transcriptomic reference dataset Search Results


reference transcriptome dataset  (Human Protein Atlas)
86
Human Protein Atlas reference transcriptome dataset
The schema of TransPilot server. (A) LLR-matrix coding for positive training nucleotide sequences. (B) LLR-matrix coding for negative training nucleotide sequences. (C) The ANN model and creation of the ranked and directed TF-target dataset. (D) Creation of ranked gene list from <t>transcriptome</t> data, identification of key TFs by TransPilot, and finally build the regulation network.
Reference Transcriptome Dataset, supplied by Human Protein Atlas, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/transcriptomic+reference+dataset/dataset+reference+transcriptome/pmc13249498-68-40-46
Average 86 stars, based on 1 article reviews
reference transcriptome dataset - by Bioz Stars, 2026-10
86/100 stars
  Buy from Supplier
reference transcriptomic datasets  (Celldex Inc)
86
Celldex Inc reference transcriptomic datasets
The schema of TransPilot server. (A) LLR-matrix coding for positive training nucleotide sequences. (B) LLR-matrix coding for negative training nucleotide sequences. (C) The ANN model and creation of the ranked and directed TF-target dataset. (D) Creation of ranked gene list from <t>transcriptome</t> data, identification of key TFs by TransPilot, and finally build the regulation network.
Reference Transcriptomic Datasets, supplied by Celldex Inc, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/transcriptomic+reference+dataset/datasets+reference+transcriptomic/pmc12956523-75-6-12
Average 86 stars, based on 1 article reviews
reference transcriptomic datasets - by Bioz Stars, 2026-10
86/100 stars
  Buy from Supplier

Image Search Results


The schema of TransPilot server. (A) LLR-matrix coding for positive training nucleotide sequences. (B) LLR-matrix coding for negative training nucleotide sequences. (C) The ANN model and creation of the ranked and directed TF-target dataset. (D) Creation of ranked gene list from transcriptome data, identification of key TFs by TransPilot, and finally build the regulation network.

Journal: Bioinformatics Advances

Article Title: TransPilot: mining key transcription factors by correlating binding sites with differentially expressed genes

doi: 10.1093/bioadv/vbag145

Figure Lengend Snippet: The schema of TransPilot server. (A) LLR-matrix coding for positive training nucleotide sequences. (B) LLR-matrix coding for negative training nucleotide sequences. (C) The ANN model and creation of the ranked and directed TF-target dataset. (D) Creation of ranked gene list from transcriptome data, identification of key TFs by TransPilot, and finally build the regulation network.

Article Snippet: The TF-target pairs were ranked by the ANN score ( Y ANN , > 0.5) and the directions (positive or negative) of the regulatory relationships for each pair were determined by the correlation coefficient between their expression levels in a reference transcriptome dataset obtained from the Human Protein Atlas database ( Uhlén et al. 2015 ).

Techniques: