GRAFT: a graph-aware fusion transformer for cancer driver gene prediction
Abstract Identifying cancer driver genes is essential for precision oncology, but existing computational methods are often limited by their reliance…
3D oncoPPI networks
Target Mapping in Cancer: Ligandable Protein Pockets on 3D OncoPPI Networks
Abstract Background/Objectives: Studying protein–protein interaction (PPI) networks is crucial in understanding cancer phenotypes and molecular mechanisms. Here, we focus on…
Learning to estimate sample-specific transcriptional networks for 7,000 tumors
Abstract Network estimation is essential for understanding the structure and function of biological systems, but current statistical approaches fail to…
Tumor tissue-of-origin classification using miRNA-mRNA-lncRNA interaction networks and machine learning methods
Abstract Introduction: MicroRNAs (miRNAs) regulate gene expression and play an important role in carcinogenesis through complex interactions with messenger RNAs…
Assessing RNA-Seq Workflow Methodologies Using Shannon Entropy
Abstract Simple Summary: We show how the relationship between the sub-network entropy of malignant up-regulated genes in twelve different types…
Identification of key genes and therapeutic drugs for cocaine addiction using integrated bioinformatics analysis
Abstract Introduction: Cocaine is a highly addictive drug that is abused due to its excitatory effect on the central nervous…
CMTCN: a web tool for investigating cancer-specific microRNA and transcription factor co-regulatory networks
Abstract Transcription factors (TFs) and microRNAs (miRNAs) are well-characterized trans-acting essential players in gene expression regulation. Growing evidence indicates that…