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Paul Guilhamon

dblp:231/4311 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2019
0000-0001-8276-5987ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%

Topics — the 1 heaviest of 1, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › genomics
genome organization
0.412019
C3D: a tool to predict 3D genomic interactions between cis-regulatory elements · Bioinform. 2019

Methods — techniques the papers use, named apart from their topics

unsupervised learning · 0.4correlation analysis · 0.4
YearPublicationVenuePosition
2019 C3D: a tool to predict 3D genomic interactions between cis-regulatory elements
abstract
MOTIVATION: The 3D genome architecture influences the regulation of genes by facilitating chromatin interactions between distal cis-regulatory elements and gene promoters. We implement Cross Cell-type Correlation based on DNA accessibility (C3D), a customizable computational tool that predicts chromatin interactions using an unsupervised algorithm that utilizes correlations in chromatin measurements, such as DNaseI hypersensitivity signals. RESULTS: C3D accurately predicts 32.7%, 18.3% and 24.1% of interactions, validated by ChIA-PET assays, between promoters and distal regions that overlie DNaseI hypersensitive sites in K562, MCF-7 and GM12878 cells, respectively. AVAILABILITY AND IMPLEMENTATION: Source code is open-source and freely available on GitHub (https://github.com/LupienLabOrganization/C3D) under the GNU GPLv3 license. C3D is implemented in Bash and R; it runs on any platform with Bash (≥4.0), R (≥3.1.1) and BEDTools (≥2.19.0). It requires the following R packages: GenomicRanges, Sushi, data.table, preprocessCore and dynamicTreeCut. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Tahmid Mehdi, Swneke D. Bailey, Paul Guilhamon, Mathieu Lupien
Bioinform.3
2018 SMuRF: a novel tool to identify regulatory elements enriched for somatic point mutations
abstract
BACKGROUND: Single Nucleotide Variants (SNVs), including somatic point mutations and Single Nucleotide Polymorphisms (SNPs), in noncoding cis-regulatory elements (CREs) can affect gene regulation and lead to disease development. Several approaches have been developed to identify highly mutated regions, but these do not take into account the specific genomic context, and thus likelihood of mutation, of CREs. RESULTS: Here, we present SMuRF (Significantly Mutated Region Finder), a user-friendly command-line tool to identify these significantly mutated regions from user-defined genomic intervals and SNVs. We demonstrate this using publicly available datasets in which SMuRF identifies 72 significantly mutated CREs in liver cancer, including known mutated gene promoters as well as previously unreported regions. CONCLUSIONS: SMuRF is a helpful tool to allow the simple identification of significantly mutated regulatory elements. It is open-source and freely available on GitHub ( https://github.com/LupienLab/SMURF ).
Paul Guilhamon, Mathieu Lupien
BMC Bioinform.1