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Isaac Crespo

Researcher at Swiss Institute of Bioinformatics

Publications -  36
Citations -  943

Isaac Crespo is an academic researcher from Swiss Institute of Bioinformatics. The author has contributed to research in topics: Gene regulatory network & Immune system. The author has an hindex of 14, co-authored 32 publications receiving 747 citations. Previous affiliations of Isaac Crespo include Complutense University of Madrid & University of Lausanne.

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Integrating Pathways of Parkinson's Disease in a Molecular Interaction Map

TL;DR: A computationally tractable, comprehensive molecular interaction map of Parkinson's disease that integrates pathways implicated in PD pathogenesis such as synaptic and mitochondrial dysfunction, impaired protein degradation, alpha-synuclein pathobiology and neuroinflammation is introduced.
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A Novel Network Integrating a miRNA-203/SNAI1 Feedback Loop which Regulates Epithelial to Mesenchymal Transition

TL;DR: A novel EMT core network integrating two fundamental negative feedback loops, miR203/SNAI1 and miR200/ZEB is proposed that could function as a switch controlling epithelial cell plasticity during differentiation and cancer progression.
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Detecting cellular reprogramming determinants by differential stability analysis of gene regulatory networks.

TL;DR: A computational method, without any preliminary selection of candidate genes, to identify reduced subsets of genes, which when perturbed can induce transitions between cellular phenotypes, and represents a useful framework to assist researchers in the field of cellular reprogramming to design experimental strategies.
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A general strategy for cellular reprogramming: the importance of transcription factor cross-repression.

TL;DR: This work introduces a method that generalizes the concept of transcription factor cross‐repression to systematically predict sets of genes, whose perturbations induce cellular transitions between any given pair of cell types, and is the first method that systematically makes these predictions without prior knowledge of potential candidate genes and pathways involved.