dorsal/arxiv
View SchemaAsterias: a parallelized web-based suite for the analysis of expression and aCGH data
| Authors | Andreu Alibes, Edward R. Morrissey, Andres Canada, Oscar M. Rueda, David Casado, Patricio Yankilevich, Ramon Diaz-Uriarte |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0610039 |
| URL | https://arxiv.org/abs/q-bio/0610039 |
Abstract
Asterias (\url{http://www.asterias.info}) is an integrated collection of freely-accessible web tools for the analysis of gene expression and aCGH data. Most of the tools use parallel computing (via MPI). Most of our applications allow the user to obtain additional information for user-selected genes by using clickable links in tables and/or figures. Our tools include: normalization of expression and aCGH data; converting between different types of gene/clone and protein identifiers; filtering and imputation; finding differentially expressed genes related to patient class and survival data; searching for models of class prediction; using random forests to search for minimal models for class prediction or for large subsets of genes with predictive capacity; searching for molecular signatures and predictive genes with survival data; detecting regions of genomic DNA gain or loss. The capability to send results between different applications, access to additional functional information, and parallelized computation make our suite unique and exploit features only available to web-based applications.
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"abstract": "Asterias (\\url{http://www.asterias.info}) is an integrated collection of\nfreely-accessible web tools for the analysis of gene expression and aCGH data.\nMost of the tools use parallel computing (via MPI). Most of our applications\nallow the user to obtain additional information for user-selected genes by\nusing clickable links in tables and/or figures. Our tools include:\nnormalization of expression and aCGH data; converting between different types\nof gene/clone and protein identifiers; filtering and imputation; finding\ndifferentially expressed genes related to patient class and survival data;\nsearching for models of class prediction; using random forests to search for\nminimal models for class prediction or for large subsets of genes with\npredictive capacity; searching for molecular signatures and predictive genes\nwith survival data; detecting regions of genomic DNA gain or loss. The\ncapability to send results between different applications, access to additional\nfunctional information, and parallelized computation make our suite unique and\nexploit features only available to web-based applications.",
"arxiv_id": "q-bio/0610039",
"authors": [
"Andreu Alibes",
"Edward R. Morrissey",
"Andres Canada",
"Oscar M. Rueda",
"David Casado",
"Patricio Yankilevich",
"Ramon Diaz-Uriarte"
],
"categories": [
"q-bio.GN",
"q-bio.OT"
],
"title": "Asterias: a parallelized web-based suite for the analysis of expression and aCGH data",
"url": "https://arxiv.org/abs/q-bio/0610039"
},
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"type": "Model",
"variant": "snapshot-2026-03-01",
"version": "0.1.0"
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