The Asia Pacific Bioinformatics Conference (APBC) series is an annual international forum for exploring research, development, and novel applications in the field of bioinformatics. The aim of APBC is to bring together academia and industry to share knowledge and experiences and to showcase innovations and achievements. It has been held since 2003 around Asia Pacific Regions.
The 21st APBC will be held in Changsha, China. The aim of this conference is to bring together researchers, academics, and industrial practitioners. APBC2023 invites high-quality original full papers on any topic related to bioinformatics and computational biology.
The goal of the Research Topic is to bring together high-quality papers that exploit the usage of innovative artificial intelligence methods that focus on the analysis of biomedical data. The central focus of the Research Topic is aligned with the theme of APBC 2023. We encourage submissions central to the theme in all areas of bioinformatics and computational biology, which are in scope for either Computational Genomics
section of Frontier in Genetics. Submission of Original Research, Review, Mini-Review, Technology, and Code articles are welcome.
The list of possible topics includes, but is not limited to:
• Single-cell sequencing data analysis
• Genome analysis
• Drug design and discovery
• Biological network analysis
• Epigenetic modification
• Biomedical text mining
• Precision medicine
• High-performance bio-computing
• DNA, RNA, Protein interactions, and diseases
For more information about the event, please access the website:http://bioinformatics.csu.edu.cn/APBC2023/index.htmlPlease note:
1. Quantitative analysis needs to be performed on a minimum number of 3 biological replicates in order to enable an assessment of significance and ensure the depth of the analysis. This includes quantitative omics studies as well as phenotypic measurements, quantitative assays, and qPCR expression analysis. Studies that do not comply with these replication requirements will not be considered for review.
2. Studies falling in the categories below will also not be considered for review unless they are extended to provide meaningful insights into gene/protein function and/or the biology of the subject described. Studies relating to the prediction of clinical outcomes require some validation of findings:
· Comparative transcriptomic analyses that only report a collection of differentially expressed genes, some validated by qPCR under different conditions or treatments;
· Re-analysis of existing genomic, and transcriptomic data which attempts to identify a candidate set of diagnostic or prognostic markers for disease.
· Descriptive studies that merely define gene families using basic phylogenetics and assign cursory functional attributions (e.g. expression profiles, hormone or metabolites levels, promoter analysis, informatic parameters).