06-22-2024, 07:28 PM
![[Image: f81e4e69b0633ef9654e94a8b9d75d5e.jpg]](https://i123.fastpic.org/big/2024/0622/5e/f81e4e69b0633ef9654e94a8b9d75d5e.jpg)
Bioinformatics in Cancer research: Discover the biomarkers
Published 6/2024
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 3h 2m | 1.72 GB
Mastering Health Bioinformatics: Biomarker Discovery, Genomic Analysis, and Functional Insights for research papers
What you'll learn
Biomarker Fundamentals: Understand the fundamental concepts of biomarkers, including their types, significance in health research, and applications
Data Handling: Learn how to access, manage, and preprocess large-scale biological data, including genomics, transcriptomics, and proteomics data.
Bioinformatics Tools: Gain proficiency in using bioinformatics tools and software for data analysis, including R, Python, and specialized biomarker
Statistical Analysis: Master statistical techniques and methodologies for identifying differentially expressed genes or proteins that serve
Data Visualization: Learn to create informative data visualizations to represent findings and insights, aiding in the interpretation of results.
Biomarker Discovery: Explore various methods for identifying and validating biomarkers, with a focus on their role in health research.
Integration of Omics Data: Understand how to integrate data from different omics levels (genomics, transcriptomics, proteomics) to discover multi-dimensional
Hands-on Experience: Gain practical experience by working with real data, performing analyses, and presenting research findings.
Interdisciplinary Collaboration: Learn the importance of collaboration between bioinformaticians, biologists, clinicians, and other experts in health research.
Upon completing this course, students will be well-equipped to conduct biomarker research, interpret data, and contribute to the field of health bioinformatics
![[Image: 2KMnn125_o.jpg]](https://images2.imgbox.com/90/f6/2KMnn125_o.jpg)
What you'll learn
Biomarker Fundamentals: Understand the fundamental concepts of biomarkers, including their types, significance in health research, and applications
Data Handling: Learn how to access, manage, and preprocess large-scale biological data, including genomics, transcriptomics, and proteomics data.
Bioinformatics Tools: Gain proficiency in using bioinformatics tools and software for data analysis, including R, Python, and specialized biomarker
Statistical Analysis: Master statistical techniques and methodologies for identifying differentially expressed genes or proteins that serve
Data Visualization: Learn to create informative data visualizations to represent findings and insights, aiding in the interpretation of results.
Biomarker Discovery: Explore various methods for identifying and validating biomarkers, with a focus on their role in health research.
Integration of Omics Data: Understand how to integrate data from different omics levels (genomics, transcriptomics, proteomics) to discover multi-dimensional
Hands-on Experience: Gain practical experience by working with real data, performing analyses, and presenting research findings.
Interdisciplinary Collaboration: Learn the importance of collaboration between bioinformaticians, biologists, clinicians, and other experts in health research.
Upon completing this course, students will be well-equipped to conduct biomarker research, interpret data, and contribute to the field of health bioinformatics
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