Supervised and unsupervised algorithms for bioinformatics and data science

Bioinformatics refers to an ever evolving huge field of research based on millions of algorithms, designated to several data banks. Such algorithms are either supervised or unsupervised. In this article, a detailed overview of the supervised and unsupervised techniques is presented with the aid of e...

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Veröffentlicht in:Progress in biophysics and molecular biology Jg. 151; S. 14 - 22
Hauptverfasser: Sohail, Ayesha, Arif, Fatima
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England Elsevier Ltd 01.03.2020
Schlagworte:
Algorithms
Computational Biology - methods
Data Science - methods
Evolutionary bioinformatics
Machine learning
Supervised Machine Learning
Support vector machine learning
Unsupervised Machine Learning
Algorithms
Support vector machine learning
Evolutionary bioinformatics
Machine learning
ISSN:0079-6107, 1873-1732, 1873-1732
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Bioinformatics refers to an ever evolving huge field of research based on millions of algorithms, designated to several data banks. Such algorithms are either supervised or unsupervised. In this article, a detailed overview of the supervised and unsupervised techniques is presented with the aid of examples. The aim of this article is to provide the readers with the basic understanding of the state of the art models, which are key ingredients of explainable machine learning in the field of bioinformatics.
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SourceType-Scholarly Journals-1
ObjectType-Feature-2
ObjectType-Review-3
content type line 23
ISSN:0079-6107
1873-1732
1873-1732
DOI:10.1016/j.pbiomolbio.2019.11.012