Analysis of Microarray Data using Machine Learning/AI in R
Decoding Genetic Data: AI-Powered Microarray Analysis in R.
Virtual (Google Meet)
Mentor Based
Moderate
3 Days (1.5 hours per day)
09 – Jan – 25
8:00 PM IST
About
Microarrays are one of the most common tools to understand biological spectacle by large-scale dimensions of biological samples, typically DNA, RNA, or proteins. The technique has been used for a variety of purposes in life science research, ranging from gene expression profiling to SNP or other biomarker identification, and further, to understand relations between genes and their activities on a large scale. Artificial intelligence (AI) and machine learning (ML) techniques can be used to analyse microarray data to gain insights into biological processes. Machine learning tools can automate the analysis of microarray data to identify patterns of gene expression. These patterns can be used to compare gene expression between different conditions, such as healthy and diseased cells. There are no curated machine learning/AI-ready datasets that meet the requirements for machine learning analyses within public functional genomics repositories at the moment.
The R language supports identifying gene expression through Bioconductor packages to show all differential gene expressions by generating the volcano map, Euclidean distances to perform clustering, Venn diagram, and heatmap.
Aim
The aim of microarray data analyses is the identification of genes showing significant differences in expression levels between two or more groups.
Workshop Objectives
- Master the fundamentals of microarray technology and its applications.
- Utilize R to preprocess, analyze, and interpret microarray data.
- Apply AI and machine learning techniques to uncover patterns in complex genetic datasets.
- Develop skills in statistical analysis and biomarker identification.
- Understand the ethical implications of genomic data handling and reporting.
Workshop Structure
DAY 1: Functional genomics repositories
- General Overview of public genomics repositories
- Overview of GEO2R, procedure to use, Edit options and features, Limitations and caveats, Summary Statistics.
DAY 2: R studio and Bioconductor packages
- R and Bioconductor packages installation
- GEOquery and limma Bioconductor package
DAY 3: Microarray Data Analysis
- Gene expression analysis with GEOquery and limma for Microarray data analysis
Participant’s Eligibility
- Undergraduate degree in Bioinformatics, Genomics, Computational Biology, or related fields.
- Professionals in biotechnological, pharmaceutical sectors, or clinical research.
- Individuals with foundational knowledge of molecular biology and an enthusiasm for computational data analysis.
Important Dates
Registration Ends
2025-01-09
Indian Standard Timing 07:00 PM
Workshop Dates
2025-01-09 to 2025-01-11
Indian Standard Timing 8:00 PM
Workshop Outcomes
- Proficiency in analyzing microarray data using advanced AI and machine learning techniques
- Capable of contributing to genetic research, diagnostics, and therapeutic developments
Mentor Profile
Designation: Professor and Head
Affiliation: Shalom New Life College, Bengaluru, Karnataka
Dr. Md Afroz Alam is a Professor and Head in the Department of Bioinformatics, at Shalom New Life College, Bengaluru, Karnataka. He received his Ph.D. Degree in Bioinformatics from Jaypee University of Information Technology, Solan, Himachal Pradesh in 2009. Then he has worked as Assistant Professor, Head and Program Coordinator in the Department of Bioinformatics at Karunya Institute of Technology and Sciences (Deemed University) for 11 Years. He is having 14 years of teaching and research experience in the field of Bioinformatics. His area of expertise includes: Computer Aided Drug Design, Molecular Modeling and Simulation, QSAR and Pharmacophore modeling, Biostatistics, R programming, Unix and Linux. He is the author of 24 research articles, 2 Book Chapter, recipient of short-term research grants, workshop grants, and National Youth leader award by Ministry of Youth Affairs and Sports under the National Service Scheme, Government of India.
Fee Structure
Student
INR. 1399
USD. 50
Ph.D. Scholar / Researcher
INR. 1699
USD. 55
Academician / Faculty
INR. 2199
USD. 60
Industry Professional
INR. 2699
USD. 85
List of Currencies
Key Takeaways
- Access to Live Lectures
- Access to Recorded Sessions
- e-Certificate
- Query Solving Post Workshop
Future Career Prospects
- Clinical Data Analyst
- Microarray Data Specialist
- Genomics Data Scientist
- Biostatistician
- Research Scientist in Genomics
- Bioinformatics Developer
Job Opportunities
- Genetic research facilities
- Pharmaceutical companies
- Healthcare settings
- Academic institutions
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