Boolean function networks

Maria Simak; Henry Horng Shing Lu; Chen Hsiang Yeang; Jinn Moon Yang

Boolean function networks

Maria Simak, Henry Horng Shing Lu^*, Chen Hsiang Yeang, Jinn Moon Yang

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Boolean function network (BFN) is a systematical approach proposed to the inference of gene regulatory networks (GRNs) and the related Boolean functions. This procedure utilizes two steps to integrate hidden Markov model (HMM), likelihood ratio test and Boolean functions for discovering direct pairwise relations between genes from time-course transcriptome data. The low computational complexity of BFN makes it advantageous for the applications on the genomewide scale. In this chapter we justify the need for novel approach and describe the inference procedure.

Original language	English
Title of host publication	Boolean Logic, Expressions and Theories
Subtitle of host publication	An Overview
Publisher	Nova Science Publishers, Inc.
Pages	1-19
Number of pages	19
ISBN (Electronic)	9781536170313
State	Published - 1 Jan 2020

Cite this

@inbook{e94b363c7a694ab99c4a7164f222920f,

title = "Boolean function networks",

abstract = "Boolean function network (BFN) is a systematical approach proposed to the inference of gene regulatory networks (GRNs) and the related Boolean functions. This procedure utilizes two steps to integrate hidden Markov model (HMM), likelihood ratio test and Boolean functions for discovering direct pairwise relations between genes from time-course transcriptome data. The low computational complexity of BFN makes it advantageous for the applications on the genomewide scale. In this chapter we justify the need for novel approach and describe the inference procedure.",

author = "Maria Simak and Lu, {Henry Horng Shing} and Yeang, {Chen Hsiang} and Yang, {Jinn Moon}",

year = "2020",

month = jan,

day = "1",

language = "English",

pages = "1--19",

booktitle = "Boolean Logic, Expressions and Theories",

publisher = "Nova Science Publishers, Inc.",

address = "United States",

}

TY - CHAP

T1 - Boolean function networks

AU - Simak, Maria

AU - Lu, Henry Horng Shing

AU - Yeang, Chen Hsiang

AU - Yang, Jinn Moon

PY - 2020/1/1

Y1 - 2020/1/1

N2 - Boolean function network (BFN) is a systematical approach proposed to the inference of gene regulatory networks (GRNs) and the related Boolean functions. This procedure utilizes two steps to integrate hidden Markov model (HMM), likelihood ratio test and Boolean functions for discovering direct pairwise relations between genes from time-course transcriptome data. The low computational complexity of BFN makes it advantageous for the applications on the genomewide scale. In this chapter we justify the need for novel approach and describe the inference procedure.

AB - Boolean function network (BFN) is a systematical approach proposed to the inference of gene regulatory networks (GRNs) and the related Boolean functions. This procedure utilizes two steps to integrate hidden Markov model (HMM), likelihood ratio test and Boolean functions for discovering direct pairwise relations between genes from time-course transcriptome data. The low computational complexity of BFN makes it advantageous for the applications on the genomewide scale. In this chapter we justify the need for novel approach and describe the inference procedure.

UR - http://www.scopus.com/inward/record.url?scp=85089046041&partnerID=8YFLogxK

M3 - Chapter

AN - SCOPUS:85089046041

SP - 1

EP - 19

BT - Boolean Logic, Expressions and Theories

PB - Nova Science Publishers, Inc.

ER -

Boolean function networks

Abstract

Other files and links

Fingerprint

Cite this