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🚀 𝐋𝐚𝐮𝐧𝐜𝐡𝐢𝐧𝐠 𝐎𝐮𝐫 𝐍𝐞𝐰 𝟑-𝐏𝐚𝐫𝐭 𝐎𝐧𝐥𝐢𝐧𝐞 𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩 𝐒𝐞𝐫𝐢𝐞𝐬: 𝐓𝐡𝐞 𝐀𝐈 𝐃𝐫𝐮𝐠 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲 𝐏𝐫𝐚𝐜𝐭𝐢𝐭𝐢𝐨𝐧𝐞𝐫 💊🤖🧬

Step into the evolving world of AI-driven drug discovery through this hands-on workshop series designed to bridge molecular science, machine learning, and AI-assisted research workflows.

🔹 𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩 𝟏: 𝐌𝐨𝐥𝐞𝐜𝐮𝐥𝐚𝐫 𝐃𝐚𝐭𝐚 𝐄𝐧𝐠𝐢𝐧𝐞𝐞𝐫𝐢𝐧𝐠: 𝐅𝐫𝐨𝐦 𝐂𝐡𝐄𝐌𝐁𝐋 𝐭𝐨 𝐌𝐋-𝐑𝐞𝐚𝐝𝐲 𝐋𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬
🔹 𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩 𝟐: 𝐏𝐫𝐞𝐝𝐢𝐜𝐭 𝐁𝐞𝐟𝐨𝐫𝐞 𝐘𝐨𝐮 𝐒𝐲𝐧𝐭𝐡𝐞𝐬𝐢𝐳𝐞: 𝐌𝐋 𝐟𝐨𝐫 𝐌𝐨𝐥𝐞𝐜𝐮𝐥𝐚𝐫 𝐏𝐫𝐨𝐩𝐞𝐫𝐭𝐢𝐞𝐬 & 𝐀𝐃𝐌𝐄𝐓
🔹 𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩 𝟑: 𝐓𝐡𝐞 𝐀𝐈-𝐀𝐮𝐠𝐦𝐞𝐧𝐭𝐞𝐝 𝐂𝐡𝐞𝐦𝐢𝐬𝐭: 𝐁𝐮𝐢𝐥𝐝𝐢𝐧𝐠 𝐋𝐋𝐌 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬 𝐟𝐨𝐫 𝐃𝐫𝐮𝐠 𝐃𝐢𝐬𝐜𝐨𝐯𝐞𝐫𝐲

🧠 𝐓𝐡𝐞 𝐬𝐞𝐫𝐢𝐞𝐬 𝐞𝐦𝐩𝐡𝐚𝐬𝐢𝐳𝐞𝐬 𝐩𝐫𝐚𝐜𝐭𝐢𝐜𝐚𝐥, 𝐦𝐞𝐧𝐭𝐨𝐫-𝐠𝐮𝐢𝐝𝐞𝐝 𝐥𝐞𝐚𝐫𝐧𝐢𝐧𝐠 through live sessions, hands-on exercises, curated datasets, Google Colab workflows, and real-world case studies used in modern computational drug discovery.

🔬 Participants can also optionally extend their learning through the parallel 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐈𝐧𝐭𝐞𝐫𝐧𝐬𝐡𝐢𝐩 𝐏𝐫𝐨𝐠𝐫𝐚𝐦, offering hands-on experience in AI-driven drug discovery projects with structured mentorship and research guidance.

📌 𝐍𝐨𝐭𝐞: Participants can register for 𝐢𝐧𝐝𝐢𝐯𝐢𝐝𝐮𝐚𝐥 𝐰𝐨𝐫𝐤𝐬𝐡𝐨𝐩𝐬 or enroll in the 𝐜𝐨𝐦𝐩𝐥𝐞𝐭𝐞 𝟗-𝐬𝐞𝐬𝐬𝐢𝐨𝐧 𝐜𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐞 𝐩𝐫𝐨𝐠𝐫𝐚𝐦 based on their learning goals.

