ArticleFrontiers in bioengineering and biotechnology2020
Predict New Therapeutic Drugs for Hepatocellular Carcinoma Based on Gene Mutation and Expression.
Article in Frontiers in bioengineering and biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 53 citations in OpenAlex.
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- Single-cell transcriptome analysis reveals the metabolic changes and the prognostic value of malignant hepatocyte subpopulations and predict new therapeutic agents for hepatocellular carcinoma.Frontiers in oncology · 2023Article
- Mechano-chemical and biological energetics of immobilized enzymes onto functionalized polymers and their applications.Bioengineered · 2022Review
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- Identification of Methicillin-Resistant Staphylococcus Aureus From Methicillin-Sensitive Staphylococcus Aureus and Molecular Characterization in Quanzhou, China.Frontiers in cell and developmental biology · 2021Article
- Synergistic Anticancer Strategy of Sonodynamic Therapy Combined with PI-103 Against Hepatocellular Carcinoma.Drug design, development and therapy · 2021Article
- iEnhancer-EBLSTM: Identifying Enhancers and Strengths by Ensembles of Bidirectional Long Short-Term Memory.Frontiers in genetics · 2021Article
- Artificial Intelligent Multi-Modal Point-of-Care System for Predicting Response of Transarterial Chemoembolization in Hepatocellular Carcinoma.Frontiers in bioengineering and biotechnology · 2021Article
- KK-DBP: A Multi-Feature Fusion Method for DNA-Binding Protein Identification Based on Random Forest.Frontiers in genetics · 2021Article
- Research on the Computational Prediction of Essential Genes.Frontiers in cell and developmental biology · 2021Review
- Bioinformatics Research on Drug Sensitivity Prediction.Frontiers in pharmacology · 2021Review
- NonClasGP-Pred: robust and efficient prediction of non-classically secreted proteins by integrating subset-specific optimal models of imbalanced data.Microbial genomics · 2020Article
- Prediction of Anticancer Peptides Using a Low-Dimensional Feature Model.Frontiers in bioengineering and biotechnology · 2020Article
- Predicting Gram-Positive Bacterial Protein Subcellular Location by Using Combined Features.BioMed research international · 2020Article
- Identifying Antioxidant Proteins by Using Amino Acid Composition and Protein-Protein Interactions.Frontiers in cell and developmental biology · 2020Article
- A Cancer Gene Module Mining Method Based on Bio-Network of Multi-Omics Gene Groups.Frontiers in oncology · 2020Article
- Identification and Classification of Enhancers Using Dimension Reduction Technique and Recurrent Neural Network.Computational and mathematical methods in medicine · 2020Article
- A Method for Identifying Vesicle Transport Proteins Based on LibSVM and MRMD.Computational and mathematical methods in medicine · 2020Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Hepatocellular carcinoma (HCC) is the fourth most common primary liver tumor and is an important medical problem worldwide. However, the use of current therapies for HCC is no possible to be cured, and despite numerous attempts and clinical trials, there are not so many approved targeted treatments for HCC. So, it is necessary to identify additional treatment strategies to prevent the growth of HCC tumors. We are looking for a systematic drug repositioning bioinformatics method to identify new drug candidates for the treatment of HCC, which considers not only aberrant genomic information, but also the changes of transcriptional landscapes. First, we screen the collection of HCC feature genes, i.e., kernel genes, which frequently mutated in most samples of HCC based on human mutation data. Then, the gene expression data of HCC in TCGA are combined to classify the kernel genes of HCC. Finally, the therapeutic score (
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.