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Mikhail Spivakov

dblp:184/4791 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2019
0000-0002-0383-3943ORCID · corroborated

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

Applied, interdisciplinary, general and emerging computing · 2

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
2 papers
Bioinformatics and computational biology · 100%
Computer graphics and multimedia
1 paper
Visualization and visual analytics · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › epigenomics
chromatin interaction analysis
0.212016
CHiCP: a web-based tool for the integrative and interactive visualization of promoter capture Hi-C datasets · Bioinform. 2016
Bioinformatics and computational biology
genomics
0.212016
CHiCP: a web-based tool for the integrative and interactive visualization of promoter capture Hi-C datasets · Bioinform. 2016
Visualization and visual analytics › biological data visualization
genomic data visualization
0.112016
CHiCP: a web-based tool for the integrative and interactive visualization of promoter capture Hi-C datasets · Bioinform. 2016

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

interactive visualization · 0.5normalization · 0.4multiple testing · 0.4differential testing · 0.4
YearPublicationVenuePosition
2019 Chicdiff: a computational pipeline for detecting differential chromosomal interactions in Capture Hi-C data
abstract
SUMMARY: Capture Hi-C is a powerful approach for detecting chromosomal interactions involving, at least on one end, DNA regions of interest, such as gene promoters. We present Chicdiff, an R package for robust detection of differential interactions in Capture Hi-C data. Chicdiff enhances a state-of-the-art differential testing approach for count data with bespoke normalization and multiple testing procedures that account for specific statistical properties of Capture Hi-C. We validate Chicdiff on published Promoter Capture Hi-C data in human Monocytes and CD4+ T cells, identifying multitudes of cell type-specific interactions, and confirming the overall positive association between promoter interactions and gene expression. AVAILABILITY AND IMPLEMENTATION: Chicdiff is implemented as an R package that is publicly available at https://github.com/RegulatoryGenomicsGroup/chicdiff. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Jonathan M. Cairns, William R. Orchard, Valeriya Malysheva, Mikhail Spivakov
Bioinform.4
2016 CHiCP: a web-based tool for the integrative and interactive visualization of promoter capture Hi-C datasets
abstract
UNLABELLED: Promoter capture Hi-C (PCHi-C) allows the genome-wide interrogation of physical interactions between distal DNA regulatory elements and gene promoters in multiple tissue contexts. Visual integration of the resultant chromosome interaction maps with other sources of genomic annotations can provide insight into underlying regulatory mechanisms. We have developed Capture HiC Plotter (CHiCP), a web-based tool that allows interactive exploration of PCHi-C interaction maps and integration with both public and user-defined genomic datasets. AVAILABILITY AND IMPLEMENTATION: CHiCP is freely accessible from www.chicp.org and supports most major HTML5 compliant web browsers. Full source code and installation instructions are available from http://github.com/D-I-L/django-chicp CONTACT: [email protected].
E. C. Schofield, Tim J. Carver, Premanand Achuthan, P. Freire-Pritchett, Mikhail Spivakov, John A. Todd, Oliver S. Burren
Bioinform.5