Launching a New Biomedical Data Science Program
Our latest program is on biomedical data science and the application of machine learning to biomedical problems. We will use practical examples from biomedical research and industry challenges, such as diagnostics and drug target discovery, and apply data analysis methods to solve them. As the biomedical industry becomes more data driven and more high-impact journals require rigorous bioinformatics analysis accompanied by clear visualization of complex data sets, it is incumbent for those who are seeking to stay relevant and up to date with the industry to learn data science skills.
In this program, we will cover three main aspects of data analysis: exploratory data analysis, data mining, and machine learning. We will combine these computational skills by exploring the intersection of biomedical topics, ranging from precision medicine to drug discovery, with key data science concepts. By the end of this program, individuals should be able to analyze large and complex data sets, build processing pipelines, and use data mining techniques to identify interpretable trends. To communicate analysis results and deploy predictive models, you will learn to generate insights through visualization and train machine learning models. This may seem like a lot, but with the intuitive T-Bio.info platform that is user-friendly and visual, a lot of those topics that require complex algorithms will be a simplified and streamlined. We will also cover aspects of biostatistics in Excel and visualization in R.
After completing the basic training using project examples that we will provide, every participant will have the option to complete a full analysis independently, or select another public domain data set and apply the learned skills to this challenge. One of our team members who is an expert in this field will help you with project selection, planning your analysis, and arriving at reproducible results. We will meet twice a week to review the program material and provide hands on guidance. Upon completion of the program, you will receive of a certificate of participation.
Here’s the link to pre-register for the program: https://edu.tbioinfo.com/omicslogic-biomedical-data-science
Testimonials about OmicsLogic Bioinformatics Training Programs
Here are some testimonials from individuals who have completed previous programs:
“Pine Biotech has done a great job putting together concise, informative, project based program around bioinformatic topics. They also have a pipeline to analyze data that seems robust and comprehensive for almost any type of bioinformatic analysis. I say this as a scientist and an educator.”
– Dr. Ian Townley, Professor of Practice,
Tulane University Department of Cell & Molecular Biology
“As a Molecular Biologist, having to write programs and codes to
analyze sequenced data seems like a lot to add to my already busy work schedule. The T-Bioinfo platform brings a new and friendly approach to analyzing genomic data, freeing up my time to focus on the biological aspects of my research. The online course are similar to a flipped classroom format and easy to follow for independent study. I thoroughly enjoyed the 3 months OmicsLogic program on RNA- seq, and transcriptomics. I would recommend this training to any Biologist looking to enhance their data analysis skills.”
– Voke Toye, PhD Cell Biology & Genetics, University of Lagos, Nigeria
Next Steps: Attend the Biomedical Data Science Free Webinar
If you are curious about this program, we will hold a free webinar September 10th to dive deeper into the details of this program. And if you are unsure if you want to commit to something at this time, our educational portal has plenty of free courses that you can sample as a flavor of what to expect in this program.
The access to industry experts, the practical hands on projects, guidance with the T-bio.info platform, and the network of people who will enroll in this program alongside you should make this course an unparalleled experience.
In case you missed our previous webinar for this course that was done yesterday, you can find it here: https://youtu.be/4Y6it6PZgC8.