🔗 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐧𝐨𝐰: https://forms.gle/bntZVsbD7mS5cPn89

If you’re working on GitHub without branches and pull requests… things can get messy fast 👀

🔀 Branching lets you work on features or fixes without touching the main code. Safe, isolated, and experiment-friendly.

🔁 Pull Requests (PRs) are how you propose changes, review code, and merge updates cleanly.

🧠 Why it matters:
Better collaboration, fewer bugs, and a clear history of changes.

🚀 Rule: Branch to build. PR to review. Merge to ship.

If you want to learn more, then join our 𝟑-𝐃𝐚𝐲 𝐇𝐚𝐧𝐝𝐬-𝐎𝐧 𝐎𝐧𝐥𝐢𝐧𝐞 𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩: 𝐆𝐢𝐭𝐡𝐮𝐛 𝐟𝐨𝐫 𝐁𝐢𝐨𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐜𝐬! 🔥

From basic version control to creating community-driven bioinformatics tools using Large Language Models (LLMs), this comprehensive workshop bridges traditional Git/GitHub skills with cutting-edge AI-powered development. 💻💡 Learn to leverage ChatGPT, Claude, and GitHub Copilot to develop, refine, and share Python/R tools that address real research gaps in bioinformatics.

📅 𝐃𝐚𝐭𝐞: June 15 - June 17, 2026
🕒 𝐓𝐢𝐦𝐞: 7:00 PM IST | 8:30 AM CDT
📍 𝐋𝐨𝐜𝐚𝐭𝐢𝐨𝐧: Online

🔗 For more information on workshop structure, curriculum, and training resources, register here: https://forms.gle/SPmhPFgD21LYJkCy6

By studying genetic alterations such as point mutations, copy number variations, insertions, deletions, and gene fusions, researchers can uncover the molecular drivers behind tumor development, progression, and therapy resistance. Each tumor carries a distinct genomic signature, making genomic profiling essential for understanding cancer biology and disease heterogeneity.

Mutational analysis plays a central role in identifying clinically significant variants, discovering biomarkers, and exploring potential therapeutic targets. From tracking tumor evolution to supporting precision oncology research, cancer genomics is helping convert complex genomic data into meaningful biological and clinical insights.

Join our 4-Day Online Hands-On Workshop on 𝐂𝐚𝐧𝐜𝐞𝐫 𝐆𝐞𝐧𝐨𝐦𝐢𝐜𝐬 𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩 (𝐌𝐮𝐭𝐚𝐭𝐢𝐨𝐧𝐚𝐥 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬; 𝐕𝐚𝐫𝐢𝐚𝐧𝐭 𝐀𝐧𝐧𝐨𝐭𝐚𝐭𝐢𝐨𝐧, & 𝐂𝐥𝐢𝐧𝐢𝐜𝐚𝐥 𝐃𝐚𝐭𝐚 𝐈𝐧𝐭𝐞𝐫𝐩𝐫𝐞𝐭𝐚𝐭𝐢𝐨𝐧)!

🧬🔬 This hands-on workshop will take you through the hallmarks of cancer, key pathways, and genomic alterations, diving into driver vs. passenger mutations, SNVs, Indels, CNVs, and SVs. Explore oncogenes, tumor suppressors, and NGS data formats (FASTQ, BAM, VCF) while working with real datasets from COSMIC, TCGA, and cBioPortal.

Learn variant analysis (IGV, ANNOVAR, VEP) & clinical annotation (MAFtools, oncoplots, mutation burden analysis), and apply your skills on real cancer data. 🚀

🔗 𝐅𝐨𝐫 𝐦𝐨𝐫𝐞 𝐢𝐧𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐨𝐧 𝐰𝐨𝐫𝐤𝐬𝐡𝐨𝐩 𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞, 𝐜𝐮𝐫𝐫𝐢𝐜𝐮𝐥𝐮𝐦, 𝐚𝐧𝐝 𝐭𝐫𝐚𝐢𝐧𝐢𝐧𝐠 𝐫𝐞𝐬𝐨𝐮𝐫𝐜𝐞𝐬, 𝐫𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐡𝐞𝐫𝐞: https://forms.gle/3GPoVrHxFpGvBt6HA

