Principles of Machine Learning for Bioinformatics
This four-day course will introduce a selection of machine learning methods used in bioinformatic analyses with a focus on RNA-seq gene expression data. We will cover unsupervised learning, dimensionality reduction and clustering; feature selection and extraction; and supervised learning methods for classification (e.g., random forests, SVM, LDA, kNN, etc.) and regression (with an emphasis on regularization methods appropriate for high-dimensional problems). Participants will have the opportunity to apply these methods as implemented in R and python to publicly available data.
Preferred or Prerequisite Skills:
This course is recommended for students with some prior knowledge of either R or python. Participants are expected to provide their own laptops with recent versions of R and/or python installed. Students will be instructed to download several free software packages (including R packages and python libraries including pandas and sklearn).
Computer Requirement:
Students should have their own laptop computer. UT EID is required for wireless access. Please be sure you know your UT EID when you come to class. To obtain a UT EID, go here.
CB25038
Instructor
Dennis Wylie (Co-Director, Bioinformatics Consulting Group, CBRS)
Dennis Wylie joined the Bioinformatics group in 2015. He has experience in NGS data analysis including variant calling and RNA-Seq-based biomarker discovery and predictive modeling (classification, regression, etc.). Prior to UT, he earned a PhD in Biophysics from UC Berkeley applying stochastic simulation methods to problems in immunology, did postdoctoral work modeling the transmission of infectious disease, and spent six years as a bioinformatician in industry.
Status
Closed
Modality
Hybrid
Course Closes
Thu, Jun 12
Procard Disclaimer
If you use the UT ProCard for payment of courses, please be aware that you can only charge ONCE per 24 hour period. Any attempts to charge more courses will fail, and you will not be registered.
For example, you may add one to many courses for one student into your shopping cart at any one time, and charge them to the ProCard, and you should receive a "registration successful!" page at the end. This is because you registered ONCE for ONE student. If you attempt to register and pay again, for example, for a different student, this will trigger the UT ProCard security system to stop payment, and your registration will not be successful. A page stating this fact will occur after you attempt to process payment. It looks a lot like the "registration was successful" page.
Ways to avoid this are: use the ProCard after 24 hours have passed, or the student may use their credit card and be reimbursed later through the usual UT accounting methods, or process the registration with an IDT, otherwise known as an Interdepartmental Transfer (talk to someone in your department that handles the accounts).
Course Semester
Course Type
June 16 - June 20 (no class on June 19)
Start Date
9:00 am - 12:00 pm
Introduction to RNA-Seq
This five-day course provides an introduction to methods for analysis of RNA-seq data. It assumes familiarity and comfort with Linux command line. A typical RNA-seq workflow will be featured, starting from quality assessment of raw data, mapping (bwa, kallisto), differential expression analysis (DESeq2), and downstream analyses and visualization. The course also describes analysis methods for dealing with single-cell RNA-Seq data. Participants will gain hands-on experience using these tools in a Linux command line environment.
Preferred or Prerequisite Skills:
Familiarity working in a UNIX environment. Consider taking the “Introduction to Biocomputing” or “Introduction to Core NGS Concepts and Tools” summer school course to refresh your UNIX skills.
Computer Requirement:
Students should have their own laptop computer. UT EID is required for wireless access on campus. Please be sure you know your UT EID when you come to class. To obtain a UT EID, go here.
CB25037
Instructor
Dhivya Arasappan (Co-Director, Bioinformatics Consulting Group, CBRS)
Dhivya Arasappan has 15 years experience analyzing NGS data from multiple platforms: Illumina, PacBio and SOLiD. Her areas of expertise include: de novo genome assembly, particularly using hybrid sequencing data, RNA-Seq analysis, exome analysis, and benchmarking of bioinformatics tools. She is the research educator for the Big Data in Biology Freshman Research Initiative stream and teaches an RNA-Seq course as part of the Summer School for Big Data in Biology.
Status
Open
Modality
Hybrid, but in-person encouraged
Course Closes
Wed, Jun 04
Procard Disclaimer
If you use the UT ProCard for payment of courses, please be aware that you can only charge ONCE per 24 hour period. Any attempts to charge more courses will fail, and you will not be registered.
For example, you may add one to many courses for one student into your shopping cart at any one time, and charge them to the ProCard, and you should receive a "registration successful!" page at the end. This is because you registered ONCE for ONE student. If you attempt to register and pay again, for example, for a different student, this will trigger the UT ProCard security system to stop payment, and your registration will not be successful. A page stating this fact will occur after you attempt to process payment. It looks a lot like the "registration was successful" page.
Ways to avoid this are: use the ProCard after 24 hours have passed, or the student may use their credit card and be reimbursed later through the usual UT accounting methods, or process the registration with an IDT, otherwise known as an Interdepartmental Transfer (talk to someone in your department that handles the accounts).
Course Semester
Course Type
June 9 - June 13
Start Date
1:00 pm - 4:00 pm
Introduction to Python
This five-day course will introduce students to basic concepts in programming using the Python language, establishing a foundation for scientific computing. Trainees will learn introductory topics such as data structures, control flow, functions, file input/output, and data parsing. The class will work with SciPy libraries like Pandas. Trainees will have full access to the teacher’s course book and course content (datasets, scripts, and jupyter notebooks).
Preferred or Prerequisite Skills:
None
Computer Requirement:
This class is offered in-person. Students must provide laptops able to connect to the internet, and a Firefox or Chrome browser. UT EID is required for wireless access. Please be sure you know your UT EID when you come to class. To obtain a UT EID, go here.
CB25036
Instructor
James Derry (Senior Systems Administrator)
James Derry is a senior systems administrator and has taught a semester-long introduction to programming course each long semester for the last 14 years.
Status
Closed
Modality
In-person
Course Closes
Wed, Jun 04
Procard Disclaimer
If you use the UT ProCard for payment of courses, please be aware that you can only charge ONCE per 24 hour period. Any attempts to charge more courses will fail, and you will not be registered.
For example, you may add one to many courses for one student into your shopping cart at any one time, and charge them to the ProCard, and you should receive a "registration successful!" page at the end. This is because you registered ONCE for ONE student. If you attempt to register and pay again, for example, for a different student, this will trigger the UT ProCard security system to stop payment, and your registration will not be successful. A page stating this fact will occur after you attempt to process payment. It looks a lot like the "registration was successful" page.
Ways to avoid this are: use the ProCard after 24 hours have passed, or the student may use their credit card and be reimbursed later through the usual UT accounting methods, or process the registration with an IDT, otherwise known as an Interdepartmental Transfer (talk to someone in your department that handles the accounts).
Course Semester
Course Type
June 9 - June 13
Start Date
9:00 am - 12:00 pm