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Sadnan Al Manir

dblp:297/4248 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2025
—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 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology › protein function prediction
protein localization
0.312025
Cell Mapping Toolkit: an end-to-end pipeline for mapping subcellular organization · Bioinform. 2025
Bioinformatics and computational biology
proteomics
0.312025
Cell Mapping Toolkit: an end-to-end pipeline for mapping subcellular organization · Bioinform. 2025

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

visualization · 0.9data integration · 0.9
YearPublicationVenuePosition
2025 Cell Mapping Toolkit: an end-to-end pipeline for mapping subcellular organization
abstract
SUMMARY: Cells are organized as a hierarchy of macromolecular assemblies, ranging from small protein complexes to entire organelles. Various technologies have been developed to elucidate subcellular architecture at different scales, such as mass spectrometry approaches for mapping protein biophysical interactions and immunofluorescence imaging for mapping protein localization. We present the Cell Mapping Toolkit, which is designed to systematically integrate data from different modalities into unified hierarchical maps of subcellular organization. The toolkit facilitates an end-to-end pipeline including processing datasets, integrating modalities, and visualizing the final cell map with rich metadata including provenance documentation at each step. The Cell Mapping Toolkit provides researchers with tools for analyzing, integrating, and visualizing diverse protein datasets in a robust and reproducible framework. AVAILABILITY AND IMPLEMENTATION: The code is freely available and is hosted on GitHub at https://github.com/idekerlab/cellmaps_pipeline. Comprehensive documentation and practical examples are provided at https://cellmaps-pipeline.readthedocs.io/.
Joanna Lenkiewicz, Christopher Churas, Mengzhou Hu, Gege Qian, Maxwell Adam Levinson, Sadnan Al Manir, Dylan Fong, Keiichiro Ono, Chengzhan Gao, Dexter Pratt, Jillian Parker, Tim Clark, Trey Ideker, Leah V. Schaffer
Bioinform.7