Processing Actionable Data in Genomics
BIOL-40327
Experience bioinformatics approaches to processing genomic data and distilling consequential biomedical information. Genomic sequencing technologies deliver massive volumes of data that require dedicated handling methods and diverse abilities for troubleshooting. This hands-on course focuses on UNIX-based analysis tasks commonly employed in the field. Instruction covers general considerations ranging from experiment configuration, data QC, and software systems, to tuning of algorithms and visualization of results. In addition, assigned work with public datasets will provide students with weekly hands-on experience with several widely used techniques, including read mapping, variant calling, annotation, and pipeline construction. Class sessions consist of video lectures covering slides, some assigned reading, quizzes, and directed forum participation. Mandatory data processing homework is a significant part of this class.
By the end of the course, you will be able to:
- Compare the utility of different types of sequencing experiments
- Structure bioinformatic pipelines to fit the experiment
- Implement steps in bioinformatic processing
- Critique genomic processing results
For more information on this course, please contact: appliedscience@ucsd.edu
Course Information
Course sessions
Section ID:
Class type:
This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.
Textbooks:
No textbook required.
Policies:
- No refunds after: 7/14/2025
Schedule:
Instructor:
Fatemeh Zare
Dr. Fatima Zare is a seasoned bioinformatics data scientist with over 8 years of experience, currently serving as the Lead Data Scientist at bioMérieux. She brings a robust background in mathematics and a passion for data, excelling in data cleaning, modeling, and uncovering actionable insights.
Specializing in tools like Python and R, Dr. Zare leverages libraries such as Pandas, NumPy, TensorFlow, and Scikit-Learn to address complex machine learning challenges, including regression, clustering, natural language processing (NLP), and time series analysis. She is proficient in platforms like Jupyter Notebook, Google Colab, and PyCharm, and ensures efficient project management using tools like Jira and Git.
Dr. Zare holds a Ph.D. in Computer Science & Engineering from the University of Connecticut and has conducted advanced research as a Postdoctoral Fellow at Harvard University. With a deep commitment to education, she combines her analytical expertise, leadership, and communication skills to empower aspiring data scientists to excel in the field.
Section ID:
Class type:
This course is entirely web-based and to be completed asynchronously between the published course start and end dates. Synchronous attendance is NOT required.
You will have access to your online course on the published start date OR 1 business day after your enrollment is confirmed if you enroll on or after the published start date.
Textbooks:
All course materials are included unless otherwise stated.
Policies:
- No refunds after: 10/6/2025
Schedule:
Instructor:
Fatemeh Zare
Dr. Fatima Zare is a seasoned bioinformatics data scientist with over 8 years of experience, currently serving as the Lead Data Scientist at bioMérieux. She brings a robust background in mathematics and a passion for data, excelling in data cleaning, modeling, and uncovering actionable insights.
Specializing in tools like Python and R, Dr. Zare leverages libraries such as Pandas, NumPy, TensorFlow, and Scikit-Learn to address complex machine learning challenges, including regression, clustering, natural language processing (NLP), and time series analysis. She is proficient in platforms like Jupyter Notebook, Google Colab, and PyCharm, and ensures efficient project management using tools like Jira and Git.
Dr. Zare holds a Ph.D. in Computer Science & Engineering from the University of Connecticut and has conducted advanced research as a Postdoctoral Fellow at Harvard University. With a deep commitment to education, she combines her analytical expertise, leadership, and communication skills to empower aspiring data scientists to excel in the field.
