Current developments is research techniques led to increase in capacity to produce extensive amounts of data within a single experiment. Contemporary challenges in biological research are related to “data-overload” and drawing conclusions from already available evidence. Recent years brought significant advancements in the field of computational analysis. Tools developed for big-data analysis and modelling, such as machine learning, Bayesian statistics, natural language processing, network analysis and visualization become more and more accessible for researchers and their use is becoming more common to answer biological questions.
The goal of this Research Topic is to highlight the possibilities arising from computational methodology. Publications in our collection should encompass tools such as data mining, modelling, big-data analysis and visualization. All used in order to tackle biological questions. System pharmacology tools can help identify novel targets. Data modelling and simulation can decrease amount of work in experimental research. Novel techniques such as single-cell or spatial transcriptomics can produce enormous amount of data, rising challenges to analysis, integration and interpretation. Showcasing novel methodological approach will help other researchers identify tools that could be applicable in their own pain pharmacology research.
We welcome the submission of manuscripts including, but not limited to, the following topics:
1. Systems pharmacology
2. PK/PD modelling
3. Transcriptomics
4. Proteomics
5. Metabolomics and metabolism modelling
6. Large-scale electrophysiology
7. Data mining and integration
8. Image processing
9. Artificial intelligence
10. And all the research that employs computational methods to gain novel biological insight from already available databases.
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.
