Prediction of regulatory elements

Albin Sandelin

doi:10.1007/978-1-60327-429-6_11

Prediction of regulatory elements

Albin Sandelin

Functional Genomics

5 Citations (Scopus)

Abstract

Finding the regulatory mechanisms responsible for gene expression remains one of the most important challenges for biomedical research. A major focus in cellular biology is to find functional transcription factor binding sites (TFBS) responsible for the regulation of a downstream gene. As wet-lab methods are time consuming and expensive, it is not realistic to identify TFBS for all uncharacterized genes in the genome by purely experimental means. Computational methods aimed at predicting potential regulatory regions can increase the efficiency of wet-lab experiments significantly. Here, methods for building quantitative models describing the binding preferences of transcription factors based on literature-derived data are presented, as well as a general protocol for scanning promoters using cross-species comparison as a filter (phylogenetic footprinting).

Original language	English
Journal	Methods in Molecular Biology
Volume	453
Pages (from-to)	233-44
Number of pages	11
ISSN	1064-3745
DOIs	https://doi.org/10.1007/978-1-60327-429-6_11
Publication status	Published - 2008

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10.1007/978-1-60327-429-6_11

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title = "Prediction of regulatory elements",

abstract = "Finding the regulatory mechanisms responsible for gene expression remains one of the most important challenges for biomedical research. A major focus in cellular biology is to find functional transcription factor binding sites (TFBS) responsible for the regulation of a downstream gene. As wet-lab methods are time consuming and expensive, it is not realistic to identify TFBS for all uncharacterized genes in the genome by purely experimental means. Computational methods aimed at predicting potential regulatory regions can increase the efficiency of wet-lab experiments significantly. Here, methods for building quantitative models describing the binding preferences of transcription factors based on literature-derived data are presented, as well as a general protocol for scanning promoters using cross-species comparison as a filter (phylogenetic footprinting).",

author = "Albin Sandelin",

note = "Keywords: Animals; Binding Sites; Computational Biology; Humans; Promoter Regions (Genetics); Regulatory Elements, Transcriptional; Transcription Factors",

year = "2008",

doi = "10.1007/978-1-60327-429-6_11",

language = "English",

volume = "453",

pages = "233--44",

journal = "Methods in Molecular Biology",

issn = "1064-3745",

publisher = "Humana Press",

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TY - JOUR

T1 - Prediction of regulatory elements

AU - Sandelin, Albin

N1 - Keywords: Animals; Binding Sites; Computational Biology; Humans; Promoter Regions (Genetics); Regulatory Elements, Transcriptional; Transcription Factors

PY - 2008

Y1 - 2008

N2 - Finding the regulatory mechanisms responsible for gene expression remains one of the most important challenges for biomedical research. A major focus in cellular biology is to find functional transcription factor binding sites (TFBS) responsible for the regulation of a downstream gene. As wet-lab methods are time consuming and expensive, it is not realistic to identify TFBS for all uncharacterized genes in the genome by purely experimental means. Computational methods aimed at predicting potential regulatory regions can increase the efficiency of wet-lab experiments significantly. Here, methods for building quantitative models describing the binding preferences of transcription factors based on literature-derived data are presented, as well as a general protocol for scanning promoters using cross-species comparison as a filter (phylogenetic footprinting).

AB - Finding the regulatory mechanisms responsible for gene expression remains one of the most important challenges for biomedical research. A major focus in cellular biology is to find functional transcription factor binding sites (TFBS) responsible for the regulation of a downstream gene. As wet-lab methods are time consuming and expensive, it is not realistic to identify TFBS for all uncharacterized genes in the genome by purely experimental means. Computational methods aimed at predicting potential regulatory regions can increase the efficiency of wet-lab experiments significantly. Here, methods for building quantitative models describing the binding preferences of transcription factors based on literature-derived data are presented, as well as a general protocol for scanning promoters using cross-species comparison as a filter (phylogenetic footprinting).

U2 - 10.1007/978-1-60327-429-6_11

DO - 10.1007/978-1-60327-429-6_11

M3 - Journal article

C2 - 18712306

SN - 1064-3745

VL - 453

SP - 233

EP - 244

JO - Methods in Molecular Biology

JF - Methods in Molecular Biology

ER -

Prediction of regulatory elements

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