CCPA: cloud-based, self-learning modules for consensus pathway analysis using GO, KEGG and Reactome

H Nguyen, VD Pham, H Nguyen, B Tran… - Briefings in …, 2024 - academic.oup.com
This manuscript describes the development of a resource module that is part of a learning
platform named 'NIGMS Sandbox for Cloud-based Learning'(https://github …

Alleviating batch effects in cell type deconvolution with SCCAF-D

S Feng, L Huang, AV Pournara, Z Huang… - Nature …, 2024 - nature.com
Cell type deconvolution methods can impute cell proportions from bulk transcriptomics data,
revealing changes in disease progression or organ development. But benchmarking studies …

DeSide: A unified deep learning approach for cellular deconvolution of tumor microenvironment

X ** human brain through computational modeling
MS Zarzor, Q Ma, M Almurey, B Kainz, S Budday - Scientific Reports, 2024 - nature.com
The human brain's distinctive folding pattern has attracted the attention of researchers from
different fields. Neuroscientists have provided insights into the role of four fundamental cell …

Identifying representative sequences of protein families using submodular optimization

H Nguyen, H Nguyen, P Nguyen, AN Luu, DC Cantu… - Scientific Reports, 2025 - nature.com
Identifying representative sequences for groups of functionally similar proteins and enzymes
poses significant computational challenges. In this study, we applied submodular …

A protocol for loading Calcein-AM into extracellular vesicles from mammalian cells for clear visualization with a fluorescence microscope coupled to a deconvolution …

MA Calderón-Peláez, JE Castellanos… - PloS one, 2025 - journals.plos.org
Extracellular vesicles (EVs) are membrane-bound structures produced and released into the
extracellular space by all types of cells. Due to their characteristics, EVs play crucial roles in …

Benchmarking second-generation methods for cell-type deconvolution of transcriptomic data

A Dietrich, L Merotto, K Pelz, B Eder, C Zackl… - bioRxiv, 2024 - biorxiv.org
In silico cell-type deconvolution from bulk transcriptomics data is a powerful technique to
gain insights into the cellular composition of complex tissues. While first-generation methods …

[HTML][HTML] Epigenomic, cistromic, and transcriptomic profiling of primary kidney tubular cells

Z Liu, L Zhang, Y Chen - Journal of Biological Methods, 2024 - pmc.ncbi.nlm.nih.gov
Spatiotemporal regulation of gene expression is essential for maintaining cellular
homeostasis throughout kidney development and disease progression. Transcription factors …

DECOMICS, a shiny application for unsupervised cell type deconvolution and biological interpretation of bulk omic data

S Karkar, A Sharma, C Herrmann, Y Blum… - Bioinformatics …, 2024 - academic.oup.com
Unsupervised deconvolution algorithms are often used to estimate cell composition from
bulk tissue samples. However, applying cell-type deconvolution and interpreting the results …