نتایج جستجو برای: gene regulatory network grn
تعداد نتایج: 1879661 فیلتر نتایج به سال:
The ecologically significant shift in developmental strategy from planktotrophic (feeding) to lecithotrophic (nonfeeding) development in the sea urchin genus Heliocidaris is one of the most comprehensively studied life history transitions in any animal. Although the evolution of lecithotrophy involved substantial changes to larval development and morphology, it is not known to what extent chang...
The correct inference of gene regulatory networks (GRN) remains as a fascinating task for researchers to understand the detailed process of complex biological regulations and functions. With availability of large dimensional microarray data, relationships among thousands of genes can be extracted simultaneously that is a reverse engineering problem. Among the different popular models to infer G...
Identification of cell-fate determinants for directing stem cell differentiation remains a challenge. Moreover, little is known about how cell-fate determinants are regulated in functionally important subnetworks in large gene-regulatory networks (i.e., GRN motifs). Here we propose a model of stem cell differentiation in which cell-fate determinants work synergistically to determine different c...
We developed a bio-inspired robot controller combining an artificial genome with an agent-based control system. The genome encodes a gene regulatory network (GRN) that is switched on by environmental cues and, following the rules of transcriptional regulation, provides output signals to actuators. Whereas the genome represents the full encoding of the transcriptional network, the agent-based sy...
MOTIVATION Gene regulatory networks (GRNs) affect numerous cellular processes and every process of life, and abnormalities of GRN lead to breast cancer. Transcription factors (TFs) and microRNAs (miRNAs) are two of the best-studied gene regulatory mechanisms. However, the architecture and feature of GRNs by TFs and miRNAs in breast cancer and its subtypes were unknown. In this study, we investi...
Evolution produces gene regulatory networks (GRNs) able to control cells. With this inspiration we evolve artificial GRN (AGRN) genomes for the reinforcement learning control of mechanical systems with unknown dynamics, a problem domain similar in its sparse feedback to that of controlling a biological cell. From the fractal GRN (FGRN), a successful but complex GRN model, we obtain the Input-Me...
Mutations in the aristaless-related homeobox (ARX) gene are associated with multiple neurologic disorders in humans. Studies in mice indicate Arx plays a role in neuronal progenitor proliferation and development of the cerebral cortex, thalamus, hippocampus, striatum, and olfactory bulbs. Specific defects associated with Arx loss of function include abnormal interneuron migration and subtype di...
Bio-inspired algorithms are widely used to optimize the model parameters of GRN. In this paper, focus is given to develop improvised versions of bio-inspired algorithm for the specific problem of reconstruction of gene regulatory network. The approach is applied to the data set that was developed by the DNA microarray technology through biological experiments in the lab. This paper introduced a...
Gene Regulatory Network (GRN) inference is a major objective of Systems Biology. The complexity of biological systems and the lack of adequate data have posed many challenges to the inference problem. Community networks integrate predictions from individual methods in a “meta predictor”, in order to compose the advantages of different methods and soften individual limitations. This paper propos...
A central question in evolutionary biology concerns the transition between discrete numbers of units (e.g. vertebrate digits, arthropod segments). How do particular numbers of units, robust and characteristic for one species, evolve into another number for another species? Intermediate phases with a diversity of forms have long been theorized, but these leave little fossil or genomic data. We u...
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