About this Research Topic
This research topic aims to bring state-of-the-art research contributions in machine intelligence to address new problems and improve over existing tasks using single-cell data. Submitted articles will be evaluated based on their quality and relevance to the research topic.
Accordingly, we welcome machine-intelligence related submissions, but not limited to the following:
· Data-Driven Approaches Based on Tensor Data
· Supervised Tensor Learning
· Semi-Supervised Tensor Learning
· Deep Learning
· Machine Learning
Re-analysis of existing genomic, transcriptomic data which attempts to identify a candidate set of diagnostic or prognostic markers for disease will not be considered for review, unless they are either (1) provided via novel machine intelligence methods or (2) extended to provide meaningful insights into gene/protein function and/or the biology of the subject described. Studies relating to the prediction of clinical outcome require some validation of findings
Keywords: Single-Cell Data, Cellular Biology, Tensor Data, Machine Learning, Artificial Intelligence
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.