PICASO: Profiling Integrative Communities of Aggregated Single-cell Omics data DOI Creative Commons
Markus Joppich, Rafael Kramann, Sikander Hayat

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 29, 2024

Abstract Various single-cell modalities covering transcriptomics, epigenetic and spatio-temporal changes in health disease phenotypes are used an exploratory way to understand biological systems at resolution. However, the vast amount of such data is not systematically linked existing biomedical data. Networks have previously been represent harmonized Integrating various resources networks has recently received increasing attention. These aggregated can provide additional insight into biology complex human diseases cell-type level, however, lack inclusion single cell expression Here, we present PICASO framework, which incorporates gene as layer associations between types, phenotypes, drugs genes. The network includes several standardized databases STRING, Uniprot, GeneOntology, Reactome, OmniPath OpenTargets. Using multiple type-specific instances each annotated scored with their respective data, comparisons states be made by computing sub-networks comparing scores conditions. Ultimately, these group-specific will allow identification relevant genes, processes potentially druggable targets, well comparison different measured groups thus communities interactions.

Language: Английский

Nanomechanical Characterization of Soft Nanomaterial Using Atomic Force Microscopy DOI Creative Commons

C. Lam,

Soyeun Park

Materials Today Bio, Journal Year: 2025, Volume and Issue: unknown, P. 101506 - 101506

Published: Jan. 1, 2025

Language: Английский

Citations

0
Novel insights into kidney disease: the scRNA-seq and spatial transcriptomics approaches: a literature review DOI Creative Commons

Mingming Ma,

Qiao Luo, Liangmei Chen

et al.

BMC Nephrology, Journal Year: 2025, Volume and Issue: 26(1)

Published: April 8, 2025

Language: Английский

Citations

0
Review: Single Cell Advances in investigating and understanding Chronic Kidney Disease and Diabetic Kidney Disease DOI
Sagar Bhayana, Philip Andreas Schytz, Emma T. B. Olesen

et al.

American Journal Of Pathology, Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 1, 2024

Language: Английский

Citations

1
PICASO: Profiling Integrative Communities of Aggregated Single-cell Omics data DOI Creative Commons
Markus Joppich, Rafael Kramann, Sikander Hayat

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Aug. 29, 2024

Abstract Various single-cell modalities covering transcriptomics, epigenetic and spatio-temporal changes in health disease phenotypes are used an exploratory way to understand biological systems at resolution. However, the vast amount of such data is not systematically linked existing biomedical data. Networks have previously been represent harmonized Integrating various resources networks has recently received increasing attention. These aggregated can provide additional insight into biology complex human diseases cell-type level, however, lack inclusion single cell expression Here, we present PICASO framework, which incorporates gene as layer associations between types, phenotypes, drugs genes. The network includes several standardized databases STRING, Uniprot, GeneOntology, Reactome, OmniPath OpenTargets. Using multiple type-specific instances each annotated scored with their respective data, comparisons states be made by computing sub-networks comparing scores conditions. Ultimately, these group-specific will allow identification relevant genes, processes potentially druggable targets, well comparison different measured groups thus communities interactions.

Language: Английский

Citations

1