Statistical Methods in Bioinformatics
Zheng, G. Publishing With Us. Book Authors Journal Authors. Statistics for Biology and Health. Statistics for Biology and Health SBH includes monographs and advanced textbooks on statistical topics relating to biostatistics, epidemiology, biology, and ecology. Share this. Titles in this series.
- statistical methods in bioinformatics;
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- Statistical Methods in Bioinformatics - An Introduction | Warren J. Ewens | Springer.
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Refine Search. Content Type. Release Date. Showing 74 results. Textbook Epidemiology Krickeberg, K. Statistical methods are presented with a focus ….
Bioinformatics - Wikipedia
Data analysts …. Ed This book serves as a reference text for regulatory, industry and academic statisticians and also a handy manual for entry level Statisticians.
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Additionally it aims to stimulate …. Using …. Ed This edited volume is a definitive text on adaptive clinical trial designs from creation and customization to utilization. As this book covers the full spectrum of topics involved …. The mean residual life has been used for many …. By recurrent events, we …. Ed Epidemiologic Studies in Cancer Prevention and Screening is the first comprehensive overview of the evidence base for both cancer prevention and screening.
This book is directed …. We will also introduce reference sources and biological databases that can aid interpretation and will show how they can be accessed and integrated into a data analysis. Methods will be demonstrated by replicating analyses from publications and real-life gene expression data will be used in the computer labs. To encourage continued learning after the course, we will also provide an overview of available web-based courses and exercises. Knowledge: Learn important statistical and bioinformatics concepts for analysing molecular data.
Have knowledge of the specific statistical challenges associated with the analysis of high-throughput biological data. Understand some of the challenges you will face when trying to apply this knowledge to the analysis of real datasets. Skills: Be able to identify the data analysis problem and match the appropriate type of statistical method and corresponding software. Perform basic analyses of high-throughput biological data using R and Bioconductor. PhD candidates at UiO will have first priority at admission to the course. Maximum number of participants is limited by the capacity of computer lab.
Students should have passed the exam in an introductory course in statistics e. Students should have a basic understanding of molecular biology, at least roughly corresponding to university study points in molecular biology, biochemistry, or similar. The teaching will be organized as an intensive course over five full days.
There will be lectures coupled with hands-on practicals and example data analyses in the computer labs. Students will need to allow for sufficient time in advance for course preparations, which include some required reading, as well as after the course for the take-home exam. The practicals will take place in the same lecture hall as the lectures.
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Attendance will be registered. Take-home exam in the form of a comprehensive data analysis task based on a recent publication, to be submitted four weeks after completion of the course. You submit your assignment in the digital examination system Inspera. Read about how to submit your assignment. You should familiarize yourself with the rules that apply to the use of sources and citations. Read more about the grading system. It is possible to take the exam up to 3 times.
If you withdraw from the exam after the deadline or during the exam, this will be counted as an examination attempt. The course is subject to continuous evaluation. At regular intervals we also ask students to participate in a more comprehensive evaluation. How to apply. Application answer to course application. University of Oslo P. Box Blindern Oslo.