About this Research Topic
Artificial Intelligence (AI) has shown its capability and prevailed in many science and engineering fields including computational systems biology. Conventionally, computational biology works on problems of biology systems at all levels, which involve individual organisms, internal biological subsystems, cells, membranes, DNAs and relevant external ecosystems, with mathematical modelling and statistical analysis. Bioinformatics and Genomics are two very related areas of computational systems biology, in which AI can exercise its full potential. Compared to conventional computational approaches, AI offers an advanced toolbox that better facilitates problem-solving in the fields. The current trend in AI methods in bioinformatics and genomics is machine learning methods, i.e., creating more efficient, reliable and accurate neural networks and deep learning models. Nevertheless, AI methods are not limited to those. In practice, Artificial Intelligence can be used to examine molecular structures and classify biological data. Research work using AI has been also found in function-structure analysis, biological/gene sequence matching, protein-protein interaction and many more.
Bioinformatics and genomics usually possess and produce a vast amount of data, deal with numerous business-critical tasks and bear high social-economical values to society. The Research Topic aims to receive studies that reflect and address the latest advancements in AI methods that focus on the challenges in bioinformatics and genomics. Particular emphasis is placed on novel and intelligent methods tackling the practical issues in the area.
The Research Topic is interested in the work of the following topics (not limited to)
• DNA, RNA and gene data analytics,
• DNA computing
• Gene structuring and restructuring
• Gene matching
• Gene function analysis
• Gene expression regulations
• Transcriptomics analysis
• Biological feature extraction and prediction
• Next-generation sequencing
• Protein data processing
• Omics data integration
• AI applications in drug development
Bioinformatics and genomics usually possess and produce a vast amount of data, deal with numerous business-critical tasks and bear high social-economical values to society. The Research Topic aims to receive studies that reflect and address the latest advancements in AI methods that focus on the challenges in bioinformatics and genomics. Particular emphasis is placed on novel and intelligent methods tackling the practical issues in the area.
The Research Topic is interested in the work of the following topics (not limited to)
• DNA, RNA and gene data analytics,
• DNA computing
• Gene structuring and restructuring
• Gene matching
• Gene function analysis
• Gene expression regulations
• Transcriptomics analysis
• Biological feature extraction and prediction
• Next-generation sequencing
• Protein data processing
• Omics data integration
• AI applications in drug development
Keywords: AI for bioinformatics, Genomics, Machine Learning in bioanalytics, DNA computing, big biodata, graph neural networks, AI-driven drug design
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
