Cancer Transcriptomics
Cancer transcriptomics is a rapidly growing field of bioinformatics that focuses on the analysis of gene expression patterns in cancer cells. By studying gene expression in cancer cells, researchers can identify genes that are important for the development and progression of cancer, as well as potential targets for new therapies. This field combines knowledge from molecular biology, genetics, and computer science to analyze large datasets and generate new insights.
Praxis Courses
Digital Biology
World renowned professor Dr. Alex Feltus from Clemson University has built this powerful computational biology journey including Python techniques to parse genomics data files, transcribe DNA files into RNA files, and translate RNA files into protein sequence files. Students will also explore the genomics of the Coronavirus. Qualifies for the BioHackers: Digital Biology digital badge.
Bioinformatics
In this Bioinformatics Journey, students will explore how computational environments such as Linux, Jupyter Notebooks, and Python impact biosciences and genomics. In addition, they will gain insights into genome data mining, structural bioinformatics, and systems biology using data-intensive hands-on labs and AI-powered collaboration. Qualifies for the BioHacker: Bioinformatics digital badge.
Medical Bioinformatics
World-renown scientist Dr. Alex Feltus teaches students how to use bioinformatics workflows to solve today’s toughest genomics problems with a focus on gene expression changes between normal and cancer tissue. In addition, students will gain insights into genome data mining, cancer and normal transcriptomics, differential gene expression analysis, and biomarker discovery. Qualifies for the BioHacker: Cancer Transcriptomics digital badge.
Praxis Credentials
Digital Biology
Earners of the Digital Biology BioHacker credential have successfully demonstrated experiential skills in computational biology, python programming, Linux command line, applied genomics, and running biological workflows on data-intensive computing systems. The Digital Biology badge requires 50+ hours of hands-on activities and labs across 17 skills in biotech R&D. This BioHacker credential was built in collaboration with world renowned professor Alex Feltus, currently at Clemson University.
Bioinformatics
Earners of the Bioinformatics BioHacker credential have successfully demonstrated experiential skills in computational biology, genome data mining, structural bioinformatics, and systems biology. The Bioinformatics badge requires 75+ hours of hands-on activities and labs across 20+ skills in biotech R&D. The Bioinformatics BioHacker credential was built in collaboration with world renowned professor Alex Feltus, currently at Clemson University.
Cancer Transcriptomics
Earners of the Cancer transcriptomics BioHacker credential have successfully demonstrated experiential skills in computational biology, genome data mining, structural bioinformatics, and systems biology. The Cancer transcriptomics badge requires 75+ hours of hands-on activities and labs across 20+ skills in biotech R&D. The Cancer transcriptomics BioHacker credential was built in collaboration with world renowned professor Alex Feltus, currently at Clemson University.
Top Cancer Transcriptomics Careers
Here are the top 10 careers in Cancer Transcriptomics for someone with the skill sets earned from these Praxis courses and digital credentials:
- Cancer Transcriptomics Researcher: As a researcher in this field, you will be responsible for designing and executing experiments to analyze the transcriptomes of cancer cells. You will use your skills in GEM Construction, GEM Preprocessing, DEG Analysis, GCN Analysis, and GRN Linking to identify key genes and pathways involved in cancer growth and progression.
- Bioinformatics Analyst: In this role, you will be responsible for analyzing and interpreting large biological datasets using bioinformatics tools and methods, with a focus on cancer transcriptomics. You will use your skills in Linux & Bash scripting, Jupyter Notebooks, and Genomics Data Formats to analyze and interpret data from the NCBI Short Read Archive, ENSEMBL, and other genomics data sources.
- Computational Biologist: This job involves using computational methods to analyze and interpret large biological datasets, with a focus on cancer transcriptomics. You will use your skills in GEM Construction, GEM Preprocessing, DEG Analysis, GCN Analysis, and GRN Linking to develop predictive models for cancer diagnosis and treatment.
- Cancer Genomics Data Scientist: In this role, you will be responsible for using genomics data to develop predictive models for cancer diagnosis and treatment. You will use your skills in GEM Construction, GEM Preprocessing, DEG Analysis, GCN Analysis, and GRN Linking to identify key genes and pathways involved in cancer growth and progression.
- Medical Bioinformatics Specialist: This position involves analyzing medical data, including cancer genomics data, to support clinical research and patient care. You will use your skills in GEM Construction, GEM Preprocessing, DEG Analysis, GCN Analysis, and GRN Linking to analyze and interpret genomics data in the context of cancer.
- Cancer Bioinformatics Engineer: In this role, you will be responsible for developing and implementing bioinformatics software and tools for cancer research. You will use your skills in Linux & Bash scripting, Jupyter Notebooks, and Genomics Data Formats to design and develop software that is optimized for cancer transcriptomics research.
- Cancer Genomics Data Manager: This job involves managing large genomics datasets for cancer research, including data from the NCBI Short Read Archive, ENSEMBL, and other genomics data sources. You will use your skills in Genomics Data Formats and Genotype-Phenotype Expression (GTEx) to manage and organize this data for analysis.
- Cancer Genomics Data Curator: In this role, you will be responsible for curating cancer genomics data for use in research. You will use your skills in Genomics Data Formats and Genotype-Phenotype Expression (GTEx) to ensure that this data is accurate and complete.
- Cancer Genomics Consultant: This job involves providing consulting services to other researchers and organizations involved in cancer genomics research.
- Software Engineer: A software engineer develops software tools and platforms for analyzing and visualizing large genomic datasets, including those generated from cancer transcriptomics studies.
