An Innovative Perspective on Metabolomics Data Analysis in Biomedical Research Using Concept Drift Detection

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F21%3A00126185" target="_blank" >RIV/00216224:14330/21:00126185 - isvavai.cz</a>

Alternative codes found

RIV/00216305:26220/21:PU142331

Result on the web

<a href="http://dx.doi.org/10.1109/BIBM52615.2021.9669418" target="_blank" >http://dx.doi.org/10.1109/BIBM52615.2021.9669418</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/BIBM52615.2021.9669418" target="_blank" >10.1109/BIBM52615.2021.9669418</a>

Result language

angličtina

Original language name

An Innovative Perspective on Metabolomics Data Analysis in Biomedical Research Using Concept Drift Detection

Original language description

The most challenging applications of data analysis prediction are mostly related to scenarios, where the source data is being provided in a time course. As the distribution of the underlying reality shifts over a time, a classification model trained on the previously relevant data starts to yield incorrect predictions about the data that are relevant right now. This phenomenon in machine learning is called concept drift. Within biomedical data, one of the molecular networks that is most significantly changing over a time, is the metabolome. Using metabolomics analysis to biomedical applications, makes an ideal tool for preventive healthcare, pharmaceutical industry, and even ecology engineering. This study provides an innovated perspective on the analysis of metabolomics datasets using the concept of drift detection. The evaluation is based on two main goals. The first goal is connected to the concept drift detection in available metabolomics datasets and the second goal is to provide the assessment of commonly used tools, resulting in the best detection approach for a general metabolomics dataset.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

—

OECD FORD branch

10602 - Biology (theoretical, mathematical, thermal, cryobiology, biological rhythm), Evolutionary biology

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2021

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Proceedings of BIBM 2021

ISBN

9781665401265

ISSN

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e-ISSN

—

Number of pages

8

Pages from-to

3075-3082

Publisher name

IEEE

Place of publication

Houston, TX, USA

Event location

Houston, TX, USA

Event date

Jan 1, 2021

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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