A unified hypothesis-free feature extraction framework for diverse epigenomic data

Our approach is implemented as an R package "l01segmentation" with a C++ backend. Available at https://github.com/boooooogey/l01segmentation.

Authors

Institutions

Publication Details

Journal
Bioinformatics Advances
Published
2024-12-26
DOI
https://doi.org/10.1093/bioadv/vbaf013
Citations
2
Primary Topic
Epigenetics and DNA Methylation
Type
article
Field-Weighted Citation Impact
0.47

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A unified hypothesis-free feature extraction framework for diverse epigenomic data

Maria D. Chikina, Ali Tuğrul Balcı
2 citations
Bioinformatics Advances
Epigenetics and DNA Methylation
0.47
article

A unified hypothesis-free feature extraction framework for diverse epigenomic data

Maria D. Chikina, Ali Tuğrul Balcı
article en
2 citations

Abstract

Our approach is implemented as an R package "l01segmentation" with a C++ backend. Available at https://github.com/boooooogey/l01segmentation.

Bioinformatics AdvancesVol. 5(1)
University of Pittsburgh (US), Carnegie Mellon University (US)
National Science Foundation, National Institutes of Health
Openalex Percentile: Top 33%
Epigenetics and DNA Methylation
0.47
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.