European Bioinformatics Institute | EMBL-EBI’s Post

Groundbreaking AI-powered antibiotic discovery! Researchers have harnessed AI to uncover new antibiotics within the global microbiome, marking a significant leap in our fight against antibiotic resistance. The team's innovative approach uses machine learning to analyze vast amounts of microbial genomic data from diverse ecosystems worldwide, identifying potential antimicrobial peptides at an unprecedented scale and speed. This breakthrough showcases AI's transformative potential in accelerating scientific discovery and addressing critical healthcare challenges. It's a prime example of how cutting-edge technology can revolutionize traditional research methods and open new avenues for drug development. As we continue to grapple with the growing threat of antibiotic-resistant infections, this research offers a promising path forward. It demonstrates the power of combining big data, AI, and biological insights to tackle complex global health issues. I'm eager to see how this approach evolves and potentially reshapes the landscape of antibiotic discovery. What are your thoughts on the role of AI in drug development? Have you encountered other instances where AI has driven significant advancements in healthcare or your field? #ArtificialIntelligence #HealthTech #DrugDiscovery #Innovation #Bioinformatics

𝐄𝐃𝐀 𝗖𝗮𝘀𝗲 𝗦𝘁𝘂𝗱𝘆: 𝗖𝗢𝗩𝗜𝗗-𝟭𝟵 𝗖𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝗧𝗿𝗶𝗮𝗹𝘀 In this case study, we dig deep into COVID-19 clinical trials using 𝐄𝐱𝐩𝐥𝐨𝐫𝐚𝐭𝐨𝐫𝐲 𝐃𝐚𝐭𝐚 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬 (𝐄𝐃𝐀). From understanding basic dataset structures to locating outliers and identifying relationships between variables, each step revealed more about the pandemic's challenges and the global response to it. 𝐇𝐞𝐫𝐞'𝐬 𝐰𝐡𝐚𝐭 𝐰𝐞 𝐚𝐜𝐡𝐢𝐞𝐯𝐞𝐝: 1.   𝐃𝐚𝐭𝐚𝐬𝐞𝐭 𝐄𝐱𝐩𝐥𝐨𝐫𝐚𝐭𝐢𝐨𝐧: We began with examining the shape, columns, and viewing the dataset's rows (n = 5, 15, 30), laying the groundwork for deeper analysis. 2.   𝐈𝐧-𝐝𝐞𝐩𝐭𝐡 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: Delving into column data types and leveraging info() and describe(), we painted a detailed picture of the clinical trials, uncovering the dataset's intricacies. 3.   𝐓𝐚𝐫𝐠𝐞𝐭𝐞𝐝 𝐐𝐮𝐞𝐫𝐢𝐞𝐬: Using loc and iloc, we extracted precise information, from trial statuses to specific NCT Numbers, peering into the dataset’s rich details. 4.   𝐌𝐢𝐬𝐬𝐢𝐧𝐠 𝐕𝐚𝐥𝐮𝐞𝐬 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: Identifying and documenting missing data illuminated the dataset's integrity, guiding our strategies for imputation and further analysis. 5.   𝐃𝐮𝐩𝐥𝐢𝐜𝐚𝐭𝐞 𝐑𝐨𝐰𝐬: Through identifying duplicates, we gained insights into data entry consistency and dataset uniqueness. 6.   𝐂𝐨𝐧𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐒𝐭𝐚𝐭𝐞𝐦𝐞𝐧𝐭𝐬 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬: This allowed us to quantify aspects such as enrollment numbers, trial statuses, and the focus on COVID-19, drawing significant conclusions from our conditions. A special thanks to my group mates Muhammad Tabish S., Mahad Ahmed, and Amna Shahzad. Their dedication and unique perspectives were instrumental in this project’s success. I’m also immensely grateful to atomcamp for creating such a conducive learning environment. #DataScience #EDA #COVID19 #ClinicalTrials #DataAnalysis #atomcamp #Teamwork #LinkedInFamily

📞Calling all Science Enthusiasts, Professionals, and Researchers! 🌍 Let’s build a stronger, more connected Science community together! I’m excited to announce the launch of our Telegram group designed to foster collaboration and knowledge-sharing across multiple fields of science and technology. 🎯 What’s in it for you? 1. Lifescience Jobs – Stay updated with the latest job opportunities in life sciences. 2. Food Science & Technology – Dive into the emerging trends shaping food innovation. 3. Science Communication – Learn how to effectively communicate complex ideas to diverse audiences. 4. Biotechnology Reference Books – Access invaluable resources for biotech learning and research. 5. Digital Marketing – Discover how digital marketing is transforming scientific outreach. 6. New Trends in AI – Explore cutting-edge AI developments impacting science and technology. 🔗 Join the group to: - Network with like-minded professionals - Share your expertise - Stay updated with the latest trends Let’s harness the power of community and innovation to drive change and push boundaries in science! Whether you’re a student, researcher, or professional in the field, there’s something valuable here for everyone. 🚀 🔗 https://lnkd.in/dVG8FtyF 🧠 Let's make science more collaborative! Feel free to share this post or tag someone who’d benefit from this amazing community. Let’s build the Science community more stronger! 💪 #Lifescience #FoodScience #SciComm #Biotechnology #DigitalMarketing #AI #ScienceCommunity #Networking #Collaboration #Innovation

