Emerging Drug Combinations for Targeting Tongue Neoplasms Associated Proteins/Genes: Employing Graph Neural Networks within the RAIN Protocol DOI Open Access
Mohsen Askari, Ali A. Kiaei, Mahnaz Boush

et al.

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

Published: June 12, 2024

Abstract Background Tongue Neoplasms is a common form of malignancy, with squamous cell carcinoma the tongue being most frequently diagnosed type due to regular mechanical stimulation. Its prevalence remains on rise among neoplastic cancer cases. Finding effective combinations drugs target genetic and protein elements contributing development Managing poses difficulty owing intricate varied nature ailment. Method In this research, we introduce novel approach using Deep Modularity Networks (DMoN) identify potential synergistic drug for condition, following RAIN protocol. This procedure comprises three primary phases: First, employing Graph Neural Network (GNN) propose treating ailment by extracting embedding vectors proteins from an extensive knowledge graph containing various biomedical data types, such as drug-protein interactions, gene expression, drug-target interactions. Second, utilizing natural language processing gather pertinent articles clinical trials involving previously recommended drugs. Finally, conducting network meta-analysis evaluate comparative efficacy these combinations. Result We utilized our dataset genes nodes, connected edges indicating their associated p-values. Our DMoN model identified Cisplatin, Bleomycin, Fluorouracil optimal combination targeting human genes/proteins cancer. Subsequent scrutiny literature confirmed validity findings. Additionally, substantiated medications concerning genes. Conclusion Through utilization part protocol, method introduces fresh way suggest notable addressing proteins/genes linked Neoplasms. holds promise in assisting healthcare practitioners researchers pinpointing best treatments patients, well uncovering fundamental mechanisms disease. Highlights A new protocol can find Neoplasms, deadly The uses pairings large data, then searches performs compare effectiveness. discovered that are suitable involved cancer, finding review statistical analysis. offers powerful assist doctors patients understand underlying causes Figure

Language: Английский

Emerging Drug Combinations for Targeting Tongue Neoplasms Associated Proteins/Genes: Employing Graph Neural Networks within the RAIN Protocol DOI Open Access
Mohsen Askari, Ali A. Kiaei, Mahnaz Boush

et al.

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

Published: June 12, 2024

Abstract Background Tongue Neoplasms is a common form of malignancy, with squamous cell carcinoma the tongue being most frequently diagnosed type due to regular mechanical stimulation. Its prevalence remains on rise among neoplastic cancer cases. Finding effective combinations drugs target genetic and protein elements contributing development Managing poses difficulty owing intricate varied nature ailment. Method In this research, we introduce novel approach using Deep Modularity Networks (DMoN) identify potential synergistic drug for condition, following RAIN protocol. This procedure comprises three primary phases: First, employing Graph Neural Network (GNN) propose treating ailment by extracting embedding vectors proteins from an extensive knowledge graph containing various biomedical data types, such as drug-protein interactions, gene expression, drug-target interactions. Second, utilizing natural language processing gather pertinent articles clinical trials involving previously recommended drugs. Finally, conducting network meta-analysis evaluate comparative efficacy these combinations. Result We utilized our dataset genes nodes, connected edges indicating their associated p-values. Our DMoN model identified Cisplatin, Bleomycin, Fluorouracil optimal combination targeting human genes/proteins cancer. Subsequent scrutiny literature confirmed validity findings. Additionally, substantiated medications concerning genes. Conclusion Through utilization part protocol, method introduces fresh way suggest notable addressing proteins/genes linked Neoplasms. holds promise in assisting healthcare practitioners researchers pinpointing best treatments patients, well uncovering fundamental mechanisms disease. Highlights A new protocol can find Neoplasms, deadly The uses pairings large data, then searches performs compare effectiveness. discovered that are suitable involved cancer, finding review statistical analysis. offers powerful assist doctors patients understand underlying causes Figure

Language: Английский

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