Closed Physalia86 closed 6 months ago
kozo2
commented
1 year ago Hi @Physalia86 , I’m sorry for the late reply. I added your event to the Bioconductor Google Calendar https://bioconductor.org/help/events/ . I would appreciate it if you could confirm that there are no problems with the addition.
kozo2
commented
1 year ago @Physalia86 I sent a PR to update the "Upcoming" section in Bioconductor Events page (as well as the Google Calendar). https://github.com/Bioconductor/bioconductor.org/pull/241
I will message you again as soon as the PR is merged.
Type
workshop
Description
COURSE OVERVIEW This course will introduce participants with the inference and analysis of biological networks from RNA-seq data using R and Bioconductor packages. The course will cover data structures for quantitative data and graphs, statistical methods for network inference, functional analyses of biological networks, and network comparison. At the end of the course, participants will be able to infer and analyze gene coexpression networks (GCNs) and gene regulatory networks (GRNs), compare networks, and integrate GCNs with genetic markers to prioritize candidate genes associated with traits.
TARGET AUDIENCE AND ASSUMED BACKGROUND The course is targeted to researchers and students that would like to learn how to use R and Bioconductor to infer and analyze networks for systems biology projects. Familiarity with RNA-seq and core Bioconductor data structures (e.g., SummarizedExperiment and GRanges) is helpful, but not essential, as they will be covered during the course. Participants need to have a working knowledge of R (R syntax, commonly used functions, basic data structures such as data frames, vectors, matrices and their manipulation).
PROGRAM Monday - 2-7 pm Berlin time zone
Inference and Analysis of Gene Co-expression Networks (GCNs)
Theory: ● Types of networks ● Topological properties of biological networks ● Representing data as graphs ● Bias correction in co-expression network inference
Practice: ● Quantitative data and the SummarizedExperiment class ● Preprocessing, normalization, and transformation of expression data ● Inference of co-expression networks ● Functional analyses of network modules ● Network visualization
Tuesday- 2-7 pm Berlin time zone
Network comparison
Theory: ● Parametric and non-parametric network comparison ● Cross-species network comparison
Practice: ● Identifying consensus modules ● Identification preserved modules between networks ● Functional analyses of differences and similarities between networks
Wednesday - 2-7 pm Berlin time zone
Network-based data integration for gene discovery
Theory: ● Introduction to genome-wide association studies ● Bottlenecks in SNP-to-gene mapping
Practice: ● The GRanges class ● SNP-to-gene mapping ● Prioritizing candidate genes associated with a phenotype
Thursday - 2-7 pm Berlin time zone
Inference and Analysis of Gene Regulatory Networks (GRNs)
Theory: ● An overview of GRN inference algorithms ● GRN inference through an ensemble of methods ● GRN analyses and applications
Practice: ● Inference of GRNs ● Functional analyses of GRNs ● GRN visualization
Location
online
Website
https://www.physalia-courses.org/courses-workshops/network-in-systems-biology/
Start date and time
September 11th 2-7 pm
End date and time
September 14th 2-7 pm
Time zone
CEST
Contact Details
info@physalia-courses.org
Registration details (if applicable)
No response
Sponsor or Organization
Sponsor or organization
Comment field
No response
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