Manipulating cellular microRNAs and analyzing high-dimensional gene expression data using machine learning workflows

Vijit Saini; Mugdha V. Joglekar; Wilson K. M. Wong; Guozhi Jiang; Najah T. Nassif; Ann M. Simpson; Ronald C. W. Ma; Louise T. Dalgaard; Anandwardhan A. Hardikar

doi:10.1016/j.xpro.2021.100910

Manipulating cellular microRNAs and analyzing high-dimensional gene expression data using machine learning workflows

Vijit Saini
, Mugdha V. Joglekar
, Wilson K. M. Wong
, Guozhi Jiang
, Najah T. Nassif
, Ann M. Simpson
, Ronald C. W. Ma
, Louise T. Dalgaard
, Anandwardhan A. Hardikar

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

MicroRNAs (miRNAs) are elements of the gene regulatory network and manipulating their abundance is essential toward elucidating their role in patho-physiological conditions. We present a detailed workflow that identifies important miRNAs using a machine learning algorithm. We then provide optimized techniques to validate the identified miRNAs through over-expression/loss-of-function studies. Overall, these protocols apply to any field in biology where high-dimensional data are produced. For complete details on the use and execution of this protocol, please refer to Wong et al. (2021a).

Original language	English
Article number	100910
Number of pages	17
Journal	Star Protocols
Volume	2
Issue number	4
DOIs	https://doi.org/10.1016/j.xpro.2021.100910
Publication status	Published - 17 Dec 2021

Bibliographical note

Publisher Copyright:
© 2021

Open Access - Access Right Statement

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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10.1016/j.xpro.2021.100910

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title = "Manipulating cellular microRNAs and analyzing high-dimensional gene expression data using machine learning workflows",

abstract = "MicroRNAs (miRNAs) are elements of the gene regulatory network and manipulating their abundance is essential toward elucidating their role in patho-physiological conditions. We present a detailed workflow that identifies important miRNAs using a machine learning algorithm. We then provide optimized techniques to validate the identified miRNAs through over-expression/loss-of-function studies. Overall, these protocols apply to any field in biology where high-dimensional data are produced. For complete details on the use and execution of this protocol, please refer to Wong et al. (2021a).",

author = "Vijit Saini and Joglekar, \{Mugdha V.\} and Wong, \{Wilson K. M.\} and Guozhi Jiang and Nassif, \{Najah T.\} and Simpson, \{Ann M.\} and Ma, \{Ronald C. W.\} and Dalgaard, \{Louise T.\} and Hardikar, \{Anandwardhan A.\}",

note = "Publisher Copyright: {\textcopyright} 2021",

year = "2021",

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day = "17",

doi = "10.1016/j.xpro.2021.100910",

language = "English",

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AU - Saini, Vijit

AU - Joglekar, Mugdha V.

AU - Wong, Wilson K. M.

AU - Jiang, Guozhi

AU - Nassif, Najah T.

AU - Simpson, Ann M.

AU - Ma, Ronald C. W.

AU - Dalgaard, Louise T.

AU - Hardikar, Anandwardhan A.

PY - 2021/12/17

Y1 - 2021/12/17

N2 - MicroRNAs (miRNAs) are elements of the gene regulatory network and manipulating their abundance is essential toward elucidating their role in patho-physiological conditions. We present a detailed workflow that identifies important miRNAs using a machine learning algorithm. We then provide optimized techniques to validate the identified miRNAs through over-expression/loss-of-function studies. Overall, these protocols apply to any field in biology where high-dimensional data are produced. For complete details on the use and execution of this protocol, please refer to Wong et al. (2021a).

AB - MicroRNAs (miRNAs) are elements of the gene regulatory network and manipulating their abundance is essential toward elucidating their role in patho-physiological conditions. We present a detailed workflow that identifies important miRNAs using a machine learning algorithm. We then provide optimized techniques to validate the identified miRNAs through over-expression/loss-of-function studies. Overall, these protocols apply to any field in biology where high-dimensional data are produced. For complete details on the use and execution of this protocol, please refer to Wong et al. (2021a).

UR - https://hdl.handle.net/1959.7/uws:65320

U2 - 10.1016/j.xpro.2021.100910

DO - 10.1016/j.xpro.2021.100910

M3 - Article

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SN - 2666-1667

VL - 2

JO - Star Protocols

JF - Star Protocols

IS - 4

M1 - 100910

ER -

Manipulating cellular microRNAs and analyzing high-dimensional gene expression data using machine learning workflows

Abstract

Bibliographical note

Open Access - Access Right Statement

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