📅 𝐃𝐚𝐭𝐞: July 6, 2026 - July 9,2026
🕒 𝐓𝐢𝐦𝐞: 7:00 PM IST | 8:30 AM CDT
📍 𝐋𝐨𝐜𝐚𝐭𝐢𝐨𝐧: Online

𝘈𝘐 𝘪𝘯 𝘤𝘭𝘪𝘯𝘪𝘤𝘢𝘭 𝘵𝘳𝘪𝘢𝘭𝘴 𝘪𝘴𝘯'𝘵 𝘫𝘶𝘴𝘵 𝘢𝘣𝘰𝘶𝘵 𝘢𝘶𝘵𝘰𝘮𝘢𝘵𝘪𝘰𝘯, 𝘪𝘵'𝘴 𝘢𝘣𝘰𝘶𝘵 𝘮𝘢𝘬𝘪𝘯𝘨 𝘣𝘦𝘵𝘵𝘦𝘳 𝘥𝘦𝘤𝘪𝘴𝘪𝘰𝘯𝘴, 𝘦𝘢𝘳𝘭𝘪𝘦𝘳.

Some of the most impactful applications today include 📉 dropout prediction, ⚠️ adverse event prediction, 🏥 site performance monitoring, and 🛡️ safety review. By analyzing patient data, site metrics, and clinical narratives, AI can help identify risks before they become costly delays, quality issues, or safety concerns.

The real value lies in moving from reactive monitoring to proactive oversight. Instead of waiting for problems to surface, clinical teams can focus attention where it's needed most, improving patient retention, prioritizing safety signals, and optimizing trial performance. As clinical trials continue to generate larger and more complex datasets, AI is becoming an essential tool for turning data into actionable insights.

Want to learn how AI is applied across real clinical trial workflows—from raw data to actionable insights?

🚨 Then join our 𝟐-𝐃𝐚𝐲 𝐇𝐚𝐧𝐝𝐬-𝐎𝐧 𝐎𝐧𝐥𝐢𝐧𝐞 𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩 𝐨𝐧 𝐀𝐩𝐩𝐥𝐢𝐞𝐝 𝐀𝐈 𝐢𝐧 𝐂𝐥𝐢𝐧𝐢𝐜𝐚𝐥 𝐓𝐫𝐢𝐚𝐥𝐬

Work through practical use cases covering data wrangling, exploratory analysis, predictive modeling, NLP on clinical text, and survival analysis techniques used in modern trials. Gain hands-on experience with methods used to optimize trial design, improve patient stratification, and predict outcomes.

📅 𝐃𝐚𝐭𝐞: June 20 – June 21, 2026
🕒 𝐓𝐢𝐦𝐞: 7:30 PM IST | 9:00 AM CDT
🎓 𝐅𝐨𝐫𝐦𝐚𝐭: Live + Hands-on Demonstrations

🔗 𝐑𝐞𝐠𝐢𝐬𝐭𝐞𝐫 𝐡𝐞𝐫𝐞: https://forms.gle/kPhv2e6buqdb5eD17

🌱 𝗨𝗻𝗹𝗼𝗰𝗸 𝘁𝗵𝗲 𝗽𝗼𝘄𝗲𝗿 𝗼𝗳 𝘁𝗿𝗮𝗻𝘀𝗰𝗿𝗶𝗽𝘁𝗼𝗺𝗶𝗰𝘀 and gain hands-on experience in 𝗣𝗹𝗮𝗻𝘁 𝗥𝗡𝗔-𝗦𝗲𝗾 𝗗𝗮𝘁𝗮 𝗔𝗻𝗮𝗹𝘆𝘀𝗶𝘀 𝘄𝗶𝘁𝗵 𝗥 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴!

Join our 𝟰-𝗱𝗮𝘆 𝗹𝗶𝘃𝗲 𝗼𝗻𝗹𝗶𝗻𝗲 𝘄𝗼𝗿𝗸𝘀𝗵𝗼𝗽 designed to take you through an end-to-end RNA-Seq workflow for plant stress research. Learn how to process raw sequencing data, perform differential expression analysis, visualize results, and derive meaningful biological insights using industry-relevant tools and R packages.

