INTRODUCTION
BDG LifeSciences is a distinguished bioinformatics company established in 2010 and operates globally. Headquartered in India the company specializes in facilitating workshops, training programs, novel & innovative research projects, and online courses in technologies of bioinformatics & life science. The company is registered under the Ministry of MSME (Micro, Small, and Medium Enterprises), Government of India, with the registration number UDYAM-UP-01-0019151. Recently, BDG Lifesciences, India has authorized BBR Group Pty Ltd., Australia (ACN 608 550 849), to operate its programs in Australia & New Zealand.
With a focus on practical application of technology, where participants work on their own computer/laptop on software/servers, BDG LifeSciences has been a leader in the sector for the last 14 years. Since its inception, BDG LifeSciences has successfully educated a diverse range of participants globally, including students, scientists, faculty members, professors, and corporate executives.
Innovation & Creativity is the core part of BDG Lifesciences and as per the increasing demand advancing in the technology we have launched a 5-day Online Technical Training in Artificial Intelligence in Genomics. It will be an extensive 5-day training program in which every day 120 minutes interactive training sessions will be conducted to give the user a unique learning experience. VIDEO RECORDING WILL BE PROVIDED. On successful completion of the course participation certificate will be awarded.
This 5-day Technical Hands-on Training program explores the integration of Artificial Intelligence (AI) in genomics. Participants will learn how AI techniques, including machine learning and deep learning, are applied to genomic data analysis, variant calling, gene expression analysis, and personalized medicine, enhancing understanding and advancements in genomics research.
Course Overview
TOPICS/MODULES COVERED IN THIS TRAINING:
Introduction to AI and Genomics
- Overview of Genomics: Genomic data types, sequencing technologies (NGS, RNA-seq, etc.), and applications in precision medicine.
- Introduction to AI: Key AI concepts, machine learning (ML), and deep learning (DL) fundamentals.
- AI in Genomics: How AI is transforming genomic data analysis.
Hands-on Activity: Setting up Python, AI libraries (TensorFlow, Keras, scikit-learn), and basic genomic data analysis workflows.
Data Preprocessing and Feature Engineering in Genomics
- Genomic Data Preprocessing: Techniques for cleaning and preparing genomic data (quality control, normalization, etc.).
- Handling Big Data: Approaches for dealing with large-scale genomic datasets, cloud computing tools, and bioinformatics pipelines.
- Feature Engineering for Genomic Analysis: Identifying and creating useful features for downstream AI models.
Hands-on Activity: Implementing data preprocessing techniques on a real genomic dataset.
Machine Learning for Genomic Data Analysis
- Supervised Learning in Genomics: Classifying genetic variants, disease prediction, and other applications using supervised ML methods.
- Unsupervised Learning: Clustering, dimensionality reduction, and pattern recognition in genomics.
- Deep Learning Models: Convolutional neural networks (CNNs), recurrent neural networks (RNNs) for genomic sequence analysis.
Hands-on Activity: Building and training machine learning models for genetic variant classification.
AI in Genomic Variant Calling and Annotation
- Variant Calling: Understanding the process of identifying genetic variants from sequencing data.
- AI-Driven Variant Annotation: Using machine learning algorithms to predict the impact of genetic variants.
- Integrating AI with Databases: Using genomic databases and AI for annotation and interpretation of variants.
Hands-on Activity: Running variant calling pipelines and annotating variants using AI-based tools.
AI in Personalized Medicine and Future Trends
- AI in Personalized Genomics: Using AI to identify biomarkers and predict treatment responses based on genetic profiles.
- AI in Genome-Wide Association Studies (GWAS): Leveraging AI to analyze complex genetic traits and diseases.
- Emerging Trends: AI in CRISPR, genome editing, and synthetic biology.
Hands-on Activity: Developing a personalized medicine model using genomic data for drug response prediction.
Practical Application
SOFTWARE & SERVERS WHICH WILL BE USED:
Programming Languages and Libraries
Genomic Data Analysis Tools
- Biopython: Tools for working with biological data, including sequence manipulation and parsing bioinformatics formats (FASTA, VCF, GFF).
- GATK (Genome Analysis Toolkit): Variant calling and annotation for genomic datasets.
- VCFtools: Software for working with VCF (Variant Call Format) files to analyze genetic variants.
AI and Machine Learning Platforms
- Google Colab: Cloud-based Jupyter notebooks for running Python code, providing GPU support for deep learning models.
- Kaggle Kernels: Cloud-based computational environment for data analysis and ML model training.
- Amazon Web Services (AWS): For larger genomic datasets, EC2 instances and S3 storage can be used.
- Microsoft Azure: AI-powered genomic analysis and cloud-based tools.
Data Repositories and Databases
- GenBank: A public database of nucleotide sequences and other genetic data.
- dbSNP: Database of single nucleotide polymorphisms for variant analysis.
- 1000 Genomes Project: Database for human genetic variation analysis.
- Ensembl: Genomic database for gene annotation and variant analysis.
- UCSC Genome Browser: Tool for visualizing and analyzing genomic data.
Visualization Tools
- IGV (Integrative Genomics Viewer): For visualizing genomic data and variants.
- Circos: Visualization tool for genomic data in circular plots.
- Plotly: Interactive data visualizations to interpret genomic and AI analysis results.
Collaborative Platforms
- GitHub: For version control and collaborative coding during the training.
- Slack/Zoom: For communication, Q&A, and sharing resources during the training.
These tools and platforms will be used throughout the training for hands-on exercises, data analysis, AI model development, and visualization, enabling participants to gain practical experience in AI-powered genomics research.
Learning Objectives
OUTCOME [WHAT PEOPLE WILL LEARN]:
By the end of this training, participants will:
- Understand the Fundamentals of AI in Genomics: Gain a solid understanding of how artificial intelligence is revolutionizing genomics, including the use of machine learning and deep learning techniques for genomic data analysis.
