FMB,单细胞,12.9截稿
https://www.frontiersin.org/research-topics/44713/innovative-artificial-intelligence-for-single-cell-analysis-network-research
尤编辑
FP,药物,11.5截稿
https://www.frontiersin.org/research-topics/43466/artificial-intelligence-and-machine-learning-for-drug-discovery-design-and-repurposing-methods-and-a
Artificial Intelligence and Machine Learning for Drug Discovery, Design and Repurposing: Methods and Applications
FG, 单细胞/药物,11.12截稿
https://www.frontiersin.org/research-topics/41755/machine-learning-methods-in-single-cell-immune-and-drug-response-prediction
Machine Learning Methods in Single-Cell Immune and Drug Response Prediction
CIBM,植物基因组,9.30截稿
https://www.mdpi.com/journal/cimb/special_issues/Comparative_Genomics
Special Issue "Functional Genomics and Comparative Genomics Analysis in Plants"
FM,5.31截稿,Phage Display: Technique and Applications
https://www.frontiersin.org/research-topics/28416/phage-display-technique-and-applications
黄编辑
FG,计算基因组, 7.13截稿
Insights in Computational Genomics: 2022
https://www.frontiersin.org/research-topics/35371/insights-in-computational-genomics-2022
FG,生物序列机器学习,7.20截稿
https://www.frontiersin.org/research-topics/35530/machine-learning-for-biological-sequence-analysis
Machine Learning For Biological Sequence Analysis
Applied Sciences,生信的进化计算,1.31截稿
https://www.mdpi.com/journal/applsci/special_issues/Evolutionary_Computing_Bioinformatics
Evolutionary Bioinformatics,6月20日截稿
Special Collection on Deep Learning in Biological Sequence Functional Analysis
https://journals.sagepub.com/page/evb/collections/special-collections/deep-learning-biological-sequence-functional-analysis
IJMS,生物医学信息处理,7.31截稿
Special Issue "Current Artificial Intelligence Approaches in Biomedical Information Processing"
https://www.mdpi.com/journal/ijms/special_issues/Artificial_Intelligence_Biomedical
MBE, 深度学习应用于生物序列分析,2022年11月30
http://www.aimspress.com/mbe/article/6127/special-articles
魏编辑
FG,3.7截稿,蛋白亚细胞
https://www.frontiersin.org/research-topics/26181/computational-analysis-of-protein-subcellular-localizations-detection-prediction-and-diseases
Computational Analysis of Protein Subcellular Localizations: Detection, Prediction and Diseases.
FPS, 5.5截稿,植物机器学习
Machine learning on understanding the epigenetic mechanisms underlying plant adaptation and domestication
https://www.frontiersin.org/research-topics/31048/machine-learning-on-understanding-the-epigenetic-mechanisms-underlying-plant-adaptation-and-domestic
FN, 3.29截稿,神经疾病
Data-driven Clinical Biosignatures and Treatment for Neurodegenerative Diseases
https://www.frontiersin.org/research-topics/26176/data-driven-clinical-biosignatures-and-treatment-for-neurodegenerative-diseases?utm_source=F-RTM&utm_medium=CFP_E1&utm_campaign=PRD_CFP_T1_RT-TITLE
陈编辑
FMB,二区,微生物组,5.27截稿
https://www.frontiersin.org/research-topics/28565/volume-ii-computational-solutions-for-microbiome-and-metagenomics-sequencing-analyses?utm_source=F-RTM&utm_medium=CFP_E1&utm_campaign=PRD_CFP_T1_RT-TITLE
Volume II: Computational Solutions for Microbiome and Metagenomics Sequencing Analyses
魏编辑 ...
CMMM, 3.18截稿. 生物序列预测
https://www.hindawi.com/journals/cmmm/si/395841/
Artificial Intelligence for Biological Sequence and Functional Analysis
Genes, 生物网络, 8.25截稿
https://www.mdpi.com/journal/genes/special_issues/Potential_Links_Biomedical_Networks
Special Issue "Identification of Potential Links in Biomedical Networks"
FG,深度学习医学图像,3.16截稿
https://www.frontiersin.org/research-topics/25580/application-of-deep-learning-techniques-in-3d-biomedical-and-clinical-images
Application of Deep Learning Techniques in 3D Biomedical and Clinical Images
魏编辑
FG, 单细胞,2.17截稿
https://www.frontiersin.org/research-topics/28070/bioinformatics-analysis-of-single-cell-sequencing-data-and-applications-in-precision-medicine-volume?utm_source=F-RTM&utm_medium=CFP_E2&utm_campaign=PRD_CFP_T1_RT-TITLE
Bioinformatics Analysis of Single Cell Sequencing Data and Applications in Preci ...
FG,2月28截稿,我是编辑
https://www.frontiersin.org/research-topics/20222/machine-learning-techniques-on-gene-function-prediction-volume-ii
Machine Learning Techniques on Gene Function Prediction Volume II