{
  "annotation_id": "9b481a44-58db-4aeb-a74d-480642f27329",
  "date_created": "2026-03-02T18:01:34.859000Z",
  "date_modified": "2026-03-02T18:01:34.859000Z",
  "file_hash": "25e61f10a6cdfa8646813bae6ed289a495c38d171176cd1eb0c2c7ea70e98fab",
  "private": false,
  "record": {
    "abstract": "In this report, correlation of the pixels comprising a microarray spot is\ninvestigated. Subsequently, correlation statistics namely: Pearson correlation\nand Spearman rank correlation are used to segment the foreground and background\nintensity of microarray spots. The performance of correlation-based\nsegmentation is compared to clustering-based (PAM, k-means) and seeded-region\ngrowing techniques (SPOT). It is shown that correlation-based segmentation is\nuseful in flagging poorly hybridized spots, thus minimizes false-positives. The\npresent study also raises the intriguing question of whether a change in\ncorrelation can be an indicator of differential gene expression.",
    "arxiv_id": "q-bio/0511030",
    "authors": [
      "Radhakrishnan Nagarajan",
      "Meenakshi Upreti"
    ],
    "categories": [
      "q-bio.GN",
      "q-bio.QM"
    ],
    "title": "Correlation Statistics for cDNA Microarray Image Analysis",
    "url": "https://arxiv.org/abs/q-bio/0511030"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "ff1172f1-2a32-4446-8517-85359a69b6fb",
    "id": "arXiv Dataset IDs",
    "type": "Model",
    "variant": "snapshot-2026-03-01",
    "version": "0.1.0"
  },
  "user_id": 1000002
}