🔬 𝗪𝗵𝗮𝘁 𝘆𝗼𝘂’𝗹𝗹 𝗹𝗲𝗮𝗿𝗻:
✅ RNA-Seq experimental design and data preparation
✅ Read alignment, quantification, and normalization
✅ Differential expression analysis with 𝗗𝗘𝗦𝗲𝗾𝟮 & 𝗲𝗱𝗴𝗲𝗥
✅ Volcano plots, heatmaps, and transcriptomic data visualization
✅ Pathway enrichment and gene ontology analysis
✅ Biological interpretation of stress-responsive genes

📅 𝗗𝗮𝘁𝗲𝘀: July 20–23, 2026
⏰ 𝗧𝗶𝗺𝗲: 7:00 PM IST | 8:30 AM CDT
💻 𝗙𝗼𝗿𝗺𝗮𝘁: Live + Hands-on Online Workshop
🔗 𝗥𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗡𝗼𝘄: https://forms.gle/4bSsNJhZSLhVKsWG7

🎯 Ideal for students, researchers, plant scientists, and professionals looking to strengthen their RNA-Seq and transcriptomics analysis skills.

A key component of NGS success is Quality Control (QC). QC is crucial for identifying potential issues early in the library preparation and sequencing process, ensuring reliable and high-quality sequencing outcomes.

📚 Join our 6-week online program “𝑭𝒓𝒐𝒎 𝑺𝒂𝒎𝒑𝒍𝒆 𝒕𝒐 𝑺𝒆𝒒𝒖𝒆𝒏𝒄𝒆𝒓: 𝑨 𝑷𝒓𝒂𝒄𝒕𝒊𝒄𝒂𝒍 𝑮𝒖𝒊𝒅𝒆 𝒕𝒐 𝑵𝑮𝑺 𝑾𝒐𝒓𝒌𝒇𝒍𝒐𝒘𝒔” and master the 𝗲𝗻𝘁𝗶𝗿𝗲 𝗡𝗚𝗦 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲, from 𝗲𝘅𝗽𝗲𝗿𝗶𝗺𝗲𝗻𝘁𝗮𝗹 𝗱𝗲𝘀𝗶𝗴𝗻 to 𝗰𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝗱𝗮𝘁𝗮 𝗶𝗻𝘁𝗲𝗿𝗽𝗿𝗲𝘁𝗮𝘁𝗶𝗼𝗻 🧬🔬

Designed with a 𝗹𝗲𝗮𝗿𝗻-𝗯𝘆-𝗱𝗼𝗶𝗻𝗴 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵, this course offers dual mentorship, bridging 𝘄𝗲𝘁-𝗹𝗮𝗯 𝗽𝗿𝗼𝘁𝗼𝗰𝗼𝗹𝘀 and 𝗰𝗼𝗺𝗽𝘂𝘁𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗯𝗶𝗼𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗰𝘀 for a truly end-to-end experience 💻⚙️

Gain hands-on exposure to 𝗹𝗶𝗯𝗿𝗮𝗿𝘆 𝗽𝗿𝗲𝗽𝗮𝗿𝗮𝘁𝗶𝗼𝗻, 𝘀𝗲𝗾𝘂𝗲𝗻𝗰𝗶𝗻𝗴 𝘀𝘁𝗿𝗮𝘁𝗲𝗴𝗶𝗲𝘀, and downstream analysis including 𝗮𝗹𝗶𝗴𝗻𝗺𝗲𝗻𝘁, 𝘃𝗮𝗿𝗶𝗮𝗻𝘁 𝗰𝗮𝗹𝗹𝗶𝗻𝗴, and 𝗶𝗻𝘁𝗲𝗿𝗽𝗿𝗲𝘁𝗮𝘁𝗶𝗼𝗻 📊

