Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Eric Y. Stutheit-Zhao

dblp:425/2834 · DBLP profile ↗
← Back
1ranked-venue papers
0as first author
1since 2021 · last 2023
—ORCID · none

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

Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

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

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › epigenomics › DNA methylation
DNA methylation analysis
0.712023
MEDIPIPE: an automated and comprehensive pipeline for cfMeDIP-seq data quality control and analysis · Bioinform. 2023
Bioinformatics and computational biology › epigenomics › DNA methylation › DNA methylation analysis
methylation level estimation
0.212023
MEDIPIPE: an automated and comprehensive pipeline for cfMeDIP-seq data quality control and analysis · Bioinform. 2023
Bioinformatics and computational biology › sequence analysis
sequencing data analysis
0.212023
MEDIPIPE: an automated and comprehensive pipeline for cfMeDIP-seq data quality control and analysis · Bioinform. 2023

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

snakemake · 0.7conda · 0.7
YearPublicationVenuePosition
2023 MEDIPIPE: an automated and comprehensive pipeline for cfMeDIP-seq data quality control and analysis
abstract
SUMMARY: Cell-free methylated DNA immunoprecipitation and high-throughput sequencing (cfMeDIP-seq) has emerged as a promising liquid biopsy technology to detect cancers and monitor treatments. While several bioinformatics tools for DNA methylation analysis have been adapted for cfMeDIP-seq data, an end-to-end pipeline and quality control framework specifically for this data type is still lacking. Here, we present the MEDIPIPE, which provides a one-stop solution for cfMeDIP-seq data quality control, methylation quantification, and sample aggregation. The major advantages of MEDIPIPE are: (i) ease of implementation and reproducibility with Snakemake containerized execution environments that will be automatically deployed via Conda; (ii) flexibility to handle different experimental settings with a single configuration file; and (iii) computationally efficiency for large-scale cfMeDIP-seq profiling data analysis and aggregation. AVAILABILITY AND IMPLEMENTATION: This pipeline is an open-source software under the MIT license and it is freely available at https://github.com/pughlab/MEDIPIPE.
Yong Zeng 0001, Wenbin Ye 0002, Eric Y. Stutheit-Zhao, Scott V. Bratman, Trevor J. Pugh, Housheng H. He
Bioinform.3