dorsal/arxiv
View SchemaProcess Pathway Inference via Time Series Analysis
| Authors | Chris Wiggins, Ilya Nemenman |
|---|---|
| Categories | |
| ArXiv ID | physics/0206031 |
| URL | https://arxiv.org/abs/physics/0206031 |
| Journal | Experim. Mech., 43(3), 2003 |
Abstract
Motivated by recent experimental developments in functional genomics, we construct and test a numerical technique for inferring it process pathways, in which one process calls another process, from time series data. We validate using a case in which data are readily available and formulate an extension, appropriate for genetic regulatory networks, which exploits Bayesian inference and in which the present--day undersampling is compensated for by prior understanding of genetic regulation.
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"abstract": "Motivated by recent experimental developments in functional genomics, we\nconstruct and test a numerical technique for inferring it process pathways, in\nwhich one process calls another process, from time series data. We validate\nusing a case in which data are readily available and formulate an extension,\nappropriate for genetic regulatory networks, which exploits Bayesian inference\nand in which the present--day undersampling is compensated for by prior\nunderstanding of genetic regulation.",
"arxiv_id": "physics/0206031",
"authors": [
"Chris Wiggins",
"Ilya Nemenman"
],
"categories": [
"physics.bio-ph",
"physics.data-an",
"q-bio.GN",
"q-bio.QM"
],
"journal_ref": "Experim. Mech., 43(3), 2003",
"title": "Process Pathway Inference via Time Series Analysis",
"url": "https://arxiv.org/abs/physics/0206031"
},
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