From small studies to precision medicine: prioritizing candidate biomarkers

There are still many open questions in data-analytic research pertaining to biomarker development in the era of personalized/precision medicine and big data. Among them is the question of what constitutes best practice for the extraction of prioritized lists of candidate biomarkers from smaller stud...

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Detalles Bibliográficos
Autores principales: Gaile, Daniel P, Miecznikowski, Jeffrey C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Research Highlight
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3978446/
https://www.ncbi.nlm.nih.gov/pubmed/24286480
http://dx.doi.org/10.1186/gm507
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author Gaile, Daniel P
Miecznikowski, Jeffrey C
author_facet Gaile, Daniel P
Miecznikowski, Jeffrey C
author_sort Gaile, Daniel P
collection PubMed
description There are still many open questions in data-analytic research pertaining to biomarker development in the era of personalized/precision medicine and big data. Among them is the question of what constitutes best practice for the extraction of prioritized lists of candidate biomarkers from smaller studies that are ‘hypothesis generating’ in nature. A recent comparison of methods to detect patient-specific aberrant expression events in small- to medium-sized (10 to 50 samples) studies provides results that favor the use of outlying degree methods. See related Research, http://genomemedicine.com/content/5/11/103
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spelling pubmed-39784462014-11-29 From small studies to precision medicine: prioritizing candidate biomarkers Gaile, Daniel P Miecznikowski, Jeffrey C Genome Med Research Highlight There are still many open questions in data-analytic research pertaining to biomarker development in the era of personalized/precision medicine and big data. Among them is the question of what constitutes best practice for the extraction of prioritized lists of candidate biomarkers from smaller studies that are ‘hypothesis generating’ in nature. A recent comparison of methods to detect patient-specific aberrant expression events in small- to medium-sized (10 to 50 samples) studies provides results that favor the use of outlying degree methods. See related Research, http://genomemedicine.com/content/5/11/103 BioMed Central 2013-11-29 /pmc/articles/PMC3978446/ /pubmed/24286480 http://dx.doi.org/10.1186/gm507 Text en Copyright © 2013 BioMed Central Ltd.
spellingShingle Research Highlight
Gaile, Daniel P
Miecznikowski, Jeffrey C
From small studies to precision medicine: prioritizing candidate biomarkers
title From small studies to precision medicine: prioritizing candidate biomarkers
title_full From small studies to precision medicine: prioritizing candidate biomarkers
title_fullStr From small studies to precision medicine: prioritizing candidate biomarkers
title_full_unstemmed From small studies to precision medicine: prioritizing candidate biomarkers
title_short From small studies to precision medicine: prioritizing candidate biomarkers
title_sort from small studies to precision medicine: prioritizing candidate biomarkers
topic Research Highlight
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3978446/
https://www.ncbi.nlm.nih.gov/pubmed/24286480
http://dx.doi.org/10.1186/gm507
work_keys_str_mv AT gailedanielp fromsmallstudiestoprecisionmedicineprioritizingcandidatebiomarkers
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