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Sheikh Nizamuddin

dblp:425/2590 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2024
0000-0002-4586-5898ORCID · reported

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

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 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 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › epigenomics
chromatin analysis
0.812024
greenPipes: an integrated data analysis pipeline for greenCUT&RUN and CUT&RUN genome-localization datasets · Bioinform. 2024
Bioinformatics and computational biology
epigenomics
0.812024
greenPipes: an integrated data analysis pipeline for greenCUT&RUN and CUT&RUN genome-localization datasets · Bioinform. 2024

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

data integration · 0.8bioinformatic pipeline · 0.8
YearPublicationVenuePosition
2024 greenPipes: an integrated data analysis pipeline for greenCUT&RUN and CUT&RUN genome-localization datasets
abstract
MOTIVATION: To study gene regulation through transcription factors and chromatin modifiers, a variety of genome-wide techniques are used. Recently, CUT&RUN-based technologies have become popular, but a pipeline for the comprehensive analysis of CUT&RUN datasets is currently lacking. Here, we present the "greenPipes" package, which includes fine-tuned parameters specifically for bioinformatic analyses of greenCUT&RUN and CUT&RUN datasets. greenPipes provides additional functionalities for data analysis and data integration with other -omics technologies, which are either not available in other pipelines developed for CUT&RUN datasets or scattered in the literature as individual packages. AVAILABILITY AND IMPLEMENTATION: Source code and a manual of the greenPipes are freely available on GitHub website (https://github.com/snizam001/greenPipes). The test datasets, comprehensive annotation files, and other datasets are available at https://osf.io/ruhj9/. CONTACT: [email protected] or [email protected]. SUPPLEMENTARY INFORMATION: The handbook of greenPipes is available online at Bioinformatics as Supplementary text.
Sheikh Nizamuddin, H. Th. Marc Timmers
Bioinform.1