Learn to generate 𝗵𝗶𝗴𝗵-𝗾𝘂𝗮𝗹𝗶𝘁𝘆 𝗡𝗚𝗦 𝗱𝗮𝘁𝗮, perform 𝘃𝗮𝗿𝗶𝗮𝗻𝘁 𝗮𝗻𝗮𝗹𝘆𝘀𝗶𝘀, and extract 𝗺𝗲𝗮𝗻𝗶𝗻𝗴𝗳𝘂𝗹 𝗯𝗶𝗼𝗹𝗼𝗴𝗶𝗰𝗮𝗹 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 relevant to research and clinical applications

🔗 𝗙𝗼𝗿 𝗺𝗼𝗿𝗲 𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗼𝗻 𝗼𝗻 𝘄𝗼𝗿𝗸𝘀𝗵𝗼𝗽 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲, 𝗰𝘂𝗿𝗿𝗶𝗰𝘂𝗹𝘂𝗺, 𝗮𝗻𝗱 𝘁𝗿𝗮𝗶𝗻𝗶𝗻𝗴 𝗿𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀, 𝗿𝗲𝗴𝗶𝘀𝘁𝗲𝗿 𝗵𝗲𝗿𝗲: https://forms.gle/SMexf9AGnvbNAGpy8

Secure your spot and build practical skills to advance in 𝗴𝗲𝗻𝗼𝗺𝗶𝗰𝘀, 𝗯𝗶𝗼𝗶𝗻𝗳𝗼𝗿𝗺𝗮𝘁𝗶𝗰𝘀, 𝗮𝗻𝗱 𝗰𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝗿𝗲𝘀𝗲𝗮𝗿𝗰𝗵 🚀

The 𝑪𝒆𝒏𝒕𝒓𝒂𝒍 𝑫𝒐𝒈𝒎𝒂 𝒐𝒇 𝑴𝒐𝒍𝒆𝒄𝒖𝒍𝒂𝒓 𝑩𝒊𝒐𝒍𝒐𝒈𝒚 outlines the flow of genetic information from DNA to RNA to protein. Each step in this process has its corresponding "omics" field:

⤷ 𝑮𝒆𝒏𝒐𝒎𝒊𝒄𝒔: The study of the entire genome of an organism.
⤷ 𝑻𝒓𝒂𝒏𝒔𝒄𝒓𝒊𝒑𝒕𝒐𝒎𝒊𝒄𝒔: The study of the complete set of RNA transcripts in an organism.
⤷ 𝑷𝒓𝒐𝒕𝒆𝒐𝒎𝒊𝒄𝒔: The study of the complete set of proteins in an organism.
⤷ 𝑴𝒆𝒕𝒂𝒃𝒐𝒍𝒐𝒎𝒊𝒄𝒔: The study of the complete set of small molecules in an organism.

𝐏𝐫𝐨𝐭𝐞𝐨𝐦𝐢𝐜𝐬 is particularly significant because proteins are the workhorses of cells, carrying out a vast array of functions. Understanding the proteome provides insights into:

⤷ Identifying proteins involved in disease processe
⤷ Developing new drugs that target specific proteins.
⤷ Tailoring treatments based on individual protein profiles.

Want to dive deeper into the exciting world of proteomics? Join us for 𝟒-𝐃𝐚𝐲 𝐎𝐧𝐥𝐢𝐧𝐞 𝐖𝐨𝐫𝐤𝐬𝐡𝐨𝐩 𝐨𝐧 𝐁𝐢𝐠 𝐃𝐚𝐭𝐚 𝐚𝐧𝐝 𝐏𝐫𝐨𝐭𝐞𝐨𝐦𝐢𝐜𝐬: 🦠 𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐢𝐧𝐠 𝐈𝐦𝐦𝐮𝐧𝐨𝐥𝐨𝐠𝐲 𝐰𝐢𝐭𝐡 𝐂𝐥𝐢𝐧𝐢𝐜𝐚𝐥 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡!

🔗 For more information on workshop structure, curriculum, and training resources, register here: https://forms.gle/dptrxdTm1J5G5WUN8

📅 Date: July 6 – July 9, 2026
⏰ Time: 7:30 PM IST | 9:00 AM CDT
📍 Location: Online