Reconstructing Latent Orderings by Spectral Clustering

Autor: Recanati, Antoine, Kerdreux, Thomas, d'Aspremont, Alexandre

Spectral clustering uses a graph Laplacian spectral embedding to enhance the cluster structure of some data sets. When the embedding is one dimensional, it can be used to sort the items (spectral ordering). A number of empirical results also suggests

Externí odkaz: http://arxiv.org/abs/1807.07122

A spectral algorithm for fast de novo layout of uncorrected long nanopore reads

Autor: Recanati, Antoine, Brüls, Thomas, d'Aspremont, Alexandre

Motivation: New long read sequencers promise to transform sequencing and genome assembly by producing reads tens of kilobases long. However their high error rate significantly complicates assembly and requires expensive correction steps to layout the

Externí odkaz: http://arxiv.org/abs/1609.07293

Relaxations du problème de sériation et applications à l'assemblage de génome de novo

Autor: Recanati, Antoine

Publikováno v: Computer Science [cs]. PSL Research University, 2018. English
Data Structures and Algorithms [cs.DS]. Université Paris sciences et lettres, 2018. English. ⟨NNT : 2018PSLEE086⟩

In a sequencing experiment, we can only “read” small fragments (reads) of DNA due to physical limitations, whose location on the genome is unknown. De novo assembly aims to put them together to retrieve the full DNA sequence, like a jigsaw puzzle

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::a7d3ace8f48e1a00d9277c57460f817d
https://hal.archives-ouvertes.fr/tel-01984368/file/thesis_main.pdf