Using Big Data to Discover Diagnostics and Therapeutics for Gastrointestinal and Liver Diseases
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Summary
Recent advances in the fields of computational and systems biology are reviewed, and opportunities for researchers to use big data sets in the fields of gastroenterology and hepatology, to complement traditional means of diagnostic and therapeutic discovery are highlighted.
- Type
- review
- Published
- 2016-10-20
- Cited by
- 55
- References
- 138
- Access
- Open access
- OpenAlex
- https://openalex.org/W2536723267
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:206243887
Keywords
Big data, Computational biology, Profiling (computer programming), Translational bioinformatics, Systems biology
References
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- Second act
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- Network-Based Elucidation of Human Disease Similarities Reveals Common Functional Modules Enriched for Pluripotent Drug Targets
- Gene Expression Signature Analysis Identifies Vorinostat as a Candidate Therapy for Gastric Cancer
- PolySearch2: a significantly improved text-mining system for discovering associations between human diseases, genes, drugs, metabolites, toxins and more
- Graph Theory Enables Drug Repurposing – How a Mathematical Model Can Drive the Discovery of Hidden Mechanisms of Action
Cited by
- Transcriptome-based repurposing of apigenin as a potential anti-fibrotic agent targeting hepatic stellate cells
- Translational Aspects of Diet and Non-Alcoholic Fatty Liver Disease
- Survey: Big Data Application in Biomedical Research
- Big Data’s Role in Precision Public Health
- Upper Respiratory Symptoms, Gut Health and Mucosal Immunity in Athletes
- Big Data and Data-Driven Healthcare Systems
- Mechanisms of NAFLD development and therapeutic strategies
- Chronic Liver Disease Classification Using Hybrid Whale Optimization with Simulated Annealing and Ensemble Classifier
- Big data in IBD: a look into the future
- Complementing preclinical safety assessments through genomic analyses
- MoDeSuS: A Machine Learning Tool for Selection of Molecular Descriptors in QSAR Studies Applied to Molecular Informatics
- Big Data Analytics in Healthcare Systems
- Random gene sets in predicting survival of patients with hepatocellular carcinoma
- GIDB: a knowledge database for the automated curation and multidimensional analysis of molecular signatures in gastrointestinal cancer
- In Silico Toxicology Data Resources to Support Read-Across and (Q)SAR
- The "Red Queen" Is Up and Running: Virus-Host Interactions Revealed Through the Prism of Multiomics.
- Harnessing big ‘omics’ data and AI for drug discovery in hepatocellular carcinoma
- Advancements in genomic medicine and the need for updated regional clinical practice guidelines in the field of hepatology.
- Limitations of non-invasive tests for assessment of liver fibrosis
- SEPSIS. Educational and Best Practice Frontiers. Beyond the Boundaries of Fatality, Enhancing Clinical Skills and Precision Medicine
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