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Quantifying Genetic Innovation: Mathematical Foundations for the Topological Study of Reticulate Evolution

SIAM Journal on Applied Algebra and Geometry(2020)10.1137/18m118150xSource: DataRank Database

Quantifying Genetic Innovation: Mathematical Foundations for the Topological Study of Reticulate Evolution is a research paper published in SIAM Journal on Applied Algebra and Geometry (2020). On theSindex it has a DataRank of 0. It has been cited 3 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access3 citations

Free full text

Cite:

Linked data & code

Gromov Hyperbolicity, Geodesic Defect, and Apparent Pairs in Vietoris-Rips Filtrations · Schloss Dagstuhl – Leibniz-Zentrum für Informatik

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (6 grants)Impact (FWCI 0.13)OA: greenTopics (41)Linked Datasets (1)DataCite Reuse (1)IDs (PubMed, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (2/2)

Has DOI
Indexed in repositories

Accessible (1/2)

Open Access

Interoperable (2/2)

DataCite relations
Linked datasets

Reusable (0/3)

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Authors (3)

Raúl Rabadán ORCID,Daniel I. S. Rosenbloom ORCID,Michael Lesnick ORCID

Live enrichment

PubMed:21097893 OpenAlex:https://openalex.org/W2795593409

National Institutes of Health

Grant: U54CA193313

National Institutes of Health

Grant: T32MH065214

National Institutes of Health

Grant: R01GM117591

National Institutes of Health

Grant: 5R01GM117591-04

Uncovering Evolutionary History using the Topology of Genomic Data with Applications to HIV

National Institutes of Health

Grant: 1U54CA193313-01

Project 1: Modeling tumor evolution in mouse and organoid models

National Institutes of Health

Grant: 4T32MH065214-14

NRSA Training Grant in Quantitative Neuroscience

FWCI

0.13

Citation Percentile

0.5%

Citation Trend

2019

2020

greenLicense: arXiv Non-Exclusive Distribution

repositoryhttps://arxiv.org/pdf/1804.01398

GREENhttps://arxiv.org/pdf/1804.01398

repositoryhttps://arxiv.org/pdf/1804.01398

publisherhttps://epubs.siam.org/doi/pdf/10.1137/18M118150X

repositoryhttp://arxiv.org/abs/1804.01398

Fields of Study

Topological and Geometric Data AnalysisHIV Research and TreatmentNeuroinflammation and Neurodegeneration MechanismsMathematicsComputer ScienceBiologyPhysics0301 basic medicine0303 health sciences03 medical and health sciences

Keywords

Persistent homologyNoveltyRecombinationBarcodeInferenceEvolutionary biologyTopology (electrical circuits)Tree (set theory)Computer scienceMathematicsBiologyCombinatoricsArtificial intelligenceAlgorithmGeneGeneticsComputational Geometry (cs.CG)FOS: Computer and information sciencesPopulations and Evolution (q-bio.PE)Quantitative Biology - Quantitative MethodsPersistent homology and applications, topological data analysisreticulate evolutiontopological data analysisProblems related to evolutionFOS: Biological sciencesFOS: MathematicsComputer Science - Computational GeometryAlgebraic Topology (math.AT)Mathematics - Algebraic TopologyQuantitative Biology - Populations and EvolutionQuantitative Methods (q-bio.QM)

Sustainable Development Goals

SDG 0: Industry, innovation and infrastructure

Gromov Hyperbolicity, Geodesic Defect, and Apparent Pairs in Vietoris-Rips Filtrations

10.4230/lipics.socg.2022.15Schloss Dagstuhl – Leibniz-Zentrum für Informatik