Reverse-engineering transcription control networks.
نویسندگان
چکیده
Microarray technologies, which enable the simultaneous measurement of all RNA transcripts in a cell, have spawned the development of algorithms for reverse-engineering transcription control networks. In this article, we classify the algorithms into two general strategies: physical modeling and influence modeling. We discuss the biological and computational principles underlying each strategy, and provide leading examples of each. We also discuss the practical considerations for developing and applying the various methods.
منابع مشابه
De-Novo Learning of Genome-Scale Regulatory Networks in S. cerevisiae
De-novo reverse-engineering of genome-scale regulatory networks is a fundamental problem of biological and translational research. One of the major obstacles in developing and evaluating approaches for de-novo gene network reconstruction is the absence of high-quality genome-scale gold-standard networks of direct regulatory interactions. To establish a foundation for assessing the accuracy of d...
متن کاملNonparametric Bayesian inference for perturbed and orthologous gene regulatory networks
MOTIVATION The generation of time series transcriptomic datasets collected under multiple experimental conditions has proven to be a powerful approach for disentangling complex biological processes, allowing for the reverse engineering of gene regulatory networks (GRNs). Most methods for reverse engineering GRNs from multiple datasets assume that each of the time series were generated from netw...
متن کاملGenome-wide In-silico Identification of Transcriptional Regulators Controlling Cell Cycle in Human Cells
Dissection of regulatory networks that control gene transcription is one of the greatest challenges of functional genomics. By utilizing human genomic sequences, models for binding sites of known transcription factors and gene expression data, we demonstrate that the reverse engineering approach, which infers regulatory mechanisms from gene expression patterns, can reveal transcriptional networ...
متن کاملCNET: an algorithm for Reverse Engineering of Causal Gene Networks
We present a novel Reverse Engineering algorithm, CNET, to reconstruct Gene Regulatory Networks from microarray time series data. CNET can be considered an improvement of the Mutual Information approach, present in the REVEAL [5] algorithm, with an innovative scoring function, to cope with noise, quantization errors and gene characteristic transcription delays. We tested the algorithm on simula...
متن کاملTowards Reverse Engineering of Genetic Regulatory Networks
The major goal o f computational biolo gy is to derive regulatory interactions between genes from large-scale gene expression data and other biological sources. There have been many attemp ts to reach this goal, but the field needs more research before we can claim that we have reached a complete understanding of reverse engineering of regulatory networks. One of the aspects that have not been ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- Physics of life reviews
دوره 2 1 شماره
صفحات -
تاریخ انتشار 2005