- Analyze Genomic Data with AI Tools: Learn to preprocess, analyze, and visualize genomic datasets using Python libraries and AI tools.
- Develop Machine Learning Models for Genomic Data: Understand how to apply supervised and unsupervised machine learning techniques for variant prediction, gene expression analysis, and personalized medicine.
- Explore Deep Learning for Genomics: Gain experience in implementing deep learning models (e.g., neural networks) to interpret complex genomic data and predict disease outcomes.
- Use AI for Variant Calling and Annotation: Learn to use AI models for accurate variant detection and annotation from genomic data, improving variant interpretation.
- Build Predictive Models for Genomic Phenotypes: Use AI to build predictive models for genomic phenotypes and identify biomarkers for disease risk and treatment response.
- Explore AI in Personalized Medicine: Understand how AI models can be applied to design personalized treatment plans based on genomic profiles.
- Implement Best Practices for AI in Genomics: Learn about the challenges of working with genomic data, including data preprocessing, model validation, and overfitting, and how to address these challenges.
- Hands-on Experience with Genomic Data Analysis: Gain practical experience using real-world genomic data from public repositories and applying AI algorithms to solve complex problems in genomics.
- Collaborative and Practical Skills: Develop collaborative skills in data science and genomics through group exercises and projects, using version control systems like GitHub.
DURATION [IN DAYS & TIME SPENT FOR EVERYDAY SESSION]: 5 days ( 2hrs / day)
SYSTEM REQUIREMENT [LIST THE SYSTEM REQUIREMENT]:Laptop or PC with 4GB RAM
PRE-REQUISITES [LIST ANY PRIOR KNOWLEDGE REQUIRED]:Not needed
Target Audience
This training is ideal for:
1. Students
- Including undergraduate and postgraduate students studying life sciences, medical sciences, and related fields.
- Medical and pharmaceutical students who are exploring AI in Drug Discovery, genetic engineering and genomic research
- Ph.D. candidates specializing in molecular biology, bioinformatics, biotechnology, or similar disciplines..
2. Academicians
- Faculty and educators seeking to integrate AI and genomic analysis into their curriculum.
- Researchers looking to apply AI techniques in experimental and computational genomics.
3. Industry Professionals:
- Individuals from fields such as microbiology, biochemistry, biotechnology, immunology, medicine, pharmacy, pharmaceutical chemistry, biomedical sciences, genetics, and bioinformatics.
- Resident doctors, bioinformaticians, pharmaceutical scientists, and professionals in academia, industry, or regulatory agencies aiming to enhance their skills in AI-driven genomics and personalized medicine.
Methodology
The program combines interactive lectures, hands-on activities using AI and genomic tools, and real-world case studies. Participants will engage in practical exercises on platforms like Python, TensorFlow, and GATK, ensuring an immersive learning experience.
Why You Should Attend
Stay at the forefront of genomics research by mastering AI tools and techniques. This training offers practical insights and prepares participants to tackle complex problems in genomics, from data analysis to personalized medicine.
Why Choose BDG LifeSciences for this Training?
1. Experience and Credibility: BDG LifeSciences, with over 14 years of expertise, is a market leader in bioinformatics course training and workshops.
2. Global Reach: Programs are accessible by participants from all around the world, and the curriculum is customized to international standards.
3. Hands-On Learning: The emphasis on practical application ensures that participants may instantly apply their knowledge.
4. Expert Advice: Training is provided by professionals with substantial knowledge of bioinformatics and related technologies.
How to Register
To secure your spot:
- Click on Register Now button and proceed.
- After registering, please email to info@bdglifesciences.com with your preferred start date and choose one of the following time slots: 6:30 AM–8:30 AM India time or 8:30 PM–10:30 PM India time.
- Kindly note that the time of the sessions will be 90-120 minutes every day.
- Once you register, please allow us 2-5 working days to make your training schedule, i.e. dates and time.
- For any further queries, feel free to email us at info@bdglifesciences.com
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T & C
- Please provide a GMAIL ID for registration as the recorded video session will be provided on YouTube. Kindly provide that email ID by which you use YouTube.
- Since the training is a one-on-one live session with a trainer on Zoom, you'll need to attend, allowing for practical hands-on learning, real-time explanations, and direct query resolution for a better learning experience.
- At the end of each session, you will receive a video recording, allowing you to review the steps as many times as needed to enhance your learning and master the topics and tasks.
- BDG Lifesceiences (OPC) Private Limited is registered under Ministry of MSME(Micro, Small and Medium Enterprises), Government of India with Registration Number:UDYAM-UP-01-0019151 hence the certificate will be provided of it. BBR Group Pty Ltd, Australia (ACN-Australian Company Number-608 550 849) has the franchisee of BDG Lifesciences to run its programs in Australia & New Zealand.
- The certificate will be issued as per the details which you will provide in the registration form while registering before payment.
- We want to make sure that you learn properly hence the training certificate will be given ONLY on successful completion of all the tasks given by the trainer.
- The certificates of all our Online programs are sent by email (softcopy) which has a unique barcode. You can take a print of that on heavy cardstock or photo paper and get it laminated if required.
- The registration is NON-REFUNDABLE and NON-TRANSFERABLE.
- BDG Lifesciences (OPC) Pvt. Ltd., India and BBR Group Pty Ltd Australia reserve the right of admission in all our programs.
- If you are removed or your registration is canceled then there will be no answer to that. We have our own reasons for such an act of ours. If we do not wish to give this training to any participant then we will refund their amount.
- You should also read the Terms & Conditions page as well as the FAQs page. For any assistance kindly chat with our AI Assistant BioBot on the website www.bdglifesciences.com
