Replaying the Evolutionary Tape: Biomimetic Reverse Engineering of Gene Networks
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Numerous methods have been developed for inference of gene regulatory networks from expression data, however, their strengths and weaknesses remain poorly understood. Accurate and systematic evaluation of these methods is hampered by the difficulty of cons ...
The experimental determination of transcriptional regulatory networks in the laboratory remains difficult and time-consuming, while computational methods to infer these networks provide only modest accuracy. The latter can be attributed in part to the limi ...
Transcription factor binding site(s) (TFBS) gain and loss (i.e., turnover) is a well-documented feature of cis-regulatory module (CRM) evolution, yet little attention has been paid to the evolutionary force(s) driving this turnover process. The predominant ...
Background: Computational inference of transcriptional regulatory networks remains a challenging problem, in part due to the lack of strong network models. In this paper we present evolutionary approaches to improve the inference of regulatory networks for ...
The expression of genes is controlled by regulatory networks, which perform fundamental information processing and control mechanisms in a cell. Unraveling and modelling these networks will be indispensable to gain a systems-level understanding of biologic ...
MicroRNAs (miRNAs) and transcription factors control eukaryotic cell proliferation, differentiation, and metabolism through their specific gene regulatory networks. However, differently from transcription factors, our understanding of the processes regulat ...
The determination of transcriptional regulatory networks is key to the understanding of biological systems. However, the experimental determination of transcriptional regulatory networks in the laboratory remains difficult and time-consuming, while current ...
Computational inference of transcriptional regulatory networks remains a challenging problem, in part due to the lack of strong network models. In this paper we present evolutionary approaches to improve the inference of regulatory networks for a family of ...
Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from single-gene single-protein experimental approach to studying the behaviour of a ...
Gene regulatory networks (GRNs) play a vital role in metazoan development and function, and deregulation of these networks is often implicated in disease. GRNs depict the dynamic interactions between genomic and regulatory state components. The genomic com ...
