Zenodo repository, a dedicated space for sharing the groundbreaking insights and methodologies behind FractiScope, the world’s first fractal intelligence scope. Here, you’ll find detailed documentation, live demonstration deep dives, and advanced analyses showcasing the power of fractal intelligence in uncovering the hidden patterns and recursive dynamics within complex systems.

Why FractiScope?

FractiScope represents a paradigm shift in the way we approach complexity. Traditional linear methods often struggle to capture the multi-scale, self-similar architectures inherent in biological, physical, and computational systems. FractiScope, powered by fractal intelligence, bridges this gap by:



Uncovering Recursive Feedback Loops: Revealing self-sustaining dynamics that drive adaptability and efficiency.

Identifying Fractal Hubs: Detecting hierarchical nodes that orchestrate system-wide interactions.

Mapping Fractal Symmetries: Highlighting repeating structures that enhance resilience and scalability.


What You’ll Discover

In this repository, we illustrate the transformative capabilities of FractiScope through real-world applications, including:



Cancer Research: Delving into the fractalized behaviors of extrachromosomal DNA (ecDNA), revealing insights into tumor evolution, therapeutic resistance, and precision oncology strategies.

Particle Physics: Analyzing the FCC-ee lattice design with nested magnets to optimize beam stability, energy efficiency, and system scalability in next-generation colliders.

Cross-Disciplinary Innovations: Exploring how fractal intelligence principles can be applied across fields like artificial intelligence, neural networks, and systems biology.


The Power of Fractal Intelligence

FractiScope is more than a tool; it’s a transformative framework that redefines how we analyze and understand the complex systems shaping our world. Whether you’re a researcher, an engineer, or an innovator, FractiScope empowers you to:



Visualize the invisible: Detect hidden patterns and relationships within your data.

Bridge disciplines: Apply universal fractal principles to solve problems across fields.

Drive breakthroughs: Unlock new possibilities in your work by embracing the power of fractalized thinking.


Join the Movement

As you explore the content in this repository, we invite you to become part of the growing community pushing the boundaries of fractal intelligence. Download the data, study the analyses, and imagine how fractal intelligence can transform your field. Together, we can uncover the intricate dynamics of the systems that drive our universe—and beyond.

Welcome to the future of exploration. Welcome to FractiScope.
DOI: 10.5281/zenodo.14291859
title: FractiScope Live Demo Deep Dives

description: Welcome to the FractiScope Live Demonstration Deep Dives Repository

Thank you for visiting this Zenodo repository, a dedicated space for sharing the groundbreaking insights and methodologies behind FractiScope, the world’s first fractal intelligence scope. Here, you’ll find detailed documentation, live demonstration deep dives, and advanced analyses showcasing the power of fractal intelligence in uncovering the hidden patterns and recursive dynamics within complex systems.

Why FractiScope?

FractiScope represents a paradigm shift in the way we approach complexity. Traditional linear methods often struggle to capture the multi-scale, self-similar architectures inherent in biological, physical, and computational systems. FractiScope, powered by fractal intelligence, bridges this gap by:



Uncovering Recursive Feedback Loops: Revealing self-sustaining dynamics that drive adaptability and efficiency.

Identifying Fractal Hubs: Detecting hierarchical nodes that orchestrate system-wide interactions.

Mapping Fractal Symmetries: Highlighting repeating structures that enhance resilience and scalability.


What You’ll Discover

In this repository, we illustrate the transformative capabilities of FractiScope through real-world applications, including:



Cancer Research: Delving into the fractalized behaviors of extrachromosomal DNA (ecDNA), revealing insights into tumor evolution, therapeutic resistance, and precision oncology strategies.

Particle Physics: Analyzing the FCC-ee lattice design with nested magnets to optimize beam stability, energy efficiency, and system scalability in next-generation colliders.

Cross-Disciplinary Innovations: Exploring how fractal intelligence principles can be applied across fields like artificial intelligence, neural networks, and systems biology.


The Power of Fractal Intelligence

FractiScope is more than a tool; it’s a transformative framework that redefines how we analyze and understand the complex systems shaping our world. Whether you’re a researcher, an engineer, or an innovator, FractiScope empowers you to:



Visualize the invisible: Detect hidden patterns and relationships within your data.

Bridge disciplines: Apply universal fractal principles to solve problems across fields.

Drive breakthroughs: Unlock new possibilities in your work by embracing the power of fractalized thinking.


Join the Movement

As you explore the content in this repository, we invite you to become part of the growing community pushing the boundaries of fractal intelligence. Download the data, study the analyses, and imagine how fractal intelligence can transform your field. Together, we can uncover the intricate dynamics of the systems that drive our universe—and beyond.

Welcome to the future of exploration. Welcome to FractiScope.