BioInformatics Series - Session 2
BioInformatics Series - Session 2
π Bioinformatics Series – Session 2! π§¬π‘
Hey bio-coders! Ready for Round 2? π―
Let’s level up your bioinformatics journey! π
In this session, we’re diving deeper into the real-world tools that scientists use every day. ππ§ͺ
You’ll explore how open-source biological databases power discoveries and how data cleaning is the first step to turning raw data into reliable science! π§Όπ¬
β¨ Here’s what’s coming up in Session 2:
β Discover famous open databases like GenBank, Ensembl, and more ππ
β Understand data cleaning in biology—from sequencing errors 𧬠to noisy lab results π§«
β Walk through your Python bio-code line by line—yes, we're breaking it down together! ππ©π»π¨π»
β Expand your DNA tool: add new functions and clean sequence data π§Ήπ§
Whether you're into genetics, evolution, or just love decoding puzzles, this session is for you! π§©β¨
π’ Presented by IEEE Student Branch ULFS2
π Led by Elie Dina, PhD student in AI & Data Science
π Date: Thursday, April 10, 2025
β° Time: 7:30 PM (1h30)
π Online via Google Meet
Join us and code your way into bioinformatics! ππ₯
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Date and Time
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- Date: 10 Apr 2025
- Time: 04:30 PM UTC to 06:00 PM UTC
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Speakers
Mr Elie Dina
BioInformatics Series - Session 2
Biography:
Mr. Elie Dina is a seasoned professional in the realm of data science and machine learning, boasting a rich experience spanning over two years. His expertise encompasses a wide array of skills and accomplishments, including the adept utilization of statistical methodologies and machine learning techniques to dissect and model datasets of varying sizes, from modest to extensive scales. He has successfully navigated the intricacies of deploying machine learning models within production environments, demonstrating a keen proficiency in implementing these solutions effectively.
With a versatile background, Mr. Dina has ventured into diverse industries, leaving an indelible mark in sectors such as environmental studies and e-commerce. His toolset includes mastery in programming languages like Python and R, coupled with a deep understanding of pivotal machine learning libraries and frameworks such as scikit-learn, TensorFlow, and Keras. Beyond technical prowess, Mr. Dina excels in communication, effortlessly conveying complex technical concepts to non-technical stakeholders and delivering data-driven insights with precision to decision-makers.
Email:
Address:France