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Bioinformatics and AI: A First Step
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Using statistical profiling to decipher hidden chromatin contacts resulting from repeated sequences
Published in HAL Thesis, 2024
Genomes are not static entities; they evolve and acquire various repeated elements Repetitive genomic elements, crucial yet challenging for NGS analysis, are addressed by Hicberg, an algorithm employing statistical inference to accurately map their reads in diverse sequencing data and, in yeast, reveals novel interactions between retrotransposons and the enigmatic 2-micron plasmid. Applied to yeast, Hicberg further unveils the influence of retrotransposons on chromatin organization and identifies other new genomic interactions, offering a more comprehensive understanding of genome structure and dynamics.
Recommended citation: Sébastien Gradit. Using statistical profiling to decipher hidden chromatin contacts resulting from repeated sequences. Genetics. Sorbonne Université, 2024. English. ⟨NNT : 2024SORUS494⟩. ⟨tel-05010244⟩
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Hicberg: Reconstruction of genomic signals from repeated elements
Published in Pending, 2025
This paper introduces Hicberg, a new method to more accurately map the 3D organization of genomes by resolving ambiguities caused by repetitive DNA sequences in Hi-C data, revealing potentially hidden structural features in various organisms.
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Using statistical profiling to decipher hidden chromatin contacts resulting from repeated sequences
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teaching
Teaching experience 2
Workshop, University 1, Department, 2015
This is a description of a teaching experience. You can use markdown like any other post.