To cultivate talents with an exploratory spirit and practical skills in the era of information technology,it is imperative to reform teaching methods and approaches.In the teaching process of the Probability and Stati...To cultivate talents with an exploratory spirit and practical skills in the era of information technology,it is imperative to reform teaching methods and approaches.In the teaching process of the Probability and Statistics course,an application-oriented blended teaching model combining problem-based learning and small private online course was explored.By organizing and implementing online and offline teaching activities based on problem-based learning,a multidimensional process-oriented learning assessment system was established.Practice has shown that this model can effectively enhance classroom teaching effectiveness,benefiting the improvement of students’overall skills and mathematical literacy.展开更多
Background:The past decade has witnessed a rapid progress in our understanding of the genetics of cancer and its progression.Probabilistic and statistical modeling played a pivotal role in the discovery of general pat...Background:The past decade has witnessed a rapid progress in our understanding of the genetics of cancer and its progression.Probabilistic and statistical modeling played a pivotal role in the discovery of general patterns from cancer genomics datasets and continue to be of central importance for personalized medicine.Results:In this review we introduce cancer genomics from a probabilistic and statistical perspective.We start from(1)functional classification of genes into oncogenes and tumor suppressor genes,then(2)demonstrate the importance of comprehensive analysis of different mutation types for individual cancer genomes,followed by(3)tumor purity analysis,which in turn leads to(4)the concept of ploidy and clonality,that is next connected to(5)tumor evolution under treatment pressure,which yields insights into cancer drug resistance.We also discuss future challenges including the non-coding genomic regions,integrative analysis of genomics and epigenomics,as well as early cancer detection.Conclusion:We believe probabilistic and statistical modeling will continue to play important roles for novel discoveries in the field o f cancer genomics and personalized medicine.展开更多
基金2023 Quality Engineering Project of Guangzhou City Polytechnic“Research on Process Assessment Mode of‘Probability Theory and Mathematical Statistics’Course Based on Application Ability Cultivation”(JY230140)2024 Quality Engineering Project of Guangzhou City Polytechnic“Exploration and Practice of Teaching Model Based on PBL+SPOC+Flipped Classroom in‘Probability Theory and Mathematical Statistics’”(J1124030)。
文摘To cultivate talents with an exploratory spirit and practical skills in the era of information technology,it is imperative to reform teaching methods and approaches.In the teaching process of the Probability and Statistics course,an application-oriented blended teaching model combining problem-based learning and small private online course was explored.By organizing and implementing online and offline teaching activities based on problem-based learning,a multidimensional process-oriented learning assessment system was established.Practice has shown that this model can effectively enhance classroom teaching effectiveness,benefiting the improvement of students’overall skills and mathematical literacy.
文摘Background:The past decade has witnessed a rapid progress in our understanding of the genetics of cancer and its progression.Probabilistic and statistical modeling played a pivotal role in the discovery of general patterns from cancer genomics datasets and continue to be of central importance for personalized medicine.Results:In this review we introduce cancer genomics from a probabilistic and statistical perspective.We start from(1)functional classification of genes into oncogenes and tumor suppressor genes,then(2)demonstrate the importance of comprehensive analysis of different mutation types for individual cancer genomes,followed by(3)tumor purity analysis,which in turn leads to(4)the concept of ploidy and clonality,that is next connected to(5)tumor evolution under treatment pressure,which yields insights into cancer drug resistance.We also discuss future challenges including the non-coding genomic regions,integrative analysis of genomics and epigenomics,as well as early cancer detection.Conclusion:We believe probabilistic and statistical modeling will continue to play important roles for novel discoveries in the field o f cancer genomics and personalized medicine.
