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Federico De Masi

Researcher at Technical University of Denmark

Publications -  39
Citations -  2454

Federico De Masi is an academic researcher from Technical University of Denmark. The author has contributed to research in topics: Type 2 diabetes & Diabetes mellitus. The author has an hindex of 17, co-authored 36 publications receiving 1988 citations. Previous affiliations of Federico De Masi include Harvard University & Massachusetts Institute of Technology.

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High-resolution DNA-binding specificity analysis of yeast transcription factors

TL;DR: High-resolution binding profiles for 89 known and predicted yeast TFs are determined and proteins that bind the PAC (Polymerase A and C) motif (GATGAG) and regulate ribosomal RNA transcription and processing, core cellular processes that are constituent to ribosome biogenesis are discovered.
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Systematic discovery of new recognition peptides mediating protein interaction networks.

TL;DR: The approach based on motif over-representation in non-homologous sequences, rediscovers known motifs and predicts dozens of others that will give molecular insight into protein networks and greatly illuminate cellular processes.

Systematic Discovery of New Recognition Peptides Mediating Protein Interaction

TL;DR: In this paper, a method based on motif over-representation in non-homologous sequences was proposed to detect linear motifs, which can explain how one protein is able to bind to very different partners.
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A Multiparameter Network Reveals Extensive Divergence between C. elegans bHLH Transcription Factors

TL;DR: This work comprehensively identifies dimerization partners, spatiotemporal expression patterns, and DNA-binding specificities for the C. elegans bHLH family of TFs, and model these data into an integrated network that displays both specificity and promiscuity, as some b HLH proteins, DNA sequences, and tissues are highly connected, whereas others are not.
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Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals

Lasse Folkersen, +91 more
TL;DR: The utility of large-scale mapping of the genetics of the proteome is demonstrated and pQTLs are provided as a resource for future precision studies of circulating proteins in human health.