On the public citation graph
https://doi.org/10.1101/423632
0 signed · 50 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1007/s10479-011-0841-3openalex-snapshot
Multiobjective evolutionary algorithms to identify highly autocorrelated areas: the case of spatial distribution in financially compromised farms
inferredcites →https://doi.org/10.1016/j.ajhg.2008.08.005openalex-snapshot
The Population Reference Sample, POPRES: A Resource for Population, Disease, and Pharmacological Genetics Research
inferredcites →https://doi.org/10.1016/j.ajhg.2013.06.020openalex-snapshot
RFMix: A Discriminative Modeling Approach for Rapid and Robust Local-Ancestry Inference
inferredcites →https://doi.org/10.1016/j.molcel.2012.08.019openalex-snapshot
Janus-Faced PIDD: A Sensor for DNA Damage-Induced Cell Death or Survival?
inferredcites →https://doi.org/10.1038/nature07331openalex-snapshot
Genes mirror geography within Europe
inferredcites →https://doi.org/10.1038/nature14230openalex-snapshot
The fine-scale genetic structure of the British population
inferredcites →https://doi.org/10.1038/nature15393openalex-snapshot
A global reference for human genetic variation
inferredcites →https://doi.org/10.1038/nbt.4314openalex-snapshot
Dimensionality reduction for visualizing single-cell data using UMAP
inferredcites →https://doi.org/10.1038/ng.139openalex-snapshot
Interpreting principal component analyses of spatial population genetic variation
inferredcites →https://doi.org/10.1038/ng.3401openalex-snapshot
Population genetic differentiation of height and body mass index across Europe
inferredcites →https://doi.org/10.1086/519795openalex-snapshot
PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses
inferredcites →https://doi.org/10.1142/s0219720017500172openalex-snapshot
Application of t-SNE to human genetic data
inferredcites →https://doi.org/10.1371/journal.pgen.0020117.eoropenalex-snapshot
Genome-Wide Analysis of Gene Expression during Early Arabidopsis Flower Development
inferredcites →https://doi.org/10.1371/journal.pgen.0020190openalex-snapshot
Population Structure and Eigenanalysis
inferredcites →https://doi.org/10.1371/journal.pgen.1000686openalex-snapshot
A Genealogical Interpretation of Principal Components Analysis
inferredcites →https://doi.org/10.1371/journal.pgen.1002453openalex-snapshot
Inference of Population Structure using Dense Haplotype Data
inferredcites →https://doi.org/10.1371/journal.pgen.1006059openalex-snapshot
The Great Migration and African-American Genomic Diversity
inferredcites →https://doi.org/10.1371/journal.pmed.1001779openalex-snapshot
UK Biobank: An Open Access Resource for Identifying the Causes of a Wide Range of Complex Diseases of Middle and Old Age
inferredcites →https://doi.org/10.1371/journal.pone.0056883openalex-snapshot
Visualization of SNPs with t-SNE
inferredcites →https://doi.org/10.2307/146277openalex-snapshot
An Overview of the Health and Retirement Study
inferredcites →https://doi.org/10.25080/majora-92bf1922-011openalex-snapshot
Statsmodels: Econometric and Statistical Modeling with Python
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python
inferredcites →https://doi.org/10.48550/arxiv.1802.03426openalex-snapshot
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
inferredcites →https://doi.org/10.5860/choice.32-5738openalex-snapshot
Stature, living standards, and economic development: essays in anthropometric history
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4165341openalex-extracted
Parkinson's Disease Diagnosis Beyond Clinical Features: A Bio-Marker Using Topological Machine Learning of rs-fMRI
inferred← citeshttps://doi.org/10.1002/cyto.a.24158openalex-snapshot
A Cancer Biologist's Primer on Machine Learning Applications in High‐Dimensional Cytometry
inferred← citeshttps://doi.org/10.1007/s41870-022-01048-yopenalex-snapshot
UMAP guided topological analysis of transcriptomic data for cancer subtyping
inferred← citeshttps://doi.org/10.1016/j.ajhg.2020.03.004openalex-snapshot
Genotyping Array Design and Data Quality Control in the Million Veteran Program
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2023.106640openalex-snapshot
Robust correlation estimation and UMAP assisted topological analysis of omics data for disease subtyping
inferred← citeshttps://doi.org/10.1016/j.egyr.2022.02.290openalex-snapshot
Detection of false data injection attack in power information physical system based on SVM–GAB algorithm
inferred← citeshttps://doi.org/10.1016/j.mlwa.2023.100490openalex-snapshot
Accounting for diverse feature-types improves patient stratification on tabular clinical datasets
inferred← citeshttps://doi.org/10.1016/j.neuroscience.2022.11.022openalex-snapshot
Parkinson’s Disease Diagnosis beyond Clinical Features: A Bio-marker using Topological Machine Learning of Resting-state Functional Magnetic Resonance Imaging
inferred← citeshttps://doi.org/10.1016/j.newideapsych.2019.04.005openalex-snapshot
Why genome-wide associations with cognitive ability measures are probably spurious
inferred← citeshttps://doi.org/10.1038/s41467-019-13056-xopenalex-snapshot
The art of using t-SNE for single-cell transcriptomics
inferred← citeshttps://doi.org/10.1093/cybsec/tyac010openalex-snapshot
Entanglement: cybercrime connections of a public forum population
inferred← citeshttps://doi.org/10.1093/nar/gkz361openalex-snapshot
Fast hierarchical Bayesian analysis of population structure
inferred← citeshttps://doi.org/10.1101/2020.01.06.896613openalex-snapshot
Measuring genetic variation in the multi-ethnic Million Veteran Program (MVP)
inferred← citeshttps://doi.org/10.1101/531210openalex-snapshot
The mutational constraint spectrum quantified from variation in 141,456 humans
inferred← citeshttps://doi.org/10.1371/journal.pgen.1009303openalex-snapshot
Creating artificial human genomes using generative neural networks
inferred← citeshttps://doi.org/10.48550/arxiv.1802.03426openalex-snapshot
UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
Editorial review for independent work. ICSAC — the Institute for Complexity
Science and Advanced Computing — runs a structured editorial panel for researchers
publishing outside journals, and publishes on CiteStamp rails. Submission is free
and goes through ORCID: icsacinstitute.org/submit.