🚀 Take your bioinformatics workflows to the next level – for free! With NF-Copilot™ Free, bioinformaticians can collaborate effortlessly without worrying about user limits or costs. At Lifebit, we’re committed to supporting innovation at all levels – from grassroots research teams to major organizations. Discover how NF-Copilot™ Free is fostering collaboration and driving discoveries. Start exploring today: https://bit.ly/3Z8dNYO #Bioinformatics #NF-Copilot #Lifebit

My first post on Substack! Sharing my thoughts on the recent news around #23andMe from a #Lupus #ResearchParticipant's perspective. Take a read, and let me know your thoughts. What would you do in this case, how would you feel? https://lnkd.in/gQwtGvrZ 🤔 Andrea Downing Michael Millenson Michael Mittelman Valencia Robinson Stacy Hurt 🌻 Grace Cordovano, PhD, BCPA Grace Vinton Matthew Zachary Alice Rathjen Michael O'Reilly Ro Khanna Lam Nguyen #ResearchParticipant #Substack #FindingBalance #LupusResearch

AuthorAID will be hosting a webinar on Introduction to Open Science 🔓 🎙 Speakers: Lamis Elkheir and Emmanuel Boakye 🗓️ Date: Fri, Sep 27, 2024, 13:00 - 14:30 EAT 🔗 Registration link: https://lnkd.in/emp9DQpB Don't miss out this great opportunity to learn about the values, principles, pillars, advantages, and global impact of Open Science. #OpenScience #Webinar #ResearchEquity AuthorAID

We're proud to have collaborated with Tim Errington from The Center for Open Science in our recent webinar! Check it out if you want to learn what challenges face #openscience and #reproducibility and improve the credibility of your #research. Watch it now → https://buff.ly/3SB7IRr #Reproducibility #ReproducibilityCrisis #DataSharing #OpenData #OpenAccess

There’s no better way to start the week than at the Bioinformatics & IT Strategy Meeting happening right now at Le Meridien Boston Cambridge! Today, leaders and innovators in bioinformatics and IT are coming together to explore groundbreaking technologies and forge new partnerships. Stay tuned as we bring you updates from the event, highlight key discussions, and share insights from some of the brightest minds in the field. Don’t miss out on the chance to see how these collaborations today will lead to the innovations of tomorrow! #Bioinformatics #ITStrategy #BostonEvents #Networking #Collaboration #HealthcareInnovation

🎉 Exciting Announcement! 🎉 My research paper "Dengue Prediction using Machine Learning" has been published in IEEE! 📚🔍 Key Points: Problem Statement: Our study addresses the challenge of accurately predicting dengue outbreaks, crucial for effective public health strategies. Methodology: We employed advanced machine learning techniques and thorough data analysis to develop a robust predictive model. Predictive Accuracy: The model showcased high accuracy in forecasting dengue outbreaks, aiding in timely intervention and resource allocation. Public Health Impact: Accurate prediction can lead to proactive measures, potentially reducing the impact of dengue outbreaks on communities. Collaborative Effort: Grateful for the contributions of my co-authors, collaborators, and research partners who made this work possible. Publication Venue: Honored to have our paper published in IEEE, a prestigious platform for scientific research. Future Directions: Excited about potential future applications and research avenues stemming from this work. Gratitude: Thank you to the academic community, funding agencies, and institutions for their support and encouragement. You can access the full paper here: https://lnkd.in/gx3giMqu #IEEE #ResearchPaper #DenguePrediction #MachineLearning #PublicHealth

As part of our ongoing commitment to fostering an open and efficient research environment, we've detailed the transformative impact of Persistent Identifiers (PIDs) in our latest blog. Discover how PIDs: ✅ Enhance data integrity and transparency ✅ Facilitate seamless collaborations across borders ✅ Support the unique identification and proper attribution of academic work Special thanks to experts from MoreBrains Cooperative, ORCID, ROR - Research Organization Registry, Crossref, and DataCite for their invaluable contributions. This blog not only sheds light on the fundamental importance of PIDs but also underscores the critical adoption rates, as seen with ORCID IDs embedded in systems like Altum, Inc.’s Proposal Central. 🔗 Read the full blog post here and learn how integrating PIDs can revolutionize your research practices: https://lnkd.in/es6WH6ZZ #ResearchInnovation #DigitalTransformation #ScholarlyPublishing #PersistentIdentifiers #Altum #PIDs