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15 - Machine learning predicts microRNA target sites

from III - Computational biology of microRNAs

Published online by Cambridge University Press:  22 August 2009

Pål Sætrom Jr.
Affiliation:
Interagon AS Laboratoriesenteret Medisinsk Teknisk Senter NO-7489 Trondheim Norway
Ola Snøve
Affiliation:
Interagon AS Laboratoriesenteret Medisinsk Teknisk Senter NO-7489 Trondheim Norway
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Summary

Introduction

Ceanorhabditis elegans' lin-4 and let-7 were discovered seven years apart in the 1990s (Lee et al., 1993; Wightman et al., 1993; Reinhart et al., 2000). Because of their importance for correct timing in post-embryonic larval development in worms, these non-protein-coding molecules were first referred to as small temporal RNAs, but following the discovery of numerous RNAs with similar characteristics (Lau et al., 2001; Lee and Ambros, 2001; Lagos-Quintana et al., 2001), lin-4 and let-7 have been recognized as the founding members of the microRNA (miRNA) family. The details of the discovery of miRNAs and their involvement in various pathways are described in earlier chapters in Part I of this book.

To enable functional inference, it is important to identify the miRNA targets, and many efforts have been made to solve this problem in the past few years. MicroRNAs are known to regulate gene expression on two levels, namely by translational suppression (Olsen and Ambros, 1999) and mRNA depletion (Yekta et al., 2004). But despite massive resources invested in this problem, we have yet to find more than one human miRNA with assigned target and function (Hornstein et al., 2005). Massive evidence does, however, support the crucial role of miRNAs in accurate and timely regulation of messages, which means that we have to develop new approaches to identify their genetic targets.

Type
Chapter
Information
MicroRNAs
From Basic Science to Disease Biology
, pp. 210 - 220
Publisher: Cambridge University Press
Print publication year: 2007

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