Conference
Optimal Selection of Microarray Analysis Methods Using a Conceptual Clustering Algorithm
| Τίτλος: | Optimal Selection of Microarray Analysis Methods Using a Conceptual Clustering Algorithm |
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| Συγγραφείς: | Rubio Escudero, Cristina, Romero Zaliz, Rocío, Cordón, Óscar, Harari, Óscar, Val, Coral del, Zwir, Igor |
| Συνεισφορές: | Lenguajes y Sistemas Informáticos, TIC-254: Data Science and Big Data Lab |
| Στοιχεία εκδότη: | Springer |
| Έτος έκδοσης: | 2022 |
| Συλλογή: | idUS - Deposito de Investigación Universidad de Sevilla |
| Περιγραφή: | The rapid development of methods that select over/under expressed genes from microarray experiments have not yet matched the need for tools that identify informational profiles that differentiate between experimental condi tions such as time, treatment and phenotype. Uncertainty arises when methods devoted to identify significantly expressed genes are evaluated: do all microar ray analysis methods yield similar results from the same input dataset? do dif ferent microarray datasets require distinct analysis methods?. We performed a detailed evaluation of several microarray analysis methods, finding that none of these methods alone identifies all observable differential profiles, nor subsumes the results obtained by the other methods. Consequently, we propose a proce dure that, given certain user-defined preferences, generates an optimal suite of statistical methods. These solutions are optimal in the sense that they constitute partial ordered subsets of all possible method-associations bounded by both, the most specific and the most sensitive available solution. |
| Τύπος εγγράφου: | conference object |
| Περιγραφή αρχείου: | application/pdf |
| Γλώσσα: | English |
| Relation: | EvoWorkshops 2006: Workshops on Applications of Evolutionary Computation (2006), pp. 172-183.; https://link.springer.com/chapter/10.1007/11732242_16; Berlin, Germany; https://hdl.handle.net/11441/139997; https://doi.org/10.1007/11732242_16 |
| DOI: | 10.1007/11732242_16 |
| Διαθεσιμότητα: | https://hdl.handle.net/11441/139997 https://doi.org/10.1007/11732242_16 |
| Rights: | Attribution-NonCommercial-NoDerivatives 4.0 Internacional ; http://creativecommons.org/licenses/by-nc-nd/4.0/ ; open access |
| Αριθμός Καταχώρησης: | edsbas.C19CC551 |
| Βάση Δεδομένων: | BASE |
| DOI: | 10.1007/11732242_16 |
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