EDBT 2026 Demo / reviewers in the wild / expert
Fiona Kathryn Hamey
dblp:152/7652
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
chromosome conformation capture |
0.2 | 1 | 2014 | FisHiCal: an R package for iterative FISH-based calibration of Hi-C data · Bioinform. 2014 |
Bioinformatics and computational biology › epigenomics › 3d genome organization
3d genome reconstruction |
0.1 | 1 | 2014 | FisHiCal: an R package for iterative FISH-based calibration of Hi-C data · Bioinform. 2014 |
Bioinformatics and computational biology › genomics
genome organization |
0.1 | 1 | 2014 | FisHiCal: an R package for iterative FISH-based calibration of Hi-C data · Bioinform. 2014 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | FisHiCal: an R package for iterative FISH-based calibration of Hi-C dataabstractUNLABELLED: The fluorescence in situ hybridization (FISH) method has been providing valuable information on physical distances between loci (via image analysis) for several decades. Recently, high-throughput data on nearby chemical contacts between and within chromosomes became available with the Hi-C method. Here, we present FisHiCal, an R package for an iterative FISH-based Hi-C calibration that exploits in full the information coming from these methods. We describe here our calibration model and present 3D inference methods that we have developed for increasing its usability, namely, 3D reconstruction through local stress minimization and detection of spatial inconsistencies. We next confirm our calibration across three human cell lines and explain how the output of our methods could inform our model, defining an iterative calibration pipeline, with applications for quality assessment and meta-analysis. AVAILABILITY AND IMPLEMENTATION: FisHiCal v1.1 is available from http://cran.r-project.org/. Yoli Shavit, Fiona Kathryn Hamey, Pietro Liò |
Bioinform. | 2 |