Online Workshop on:
Last date for registration: 5th April 2025
About Workshop
Over the past decade, computational methods in precision oncology have advanced significantly, leading to major discoveries that have driven the development of new therapeutics and diagnostics. This progress is largely due to the surge in multi-omics data generated by advancements in sequencing technologies and their reduced costs. Understanding these methods is essential for analyzing large volumes of multi-omics oncology data. This workshop is designed with these objectives in mind. It aims to provide insights into advanced computational approaches in oncology and precision medicine, offering participants a unique opportunity to learn about cutting-edge tools and methods. The workshop will feature expert computational scientists from renowned institutions, sharing their empirical knowledge with participants in the field of computational precision oncology.
At the end of successful completion of the workshop, participants will be provided certificates from CCE, IIT Hyderabad. Seats are limited, so early registration is recommended.
Workshop Topics
Multi-omics Approaches in Precision Oncology
Multi-omics Approaches
Learn integrative analysis techniques for comprehensive cancer profiling across different data types.
Somatic Mutation and Copy Number Variation Calling
Somatic Mutations & CNVs
Discover techniques for accurate detection and interpretation of cancer-specific genetic alterations.
Identification of Tumor subtypes Using Clustering Methods
Tumor Subtypes & Clustering
Explore algorithms to classify tumors into meaningful subtypes for personalized treatment strategies.
Network based approach for biomarkers and therapeutic targets
Network-Based Approaches
Learn to identify potential cancer biomarkers and drug targets using network biology principles.
Unraveling Biological Pathways Using Transcriptomic Data
Biological Pathway Analysis
Master techniques to decode molecular mechanisms from transcriptome data.
Differential Gene Expression Analysis
Differential Expression Analysis
Learn methods to identify genes with significant expression changes between cancer and normal conditions.
Chimeric RNAs in Cancer Research
Chimeric RNAs
Understand the role of fusion transcripts in oncogenesis and their potential as biomarkers.
Methods of Chimeric RNAs Identification
Chimeric RNA Identification
Explore computational approaches for detecting fusion transcripts from RNA-seq data.
Basic Prerequisites
Linux Experience
Familiarity with Linux operating system and command-line interface
Programming Skills
Basic knowledge of Python and/or R programming languages
Required Equipment
Laptop with required software installed (list will be provided)
Featured Speakers
Registration Fee
Workshop Schedule
- Overview of the workshop
- Somatic Mutation and Copy Number Variation Calling
- Multi-omics Approaches in Precision Oncology
- Identification of Tumor subtypes Using Clustering Methods
- Unraveling Biological Pathways Using Transcriptomic Data Analysis
- Differential Gene Expression Analysis Using Transcriptomic Data
- Chimeric RNAs in Cancer Research
- Methods of Chimeric RNAs Identification
- Network based approach for identifying biomarkers and new therapeutic targets