Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

GSVA score reveals molecular signatures from transcriptomes for biomaterials comparison.

Journal of biomedical materials research. Part A - 1 Jun 2021

Ferreira Marcel R, Santos Gerson A, Biagi Carlos A, Silva Junior Wilson A, Zambuzzi Willian F

Abstract excerpt

Two in silico methodologies were implemented to reveal the molecular signatures of inorganic hydroxyapatite and β-TCP materials from a transcriptome database to compare biomaterials. To test this new methodology, we choose the array E-MTAB-7219, which contains the transcription profile of osteoblastic cell line seeded onto 15 different biomaterials up to 48 hr. The expansive potential of the methodology was...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Biocompatible Materials
Share to Computer Simulation

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Durapatite

Share to Materials Testing

Share to Osteoblasts

Share to Polystyrenes

Share to Titanium

Share to Transcriptome

Source

Identifiers

PMID: 32820608
DOI: 10.1002/jbm.a.37090

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

GSVA score reveals molecular signatures from transcriptomes for biomaterials comparison.PMID 32820608Read ↗

Cluster analysis and gene expression profiles: A cDNA microarray system-based comparison between human dental pulp stem cells (hDPSCs) and human mesenchymal stem cells (hMSCs) for tissue engineering cell therapySemantic proximity Read ↗

Similar, but not the same: multi-omics comparison of human valve interstitial cells and osteoblast osteogenic differentiation expanded with an estimation of data-dependent and data-independent PASEFSemantic proximity Read ↗

Transcriptome analysis of human peri-implant soft tissue and periodontal gingiva: a paired design studySemantic proximity Read ↗

Measuring consistency among gene set analysis methods: A systematic study.Semantic proximity Read ↗

Characterizing the Macrophage Response to Immunomodulatory Biomaterials Through Gene Set Analyses.Semantic proximity Read ↗

Identifying the best reference gene for RT-qPCR analyses of the three-dimensional osteogenic differentiation of human-induced pluripotent stem cellsSemantic proximity Read ↗

Gene expression signatures of a fibroblastoid preosteoblast and cuboidal osteoblast cell model compared to the MLO-Y4 osteocyte cell modelSemantic proximity Read ↗

Recommendations for improving accuracy of gene expression data in bone and cartilage tissue engineeringSemantic proximity Read ↗

On the correlation between material-induced cell shape and phenotypical response of human mesenchymal stem cells.Semantic proximity Read ↗

Assessing Biomaterial‐Induced Stem Cell Lineage Fate by Machine Learning‐Based Artificial IntelligenceSemantic proximity Read ↗

Differential and Interactive Effects of Substrate Topography and Chemistry on Human Mesenchymal Stem Cell Gene ExpressionSemantic proximity Read ↗

On the correlation between material-induced cell shape and phenotypical response of human mesenchymal stem cellsSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.